LERNEN UND ADAPTATION IM VISUELLEN …elib.suub.uni-bremen.de/diss/docs/00010953.pdf · genannten...

LERNEN UND ADAPTATION IM VISUELLEN SYSTEM DES MENSCHEN

Sven Wischhusen

vorgelegt dem Fachbereich 2 (Biologie/Chemie) der Universität Bremen

als

DISSERTATION

zur Erlangung des akademischen Grades

DOKTOR DER NATURWISSENSCHAFTEN (Dr. rer. nat.)

i

Inhaltsverzeichnis

Gutachter .................................................................................................................................. iiEigenanteil und Erklärung...................................................................................................... iiÜbersicht über Publikationen und Manuskripte .................................................................iiiDanksagung.............................................................................................................................. iv

1. Einleitung .............................................................................................................................. 11.1 Ein erster Überblick ......................................................................................................... 1 1.2 Plastizität, Lernen und Adaptation: Begriffsabgrenzung und Beispiele .......................... 2 1.3 Neuronale Korrelate der Sensomotorik............................................................................ 8 1.4 Sensomotorische Plastizität am Beispiel der Prismenadaptation ................................... 11

2. Allgemeine Methodik ......................................................................................................... 152.1 Verhaltensuntersuchungen und Psychophysik ............................................................... 15 2.2 Sensomotorische Aufgaben: Zeige- und Wurfbewegungen........................................... 16 2.3 Datenauswertung............................................................................................................ 19

3. Motivation und Zusammenfassung der Studien ............................................................. 203.1 Motivation der Studien................................................................................................... 20 3.2 Zusammenfassung von Studie 1..................................................................................... 22 3.3 Zusammenfassung von Studie 2..................................................................................... 23 3.4 Zusammenfassung von Studie 3..................................................................................... 25

4. Fazit ..................................................................................................................................... 27

5. Studie 1 Incomplete visuomotor adaptation despite extensive training..................... 28

6. Studie 2 Task-specificity of prism adaptation: no transfer from pointing to throwing.................................................................................................................................................. 50

7. Studie 3 Effects of training conditions on spatial generalization of prism adaptation.................................................................................................................................................. 71

Abkürzungsverzeichnis.......................................................................................................... 92

Literaturverzeichnis............................................................................................................... 93

ii

Gutachter

1. Gutachter: Professor Dr. Manfred Fahle, Universität Bremen

2. Gutachter: Professor Dr. Ben Godde, Jacobs University Bremen

Tag des Kolloquiums: 17.04.2008

Eigenanteil und Erklärung

Die wissenschaftlichen Untersuchungen, auf denen diese Dissertation beruht, habe ich

selbständig durchgeführt und ausgewertet. Die vorliegenden Manuskripte habe ich

eigenständig verfasst und lediglich die endgültige Fassung mit meinem Betreuer und

Mitautoren, Herrn Professor Manfred Fahle, überarbeitet.

Ich erkläre hiermit, dass ich die Arbeit ohne unerlaubte fremde Hilfe angefertigt und keinerlei

anderen Quellen und Hilfsmittel als die angegebenen benutzt habe. Ferner sind alle wörtlich

oder inhaltlich anderen Werken entnommenen Stellen im Text als solche kenntlich gemacht.

Sven Wischhusen

Bremen, 29.02.2008

iii

Übersicht über Publikationen und Manuskripte

Die vorliegende Dissertation beruht kumulativ auf folgenden drei Manuskripten, die als

Fachartikel zur Veröffentlichung in internationalen neurowissenschaftlichen Fachzeitschriften

eingereicht wurden:

Fachartikel

Wischhusen, S. & Fahle, M. (2008). Incomplete visuomotor adaptation despite extensive training. Vision Research (eingereicht).

Wischhusen, S. & Fahle, M. (2008). Task-specificity of prism adaptation: no transfer from pointing to throwing. Experimental Brain Research (eingereicht).

Wischhusen, S. & Fahle, M. (2008). Effects of training conditions on spatial generalization of prism adaptation. Journal of Motor Behavior (eingereicht).

Konferenzbeiträge

Fahle, M., Wischhusen, S., & Spang, K. (2005). Prism adaptation by gain control. Perception, 34 (Suppl.), 28th European Conference on Visual Perception, A Coruña, Spain.

Wischhusen, S. & Fahle, M. (2005). Prism adaptation: no generalization from one visuomotor task to another. Workshop “Preemptive Perception”, Hanse Institute for Advanced Study, Delmenhorst, Germany.

Wischhusen, S. & Fahle, M. (2006). Is prism adaptation complete? 5th Forum of European Neuroscience, Vienna, Austria.

Fahle, M., Eggert, T., & Wischhusen, S. (2006). Perceptual learning in a visual masking task. Workshop “Visual Masking and the Dynamics of Vision and Consciousness”, Hanse Institute for Advanced Study, Delmenhorst, Germany.

Fahle, M., Wischhusen, S., & Spang, K. (2006). Prism adaptation and normalization of eye-hand coordination. Perception, 35 (Suppl.), 29th European Conference on Visual Perception, St. Petersburg, Russia.

Fahle, M., Eggert, T., Wischhusen, S., & Spang, K. (2006). Perceptual learning with masked stimuli. Perception, 35 (Suppl.), 29th European Conference on Visual Perception, St. Petersburg, Russia.

Wischhusen, S., Schütze, C., & Fahle, M. (2007). Prism adaptation in a patient with damage to the right parietal cortex – a case study. 31st Göttingen Neurobiology Conference, Göttingen, Germany.

iv

Danksagung

Zuallererst gilt mein ganz herzlicher Dank meinem Betreuer, Herrn Professor Manfred Fahle,

für die interessante und lehrreiche Zeit in seiner Arbeitsgruppe und dafür, dass er mir die

Möglichkeit gegeben hat, meine Doktorarbeit zu schreiben und dabei einen tiefen Einblick in

die naturwissenschaftliche Forschung zu bekommen. Für die Unterstützung und die

konstruktive Kritik während der gesamten Zeit bedanke ich mich sehr!

Darüber hinaus danke ich Herrn Professor Ben Godde von der Jacobs University Bremen

dafür, dass er sich bereit erklärt hat, seinen Sachverstand als „zweiter“ Gutachter für diese

Arbeit zur Verfügung zu stellen.

Mein besonderer Dank gilt den Kollegen der Arbeitsgruppe „Human-Neurobiologie“ am

Institut für Hirnforschung, die im Laufe der Zeit zu guten Freunden geworden sind: Dani

Högl, Sirko Straube, Cathleen Grimsen und Tina Friederich.

Ein herzliches Dankeschön geht auch an die Mitarbeiter und Studenten aus der Arbeitsgruppe,

die mich unterstützt und mir bei allen kleinen und großen Problemen stets geholfen haben.

Des Weiteren möchte ich mich bei allen freiwilligen Versuchspersonen, die mit vollem

Einsatz und viel Geduld an den Experimenten teilgenommen haben, bedanken. Diese Arbeit

hat mir immer sehr viel Freude bereitet!

Ein großer Dank geht aber auch an meine Eltern und meine Familie in Worpswede und umzu,

die mich einerseits immer wieder auf den „Boden der Tatsachen“ zurückgebracht haben,

deren echter Unterstützung ich mir jedoch während der ganzen Zeit immer sicher sein konnte.

Außerdem danke ich meinen Freunden Alex, Jan-Dirk, Jan Christoph, Jörg und Niels einfach

dafür, dass sie immer da und für allerlei lustige Aktionen zu haben waren!

Einleitung 1

1. Einleitung

1.1 Ein erster Überblick

Nach einem Gegenstand – beispielsweise einer Kaffeetasse auf einem Tisch – zielgerichtet zu

greifen ist eigentlich keine komplizierte Angelegenheit. Oder doch? An der Ausführung einer

solchen Aufgabe sind ganz verschiedene Gehirnsysteme beteiligt: Zunächst muss das Objekt

visuell lokalisiert werden. Die visuelle Information über die Position des Objekts wird in

einem nächsten Schritt mit der sensorisch-propriozeptiven Information über die aktuelle

Körperposition in Bezug zum Objekt abgeglichen und für die Bewegungsplanung

umgewandelt („sensomotorische Transformation“). Auf der Basis des Abgleichens

sensorischer und motorischer Koordinaten kann die Bewegung schließlich geplant und

ausgeführt werden (Krakauer & Ghez, 2000). Dass es im Normalfall keine große Mühe

bereitet, nach einer Kaffeetasse zu greifen, begründet sich aus der funktionellen Kopplung

von Sensorik und Motorik (kurz: Sensomotorik1), einer Kopplung, die so zuverlässig und

automatisiert ist, dass wir uns über die komplexe Leistung, die das Gehirn für die erfolgreiche

Ausführung einer Bewegung vollbringt, in der Regel nicht bewusst sind.

Diese funktionelle Kopplung von Sensorik und Motorik kann bei gesunden menschlichen

Versuchspersonen gezielt experimentell manipuliert werden, beispielsweise mit Hilfe einer

Prismenbrille, durch welche die Versuchsperson die visuelle Welt als seitlich versetzt

wahrnimmt. Aufgrund der Prismenbrille kommt es zu einer Nicht-Übereinstimmung zwischen

sensorischen und motorischen Koordinaten mit der Folge, dass Bewegungen zunächst in

Richtung der prismatischen Versetzung abweichen (vgl. Redding et al., 2005). Um in dem

genannten Beispiel zu bleiben: Versuchspersonen würden es mit Prismenbrille zunächst nicht

schaffen, die Kaffeetasse zielgerichtet zu greifen.

Eine weitere wichtige Eigenschaft des Gehirns ist die Fähigkeit, seine Organisation kurzfristig

und flexibel neuen Gegebenheiten anzupassen: Diese Neuroplastizität ermöglicht somit, dass

die sensomotorischen Koordinaten während des Tragens einer Prismenbrille neu miteinander

abgeglichen und gekoppelt werden. Im Verlauf dieses Prozesses werden die Bewegungen an

die neuen Bedingungen angepasst, d.h. es kommt zu einer sensomotorischen Adaptation.

1 Kurzer Ausflug in die Nomenklatur: Neben dem Begriff der „Sensomotorik“, der die funktionelle Verknüpfung von sensorischer Information (visuell, auditiv, somatosensorisch, propriozeptiv) und Motorik beschreibt, findet sich auch der Begriff der „Visuomotorik“, bei dem die Verknüpfung speziell von visueller Information und Motorik hervorgehoben wird (vgl. Birbaumer & Schmidt, 2003).

Einleitung 2

Plastische Prozesse bilden damit die Grundlage der sensomotorischen Adaptation, in deren

Verlauf die Bewegungen trotz der (experimentellen) Manipulation eine immer größere

Genauigkeit aufweisen. Die Kaffeetasse könnte folglich nach einigen Versuchen trotz der

Prismenbrille zielgerichtet ergriffen werden.

Prismenadaptation ist ein Beispiel für einen Adaptationsprozess im sensomotorischen

System. Die Untersuchung der Mechanismen und Charakteristika dieses

Adaptationsprozesses kann wichtige Antworten auf die Frage liefern, in welcher Art Sensorik

und Motorik funktionell miteinander verknüpft sind und welches die Merkmale und Faktoren

der Neuroplastizität im sensomotorischen System sind. Es geht folglich darum, wie und mit

welchen Mechanismen es das Gehirn schafft, neuronale Repräsentationen schnell neuen

Wahrnehmungsbedingungen anzupassen.

In der vorliegenden Arbeit wurden verschiedene Ausprägungsformen von Neuroplastizität im

visuellen System – Lernen und insbesondere Adaptation – unter Verwendung des

Prismenadaptations-Paradigmas2 bei gesunden menschlichen Versuchspersonen

psychophysikalisch untersucht. Zunächst sollen jedoch wichtige Begriffe wie Plastizität,

Lernen und Adaptation sprachlich voneinander abgegrenzt und anhand von Beispielen in

einen konzeptuellen Zusammenhang gestellt werden.

1.2 Plastizität, Lernen und Adaptation: Begriffsabgrenzung und Beispiele

Plastizität

In einer sich fortlaufend ändernden Umwelt muss das zentrale Nervensystem (ZNS) die

Fähigkeit aufweisen, seine strukturelle und funktionelle Organisation stets diesen neuen

Umweltbedingungen anzugleichen, um dem Organismus angepasstes Verhalten zu

ermöglichen. Diese Eigenschaft des Gehirns, sich neuen Bedingungen anzupassen, bezeichnet

man als neuronale Plastizität, kurz Neuroplastizität (Sterr, 2008). Neuroplastische Prozesse

sind insbesondere in Arealen der Großhirnrinde (Cortex) untersucht und nachgewiesen

worden; eine Übersicht zur corticalen Neuroplastizität geben Buonomano & Merzenich

(1998). Dabei treten Veränderungen sowohl auf der Ebene von Synapsen und Neuronen als

auch von größeren Neuronenverbänden auf. Sterr (2008) unterscheidet Ebenen molekularer, 2 Schon an dieser Stelle sei darauf hingewiesen, dass die plastischen Veränderungen im Gehirn, die im Zusammenhang mit der Prismenadaptation auftreten, nicht auf das visuelle System im engeren Sinne, d.h. auf die frühen visuellen Areale (V1, V2 etc.), beschränkt sondern vielmehr auch in „höheren“ multimodalen sowie motorischen Arealen zu finden sind.

Einleitung 3

struktureller und funktioneller Plastizität. Neuronale Veränderungen, die im Zusammenhang

mit Entwicklung und Reifung (Entwicklungsplastizität), nach Läsionen des ZNS sowie durch

Erfahrung und Übung auftreten, sind folglich nur aufgrund plastischer Prozesse im Gehirn

möglich.

Lernen – allgemein

Die Anpassungsfähigkeit des Gehirns äußert sich u.a. durch Lernen, worunter man ganz

allgemein den Erwerb von Fähigkeiten und Fertigkeiten durch Übung versteht. Menzel (2001,

S. 504) definiert Lernen als „[…] die Fähigkeit, Verhalten aufgrund individueller Erfahrung

so zu ändern, daß es veränderten Situationen besser angepaßt ist“ und unterstreicht damit den

biologischen Anpassungswert von Lernen für den Organismus. Lernen umfasst eine

längerfristige Verhaltensanpassung aufgrund von Erfahrung, wobei die funktionelle

Grundlage von Lernprozessen in der Plastizität der beteiligten neuronalen Strukturen

begründet ist. Je nach untersuchter neurobiologischer Domäne unterscheidet man zwischen

kognitivem, perzeptuellem und motorischem Lernen, wobei die beiden letzteren für die

vorliegende Arbeit von größerer Bedeutung sind.

Perzeptuelles Lernen

Perzeptuelles Lernen, eine andauernde Verbesserung der Wahrnehmungsleistung durch

Übung bzw. Erfahrung, verdeutlicht, dass auch (frühe) sensorische Areale des Gehirns beim

erwachsenen Menschen durch Übung modifizierbar und damit plastisch sind (Fahle, 2002).

Perzeptuelle Lernprozesse bei Erwachsenen, die mit neuronalen Veränderungen auf frühen

Ebenen der sensorischen Informationsverarbeitung einhergehen müssen, waren insofern eine

Überraschung, weil lange Zeit die Auffassung vertreten wurde, dass plastische

Veränderungen der sensorischen Cortices auf ein relativ kleines Zeitfenster während der

frühen Individualentwicklung – die sog. „kritische Periode“ – beschränkt seien (Fahle, 2002).

Perzeptuelles Lernen liefert damit den experimentellen Nachweis dafür, dass auch bei der

sensorischen Informationsverarbeitung im adulten Gehirn plastische Prozesse auftreten

können, die zu dauerhaften Veränderungen der Wahrnehmungsleistung führen und damit der

o.g. Definition von Lernen entsprechen.

Perzeptuelles Lernen wurde beim Menschen insbesondere im visuellen (siehe Fahle, 2004;

Gilbert et al., 2001; Karmarkar & Dan, 2006; Seitz & Watanabe, 2005), somatosensorischen

(z.B. Godde et al., 2000; Hodzic et al., 2004; Pleger et al., 2003) sowie im auditorischen

System (siehe Dahmen & King, 2007) mit psychophysikalischen und neurophysiologischen

Einleitung 4

Methoden untersucht; hierbei konnten durch Lernen induzierte neuronale Veränderungen in

den frühen bzw. primären corticalen sensorischen Projektionsarealen (V1, S1 und A1) bei

entsprechenden sensorischen Aufgaben nachgewiesen werden.

Die durch perzeptuelles Lernen hervorgerufenen Verbesserungen der Wahrnehmungsleistung

weisen häufig eine sehr hohe Spezifität für die trainierten Reiz-Eigenschaften auf (z.B.

Orientierung bzw. Position des Reizes). Diese Spezifität ist ein starker Hinweis darauf, dass

die neuronalen Korrelate des perzeptuellen Lernens in frühen sensorischen Arealen zu finden

sind, da hier einfache Reiz-Merkmale in räumlich geordneter Form repräsentiert werden und

diese frühen Stufen der sensorischen Informationsverarbeitung ein günstiges Signal-zu-

Rausch-Verhältnis aufweisen (Fahle, 2004; 2005; für eine alternative Erklärung siehe Mollon

& Danilova, 1996). Neuronale Korrelate perzeptuellen Lernens finden sich aber auch in

„späteren“ sensorischen Arealen, wobei die Selektion der entsprechenden Areale durch Top-

Down-Modulationen entsprechend den Erfordernissen der sensorischen Aufgabe vermittelt

wird (Fahle, 2004).

Motorisches Lernen

Auch im motorischen System, das die Ausführung zielgerichteter Bewegungen plant und

steuert, finden Funktionsanpassungen durch Lernen statt: Motorisches Lernen ist, ähnlich wie

perzeptuelles Lernen, implizit, d.h. der Lernprozess läuft beim Lernenden unbewusst ab

(Konczak, 2003). Dabei kann motorisches Lernen allerdings nicht isoliert betrachtet werden,

da immer eine enge Verknüpfung zwischen sensorischer Informationsverarbeitung und

Bewegungsausführung besteht. Die Unterscheidung zwischen perzeptuellem und

motorischem Lernen ist im Prinzip konzeptuell und zeigt an, auf welchem Gehirnsystem

(sensorisch vs. motorisch) der Untersuchungsschwerpunkt liegt; im praktisch-experimentellen

Zusammenhang kommt es dagegen immer zum sensomotorischen Lernen (vgl. Konczak,

2003). Hierzu passt auch die Beobachtung, dass sowohl beim perzeptuellen als auch beim

motorischen Lernen auf der physiologischen Ebene ganz ähnliche Mechanismen wirksam

sind, was darauf hindeutet, dass beide Lernprozesse auf gleichen neuronalen

Funktionsprinzipen beruhen (Paz et al., 2004).

Welches sind die Charakteristika motorischen Lernens? Während motorische Reflexe und

einfache Bewegungsprogramme3 im Genom eines Organismus encodiert sind, setzen

komplexere motorische Verhaltensweisen in einer wechselnden Umwelt die fortlaufende 3 Ein Bewegungsprogramm, die zeitliche Abfolge von motorischen Kommandos, führt letztlich zur Bewegung eines bestimmten motorischen Effektors, z.B. des Arms (Shadmehr & Wise, 2005).

Einleitung 5

Anpassung und Erweiterung von bestehenden Bewegungsprogrammen voraus. Laut

Shadmehr & Wise (2005), die als Modell Reich- und Zeigebewegungen des Arms verwenden,

umfasst motorisches Lernen neben a) der Erweiterung des Bewegungsrepertoires um neue

Fertigkeiten (engl. „skill acquisition“) auch b) die Modifikation bzw. Anpassung eines bereits

bestehenden Bewegungsprogramms an neue Bedingungen (engl. „motor adaptation“), wobei

beide Prozesse zur Stabilität und Kontrolle der Bewegung beitragen.

Während beim perzeptuellen Lernen Wahrnehmungsleistungen durch Übung verbessert

werden und damit zum „adaptiven“ Verhalten des Organismus beitragen, stehen beim

motorischen Lernen neue bzw. angepasste Bewegungsprogramme im Vordergrund, die ein

effizienteres Verhalten ermöglichen. Anders ausgedrückt: Wird beim perzeptuellen Lernen

die Informationsverarbeitung des sensorischen Eingangs optimiert, kommt es beim

motorischen Lernen zu Verbesserungen des motorischen Ausgangs bzw. der Ausführung

einer Bewegung.

Die von Shadmehr & Wise (2005) vorgenommene Unterscheidung zwischen dem Erwerb

neuer motorischer Fertigkeiten einerseits und motorischer Adaptation andererseits ist insofern

sinnvoll, als es bei der motorischen Adaptation zur Anpassung eines vorhandenen

Bewegungsprogramms an neue externe Bedingungen kommt, d.h. die Leistungsfähigkeit des

motorischen Systems wird bei veränderten Bedingungen durch adaptive Prozesse

wiederhergestellt. Shadmehr & Wise (2005, S. 47): „Adaptation involves changes in motor

performance that allow the motor system to regain its former capabilities in altered

circumstances“. Der Prozess der motorischen Adaptation gewährleistet folglich eine

erfolgreiche Bewegungsausführung unter veränderten Bedingungen.

Welcher Art können diese veränderten „externen“ Bedingungen sein? Experimentell kann die

erfolgreiche Bewegungsausführung durch Prismen, durch welche die visuelle Welt

beispielsweise seitlich versetzt wahrgenommen wird, gestört werden. Infolge der durch die

Prismen verursachten Manipulation des sensomotorischen Systems weichen zielgerichtete

Armbewegungen zunächst ab, aber im Verlauf der Adaptation wird die Genauigkeit der

Armbewegungen wiederhergestellt (siehe Abschnitt 1.4). Während dieses Prozesses wird

keine neue motorische Fertigkeit hervorgebracht, sondern ein bestehendes

Bewegungsprogramm wird an neue (sensomotorische) Bedingungen angepasst, um

zielgerichtete und präzise Armbewegungen trotz der Prismen zu ermöglichen. Darüber hinaus

können Adaptationsprozesse unter Verwendung externer Kraftfelder (engl. „force field

adaptation“) oder mit Hilfe von rotierter visueller Rückmeldung (engl. „rotation adaptation“)

untersucht werden (Shadmehr & Wise, 2005).

Einleitung 6

Adaptation: Motorisch, perzeptuell, sensomotorisch

Ähnlich wie der Begriff „Lernen“ wird auch der Begriff „Adaptation“ in verschiedenen

Kontexten und auf ganz verschiedene neurobiologische Phänomene angewandt, weshalb eine

einheitliche Definition schwierig ist. Ganz allgemein versteht man unter Adaptation eine

kurzfristige Anpassung an neue Bedingungen (Wade & Verstraten, 2005), was gut mit der

o.g. Begriffsabgrenzung von motorischer Adaptation zu vereinen ist. Eine sensorische

Adaptation (z.B. Licht-Adaptation) tritt dagegen durch eine längere sensorischer Stimulation

auf und verschiebt den Arbeitsbereich eines biologischen Sensors (Palmer, 1999). Eine

perzeptuelle Adaptation betrifft eine Veränderung des Perzepts, d.h. des subjektiven

Wahrnehmungsinhalts (z.B. Bewegungsnacheffekt, siehe Huk et al., 2001; Ibbotson, 2005)

oder beeinflusst die sensomotorische Integration, wie z.B. bei der Prismenadaptation (Wade

& Verstraten, 2005).

Aus dieser Einleitung ergibt sich in Bezug auf die Prismenadaptation ein konzeptuelles

Problem: Autoren, die die perzeptuellen Veränderungen infolge der Prismenadaptation

betonen, sehen in dem Prozess ein Beispiel für eine perzeptuelle Adaptation (z.B. Palmer,

1999; Wade & Verstraten, 2005), während Autoren, die mit adaptiven motorischem

Veränderungen (z.B. Shadmehr & Wise, 2005) argumentieren, den Prozess eher in den

Bereich der motorischen Adaptation einordnen. Für beide Standpunkte gibt es experimentelle

Belege, wobei eine rein perzeptuelle Perspektive die starke motorische Komponente der

Adaptation außer Acht lässt, während eine rein motorische Betrachtungsweise vernachlässigt,

dass während der Prismenadaptation auch Veränderungen im perzeptuellen System auftreten

können.

Prismenadaptation ist folglich ein gutes Beispiel für einen integrativen biologischen

Adaptationsprozess, der sich genau an der Schnittstelle von Wahrnehmungssystem und

Motorik befindet und sich daher weder ausschließlich in die perzeptuelle noch in die

motorische Domäne einordnen lässt – vielmehr sind beide Systeme an diesem

Adaptationsprozess beteiligt. Um der Tatsache gerecht zu werden, dass sowohl im sensorisch-

perzeptuellen – insbesondere im visuellen – System als auch im motorischen System

plastische Veränderungen wirksam werden können, wird Prismenadaptation in der

vorliegenden Arbeit als sensomotorischer Adaptationsprozess verstanden, der eine durch

Prismen induzierte Störung der Sensomotorik kurzfristig und schnell kompensiert.

Was unterscheidet sensomotorische Adaptation von sensomotorischem Lernen? Ein

wesentlicher Unterschied betrifft die Zeitskalen, auf denen beide Prozesse operieren:

Einleitung 7

Während es durch Lernen zu länger andauernden Veränderungen in der neuronalen

Verarbeitung kommt, wird das sensomotorische System durch Adaptation kurzfristig (im

Zeitbereich von wenigen Sekunden bis Minuten) neuen Bedingungen angepasst. Der

Adaptationsmechanismus operiert flexibel innerhalb eines kurzen Zeitfensters, um die

ursprüngliche Leistungsfähigkeit des Systems wiederherzustellen.

Ein wesentliches Charakteristikum von Adaptationsprozessen – seien sie sensorisch,

perzeptuell oder motorisch – ist das Auftreten sog. Nacheffekte infolge der Adaptation

(Palmer, 1999; Wade & Verstraten, 2005). Während das Lernen neuer perzeptueller oder

motorischer Fertigkeiten nicht dazu führt, dass nach „Abschluss“ des Lernens Nacheffekte

auftreten, ist eine Adaptation an neue Bedingungen immer mit einer De-Adaptation

verbunden (Nacheffekt) sobald die alten Bedingungen wiederhergestellt sind (Shadmehr &

Wise, 2005). Nacheffekte zeigen somit an, dass der Adaptationsprozess auf einen aktuellen

Kontext ausgerichtet ist.

Auch bei der Prismenadaptation tritt ein negativer Nacheffekt auf, d.h. zielgerichtete

Armbewegungen weichen zunächst in der dem Prismeneffekt entgegen gesetzten Richtung ab

(Fernandez-Ruiz & Diaz, 1999; Harris, 1965; Redding et al., 2005). Der durch die

Prismenadaptation hervorgerufene Nacheffekt weist ferner darauf hin, dass der

Adaptationsprozess nicht ausschließlich auf kognitiven Mechanismen, einer „bewussten“

Korrektur, beruht (Palmer, 1999): Obwohl nach dem Entfernen der Prismen die

ursprünglichen sensomotorischen Bedingungen wiederhergestellt sind, weichen die

Bewegungen in der Gegenrichtung ab, was darauf hinweist, dass durch die Prismenadaptation

ein neuer funktioneller Abgleich („Verrechnung“) von sensorischen und motorischen

Koordinaten stattgefunden hat (s.u.).

Diese kurzfristige und schnelle Anpassung an neue sensomotorische Bedingungen

charakterisiert den Prozess der Prismenadaptation. Dass durch längerfristiges

sensomotorisches Training unter Verwendung von Prismen neben Adaptations- auch

„klassische“ Lernprozesse aktiviert werden, die zu einer neuen Fertigkeit führen, machen die

Ergebnisse von Martin et al. (1996b) deutlich. In dieser psychophysikalischen Studie wurde

gezeigt, dass menschliche Versuchspersonen nach mehreren Wochen Training zwischen

Bedingungen mit und ohne Prismenbrille unmittelbar wechseln konnten, d.h. es war ihnen

möglich, je nach Kontext das passende Bewegungsprogramm auszuwählen. Nach dem

Training waren weder Prismen- noch Nacheffekt zu beobachten, was den Schluss nahe legt,

dass die Versuchspersonen durch sensomotorisches Lernen zwischen den Bedingungen mit

und ohne Prismen hin- und herwechseln konnten.

Einleitung 8

Diese Ergebnisse verdeutlichen, dass der Übergang zwischen Adaptation und Lernen im

sensomotorischen System fließend ist und sich beide Prozesse gegenseitig bedingen. In den

Untersuchungen der vorliegenden Arbeit spielen durch Lernen bedingte Veränderungen des

sensomotorischen Systems eine untergeordnete Rolle; vielmehr wurden die kurzfristigen

Anpassungsmechanismen untersucht, was als Prismenadaptation bezeichnet werden soll.

1.3 Neuronale Korrelate der Sensomotorik

Verschiedene sensorische (insbesondere visuelle), sensomotorische und motorische Areale

des Gehirns tragen zur Prismenadaptation bei. In diesem Abschnitt werden die neuronalen

Korrelate des sensomotorischen Systems daher kurz vorgestellt.

Analyse durch das visuelle System

Die Ausführung einer zielgerichteten visuell-geführten Bewegung zu einem Objekt ist

unmittelbar mit der sensorischen Analyse und Lokalisation des Objekts im Raum verknüpft

(Sensomotorik, s.o.). Die räumliche Lokalisation ist im Wesentlichen eine Funktion des

visuellen Systems, da dieses Sinnessystem eine räumlich hochauflösende dreidimensionale

Analyse der Außenwelt ermöglicht (Wurtz & Kandel, 2000b).

Nach dem peripheren visuellen System (Auge und Netzhaut) sowie dem visuellen Thalamus

als subcorticale Zwischenstation stellt der primäre visuelle Cortex (V1) am hinteren

Okzipitalpol das erste corticale Analysemodul dar, in dem visuelle Basismerkmale (z.B.

Orientierung) in räumlich (retinotop) geordneter Weise repräsentiert sind (Wurtz & Kandel,

2000a). In den hierarchisch nachgeschalteten visuellen Arealen (V2, V3, V5/MT etc.) erfolgt

eine zunehmend spezialisierte neuronale Verarbeitung von Muster-, Farb- und

Bewegungsinformation, wobei funktionell zwei getrennte visuelle Verarbeitungspfade

unterschieden werden: a) Ein sog. ventraler „Was-Pfad“, der vom okzipitalen in den

temporalen Cortex zieht und mit Objektwahrnehmung in Zusammenhang steht und b) ein sog.

dorsaler „Wo-Pfad“, der sich in den parietalen Cortex erstreckt und visuell-räumliche

Funktionen aufweist (Grill-Spector & Malach, 2004; Wurtz & Kandel, 2000b). Um die

visuelle Verarbeitung handlungsrelevanter räumlicher Information im dorsalen Pfad zu

betonen wurde dieser von Goodale & Milner (1992) als „vision-for-action“-Pfad bezeichnet –

im Gegensatz zum ventralen Pfad, der auf die Verarbeitung visueller Information für die

Wahrnehmung („vision-for-perception“) spezialisiert ist.

Einleitung 9

Neuere Untersuchungen deuten auf dynamische Interaktionen zwischen beiden Pfaden hin

(Goodale & Westwood, 2004), wobei kürzlich in einer Human-fMRT-Studie von Konen &

Kastner (2008) gezeigt werden konnte, dass es auch im dorsalen Pfad zu Objekt-spezifischen

neuronalen Aktivierungen kommt. Ein wesentlicher Unterschied in der neuronalen

Verarbeitung der beiden Pfade könnte in der Codierung der visuellen Information, d.h. in der

Art der Referenzsysteme, begründet sein (vgl. Schenk, 2006): Während der ventrale Pfad

visuelle Information in einem Objekt-bezogenen (allozentrischen) Referenzsystem

verarbeitet, encodiert der dorsale Pfad visuelle Information Subjekt-bezogen, also in einem

egozentrischen Koordinatensystem.

Sensomotorische Transformation im posterioren parietalen Cortex

Der erste Schritt bei der Planung einer Bewegung ist die visuell-räumliche Analyse des

Objekts durch die corticalen Areale des dorsalen Pfades. Da das visuelle System und das

motorische System unterschiedliche räumliche Bezugssysteme aufweisen, kommt es in einem

intermediären Schritt zur Umwandlung der visuellen (retinalen) Koordinaten in motorische

(Arm-zentrierte) Koordinaten für die Bewegungsplanung, ein Prozess, der als

sensomotorische Transformation bezeichnet wird und eine wesentliche Funktion des

posterioren parietalen Cortex (PPC) darstellt (Andersen et al., 2004). In verschiedenen

neuronalen Populationen im PPC können sowohl sensorische als auch motorische

Aktivierungen nachgewiesen werden, so dass der PPC als sensomotorische Schnittstelle für

die Planung von Augen- und Armbewegungen angesehen werden kann (Buneo & Andersen,

2006). Neben dem Areal LIP (engl. „lateral intraparietal“), das bei der Planung von

Augenbewegungen aktiviert wird, ist für zielgerichtete Armbewegungen das Areal PRR (engl.

„parietal reach region“) von Bedeutung, das zunächst beim Affen und später in einer fMRT-

Studie von Connolly et al. (2003) auch beim Menschen nachgewiesen werden konnte.

Für die Planung einer visuell-geführten Bewegung wird im PPC eine Umwandlung der

retinalen in motorische Koordinaten vollzogen, wobei die retinalen Koordinaten mit

sensorischen Informationen über die aktuelle Augen-, Kopf- und Körperposition

(propriozeptive Signale) in Bezug zum Objekt kombiniert werden; dabei existieren

verschiedene Modelle darüber, ob diese Informationen auf neuronaler Ebene seriell,

kombinatorisch oder direkt miteinander abgeglichen werden (Andersen et al., 2004). Die

Transformation in motorische Koordinaten, die auf das Effektororgan, z.B. den Arm, zentriert

sind, umfasst folglich auch die Integration verschiedener sensorischer Modalitäten im PPC

(Andersen et al., 1997). Eine PET-Studie von Clower et al. (1996) konnte zeigen, dass es

Einleitung 10

während der Prismenadaptation zu neuronalen Aktivierungen im PPC – in der Hemisphäre

kontralateral zum sich bewegenden Arm – kommt, was darauf hindeutet, dass die

sensomotorischen Repräsentationen im PPC plastischen Veränderungen unterliegen können

(s.u.).

Kontrolle von Bewegung durch corticale und subcorticale motorische Areale

Das periphere motorische System steuert letztlich die Ausführung einer Bewegung durch ein

motorisches Effektororgan auf Basis des komplexen räumlich-zeitlichen Zusammenspiels der

beteiligten Muskeln. Die zentralnervöse Vorbereitung der Bewegung erfolgt jedoch durch

corticale und subcortiale motorische Areale, die spezifisch und Kontext-bezogen an der

Planung und Kontrolle der Bewegung beteiligt sind bzw. diese modulieren: Der motorische

Cortex untergliedert sich in den primären motorischen Cortex (M1), das supplementär-

motorische Areal (SMA) sowie den prämotorischen Cortex (PMC). Körperteile werden in M1

somatotop repräsentiert, wobei die Größe der Repräsentation eine Funktion der Feinheit der

motorischen Steuerung ist (Blickhan, 2001). Eingänge erhält der motorische Cortex von den

Basalganglien, dem Kleinhirn (über den Thalamus) und aus den sensorischen Cortices; den

Hauptausgang bildet die sog. Pyramidenbahn, die „absteigend“ in das Rückenmark projiziert

(ebd.). Es besteht eine enge Verknüpfung zwischen dem motorischen und dem posterior

anliegenden somatosensorischen Cortex, in dem die Körperteile ebenfalls somatotop

repräsentiert sind. Das SMA und der PMC spielen insbesondere bei der Vorbereitung einer

Handlung eine Rolle; neuronale Aktivität im PMC liefert kontextuelle und räumliche

Information für die Bewegungsplanung, wobei enge wechselseitige Verbindungen zum PPC

bestehen, also dem Bereich des Gehirns, in dem die sensomotorische Transformation der

visuellen in motorische Koordinaten erfolgt (Shadmehr & Wise, 2005).

Ein wesentliches neuronales Substrat motorischer Kontrolle ist das Kleinhirn (Cerebellum),

das insbesondere bei der Feinabstimmung von Bewegungen und bei der Bewegungskorrektur

durch die Generierung eines neuronalen Fehlersignals eine wichtige Rolle spielt (Ghez &

Thach, 2000). Neben diesen eher allgemeinen motorischen Funktionen wird das Kleinhirn

auch mit motorischem Lernen und Adaptationsprozessen in Zusammenhang gebracht, eine

Vorstellung, die auf theoretische Arbeiten von Marr (1969) sowie Albus (1971) zurückgeht

und für die es eine Reihe von experimentellen Belegen gibt (eine Übersicht dazu liefern z.B.

Glickstein, 2007; Halsband et al., 2006; Thach et al., 1992). Auch für die Prismenadaptation

spielt das Kleinhirn eine entscheidende Rolle – neben dem posterioren parietalen Cortex wird

es als das wesentliche neuronale Substrat der plastischen Anpassungsprozesse, die während

Einleitung 11

der Prismenadaptation wirksam sind, diskutiert; die entsprechenden experimentellen Belege

werden im weiteren Verlauf bzw. in den Manuskripten näher vorgestellt.

1.4 Sensomotorische Plastizität am Beispiel der Prismenadaptation

Prozesse und Mechanismen

Wie im vorigen Abschnitt beschrieben, sind an der Planung und Ausführung einer

zielgerichteten Armbewegung ganz verschiedene Teile des Gehirns mit unterschiedlichen

funktionellen Eigenschaften beteiligt, wobei die hochgradig automatisierte sensomotorische

Bewegungsplanung in der Regel die präzise und erfolgreiche Ausführung einer Bewegung

gewährleistet.

Setzt man dagegen einer Versuchsperson eine geeignete Prismenbrille auf, durch welche sie

die visuelle Welt um einen bestimmten Winkelbetrag beispielsweise in der horizontalen

Ebene versetzt wahrnimmt, weichen zielgerichtete visuell-geführte Armbewegungen zunächst

in der Richtung der prismatischen Versetzung seitlich ab. Wodurch wird dieser Prismeneffekt

ausgelöst? Eintreffendes Licht wird durch die Prismen gebrochen und dabei zur Prismenbasis

abgelenkt, was zur Folge hat, dass die Strahlen auch im Augenhintergrund seitlich abgelenkt

ankommen. Damit das Ziel weiterhin visuell fixiert werden kann, wird eine gleichsinnige

kompensatorische Augenbewegung in die Gegenrichtung der Prismenbasis ausgeführt, d.h.

die Augenstellung im Kopf wird unter dem Einfluss der Prismen verändert. Die manipulierte

Augenstellung führt dazu, dass der Arm zu dem „virtuellen“ – als seitlich versetzt

wahrgenommen – Ziel geleitet wird und nicht die tatsächliche physikalische Zielposition

erreicht. Der Prismeneffekt ergibt sich folglich primär aus der Planung einer Armbewegung

zu einem als versetzt wahrgenommenen Ziel, was eine direkte Folge der durch die Prismen

verursachten veränderten Augenstellung im Kopf ist (vgl. Ghez & Thach, 2000; Martin et al.,

1996b). Die Größe des Prismeneffekts ist dabei proportional zur Stärke der optischen

Versetzung durch die Prismen (Fernandez-Ruiz & Diaz, 1999). Der initiale Prismeneffekt

fällt jedoch meist geringer aus als aufgrund der optischen Eigenschaften der Prismen

rechnerisch zu erwarten wäre (dazu siehe Redding & Wallace, 2004).

Der Prozess der Prismenadaptation, der bereits von Helmholtz (1867) beschrieben wurde,

umfasst die zunehmende Verringerung des seitlichen motorischen Fehlers aufgrund visueller

Rückmeldung über die räumliche Genauigkeit der Armbewegung. Im Verlauf der Adaptation

werden die Armbewegungen durch Training – aktives Ausüben und Wiederholen der

motorischen Aufgabe – korrigiert und an die veränderten sensomotorischen Bedingungen

Einleitung 12

angepasst bis das Ziel trotz der Prismenbrille wieder getroffen wird (Harris, 1965; Redding et

al., 2005).

Dass es sich dabei um einen „klassischen“ Adaptationsprozess handelt, zeigt der negative

Nacheffekt, der auftritt, wenn die Versuchsperson nach erfolgter Adaptation die

sensomotorische Aufgabe ohne Prismenbrille ausführt: In diesem Fall weichen die

Armbewegungen zunächst in der dem Prismeneffekt entgegengesetzten Richtung seitlich ab,

d.h. es tritt erneut ein motorischer Fehler auf, der aber im weiteren Verlauf des

sensomotorischen Trainings vollständig abgebaut wird (Harris, 1965; Redding et al., 2005).

Der Nacheffekt lässt darauf schließen, dass es im Verlauf des Adaptationsprozesses durch

Training zu einer neuen funktionellen Kopplung innerhalb des sensomotorischen Systems

gekommen ist; durch diese wird sichergestellt, dass die intendierten Armbewegungen trotz

der neuen sensomotorischen Bedingungen zielgerichtet und präzise ausgeführt werden

können. Der Prozess des Neu-Abgleichs sensomotorischer Koordinaten setzt funktionelle

Plastizität der beteiligten neuronalen Strukturen voraus (s.o.). Mit dem Verschwinden des

Nacheffekts ist die De-Adaptation abgeschlossen und die ursprüngliche sensomotorische

Kopplung wieder hergestellt.

Ohne an dieser Stelle auf die Details des entsprechenden Modells eingehen zu können, sei

festgehalten, dass Redding & Wallace (2002; 2003a) bzw. Redding et al. (2005) die

Prismenadaptation im wesentlichen auf zwei adaptive Mechanismen im Gehirn zurückführen:

a) einen Mechanismus strategischer (Re-)Kalibrierung (engl. „strategic re-/calibration“) und

b) einen Mechanismus räumlicher (Neu-)Ausrichtung (engl. „spatial re-/alignment“). Diese

beiden Mechanismen interagieren dynamisch und tragen gemeinsam zum adaptiven Verhalten

bei. Dabei führt der („kognitive“) Kalibrierungs-Mechanismus zu einer schnellen Reduktion

des motorischen Fehlers während des Tragens der Prismenbrille, d.h. die Genauigkeit des

motorischen Ausgangs steigt mit der Anzahl der ausgeführten Armbewegungen an. Parallel

dazu operiert der („sensomotorische“) Neuausrichtungs-Mechanismus und gleicht die

Koordinatensysteme (visuell, propriozeptiv, motorisch) räumlich-funktionell neu miteinander

ab, wodurch die räumlichen Bezugssysteme der Sensomotorik unter dem Einfluss der

Prismenbrille adaptiv in Übereinstimmung gebracht werden.

In einer neueren Untersuchung dissoziieren Redding & Wallace (2006a) beide Mechanismen,

indem sie das Generalisierungsmuster des Nacheffekts auf neue Aufgaben miteinander

vergleichen; leider tragen sie weiter zur sprachlichen Unschärfe im Zusammenhang mit der

Prismenadaptation bei, indem sie „recalibration“ als ein Beispiel für „kognitives Lernen“

anführen, während „realignment“ ein Beispiel für „perzeptuelles Lernen“ sei (S. 1006f.).

Einleitung 13

Eine Studie von Michel et al. (2007) deutet darauf hin, dass sich beide Mechanismen

bedingen, wobei der kognitive Mechanismus jedoch zu einer schwächeren Adaptation im

Vergleich zum sensomotorisch-automatischen Mechanismus führt: Erfolgte die Adaptation an

eine gegebene prismatische Versetzung abrupt, also mit einer starken bewusst-kognitiven

Komponente, war der Nacheffekt schwächer als bei einer progressiven Adaptation während

der sich die Versuchsperson über die prismatische Versetzung nicht „bewusst“ war. Das

bedeutet, dass der „kognitive“ Mechanismus zwar schnell die prismatische Versetzung

kompensieren kann, dieser jedoch nicht zu einem so präzisen funktionellen Abgleich

sensomotorischer Koordinaten führt wie der „automatische“ Mechanismus.

Im Prinzip sind mindestens drei Subsysteme der Sensomotorik als Locus der Prismen-

induzierten Veränderungen im Verlauf des Adaptationsprozesses denkbar: a) die räumliche

Codierung im visuellen System, b) die Lokalisation der Körperteile (insbesondere des Arms)

im Raum durch das propriozeptive System und c) die Bewegungsausführung durch das

motorische System. Folglich könnte die Prismenadaptation visuell, propriozeptiv oder

motorisch realisiert werden, wobei es für alle drei Erklärungsmöglichkeiten experimentelle

Hinweise gibt (siehe z.B. Harris, 1963; 1965; Martin et al., 1996b; Redding et al., 2005;

Uhlarik & Canon, 1971). Wahrscheinlich ist, dass es in allen drei Subsystemen zu schnellen

adaptiven Veränderungen kommen kann, wobei die relativen Beiträge von der

sensomotorischen Aufgabe, dem experimentellen Kontext sowie den spezifischen

experimentellen Bedingungen wie beispielsweise der Art der sensorischen Rückmeldung etc.

abhängen.

Neuronale Substrate der Verarbeitung

Neben einer Vielzahl psychophysikalischer Studien über funktionelle Aspekte der

Prismenadaptation liegen auch einige Studien über die beteiligten neuronalen Substrate vor.

So konnten bereits Weiner et al. (1983) zeigen, dass menschliche Patienten mit einer Läsion

des Kleinhirns Probleme bei der Prismenadaptation aufweisen und dementsprechend auch der

Nacheffekt erheblich reduziert ist, was auf eine Rolle des Kleinhirns beim funktionellen

Abgleich sensomotorischer Koordinaten hinweist. Ähnliche Ergebnisse lieferte die

Patientenstudie von Martin et al. (1996a), die den Vorteil hatte, dass aufgrund des Einsatzes

bildgebender neuroradiologischer Verfahren (Magnetresonanz- bzw. Computertomographie)

eine genauere Analyse über Art und Ausmaß der cerebellären Schädigung möglich war. Auch

die Ergebnisse der Studien von Morton & Bastian (2004) sowie Pisella et al. (2005) lassen auf

Einleitung 14

eine wesentliche Rolle des Kleinhirns bei der Prismenadaptation schließen. In

Übereinstimmung mit den Befunden beim Menschen konnte beim Rhesusaffen (Macaca

mulatta) nachgewiesen werden, dass focale Läsionen des Kleinhirns die Fähigkeit zur

Prismenadaptation massiv beeinträchtigen (Baizer et al., 1999).

Als corticales neuronales Substrat der Prismenadaptation wird der posteriore parietale Cortex

diskutiert, was sowohl in der bereits genannten PET-Studie von Clower et al. (1996) bei

Normalpersonen als auch in Patientenstudien u.a. von Newport & Jackson (2006) sowie

Newport et al. (2006) nachgewiesen werden konnte. Diese Ergebnisse weisen darauf hin, dass

die sensomotorischen Repräsentationen im PPC schnellen plastischen Veränderungen

unterzogen werden können, wobei dieses möglicherweise durch die Aktivität eines parieto-

cerebellären Netzwerks vermittelt wird.

Dass die Prismenadaptation auch einen Einfluss auf höhere Ebenen der neuronalen

Informationsverarbeitung hat (insbesondere auf die Raumrepräsentation), legen Studien zur

Prismenadaptation bei Neglect-Patienten nahe. Neglect ist eine Störung der räumlichen

Repräsentation der Außenwelt, die auf eine meist rechtsseitige Läsion im parietalen Cortex

zurückgeht und sich bei Patienten in Form eines Defizits bei der Orientierung auf Reize in der

kontraläsionalen Seite des Raumes äußert (Redding & Wallace, 2006b; Rode et al., 2003).

Rossetti et al. (1998) konnten nachweisen, dass es bei Patienten mit linksseitigem Neglect

nach der Adaptation an rechtsversetzende Prismen (Nacheffekt nach links) bei

neuropsychologischen Tests von räumlichen Aufgaben zu länger anhaltenden Verbesserungen

kommt. Dies zeigt, dass die plastischen Veränderungen im Verlauf der Prismenadaptation

räumliche Repräsentationen spezifisch beeinflussen.

Allgemeine Methodik 15

2. Allgemeine Methodik

2.1 Verhaltensuntersuchungen und Psychophysik

Methodisch lässt sich diese Arbeit in den Bereich der Psychophysik einordnen, in der die

quantitativen Beziehungen zwischen Reizgröße und subjektiver Empfindungsgröße erfasst

werden (Birbaumer & Schmidt, 2003). Durch das systematische Variieren einer bestimmten

(physikalisch definierten) Reizgröße und das Messen der darauf folgenden subjektiven

Empfindung bzw. des Verhaltens einer Versuchsperson wird auf die zugrunde liegenden

Mechanismen und Prozesse geschlossen. Psychophysikalische Methoden eignen sich folglich

besonders gut, um die funktionellen Merkmale eines Prozesses zu charakterisieren, wobei der

Vorteil dieses methodischen Ansatz auch darin liegt, dass für die Untersuchungen keine

experimentellen Eingriffe bei der Versuchsperson vorgenommen werden müssen, d.h. es

handelt sich um eine nicht-invasive Methode.

Der psychophysikalische Ansatz soll am Beispiel der Prismenadaptation näher erläutert

werden: Der Versuchsperson wird eine geeignete experimentelle Aufgabe gestellt,

beispielsweise die Ausführung einer visuell-geführten Armbewegung zu einem Ziel, wobei

die Genauigkeit der Armbewegungen unter verschiedenen Bedingungen (z.B. mit vs. ohne

Prismenbrille) kontinuierlich aufgezeichnet und gemessen wird. Mit Hilfe dieses Verfahrens

wird eine quantitative Beziehung zwischen den physikalischen Reizeigenschaften (in diesem

Fall z.B. Stärke und Richtung der prismatischen Versetzung) und dem beobachtbaren

Verhalten (Genauigkeit der Armbewegung) unter verschiedenen Bedingungen hergestellt, um

auf die zugrunde liegenden Prozesse und Mechanismen zu schließen. Die

psychophysikalische Untersuchung der Prismenadaptation charakterisiert den Prozess folglich

auf der Verhaltensebene und liefert über die geeignete Variation der experimentellen

Bedingungen Erkenntnisse über die funktionellen Aspekte der Adaptation. Beispielsweise

kann man durch das Messen der Größe des Nacheffekts unter verschiedenen Bedingungen die

Stabilität bzw. die Generalisierbarkeit des Adaptationsprozesses untersuchen (siehe Studie 3).

Bei der Interpretation psychophysikalischer Daten muss jedoch berücksichtigt werden, dass

Aussagen über die zugrunde liegenden neuronalen Prozesse und Substrate nur indirekt

möglich sind, da keine neurophysiologischen Signale, sondern Verhaltensantworten gemessen

werden. Um sowohl funktionelle als auch neuronal-strukturelle Aspekte der


Prismenadaptation zu untersuchen wäre folglich ein Paradigma geeignet, das (indirekte)

psychophysikalische und (direkte) neurophysiologische bzw. bildgebende Methoden

miteinander kombiniert. Gerade bei menschlichen Versuchspersonen sind

neurophysiologischen Untersuchungen jedoch enge ethische und methodische Grenzen

gesetzt. Allerdings können psychophysikalische Untersuchungen zur Adaptationsfähigkeit bei

Patienten mit anatomisch umschriebenen Läsionen des ZNS ebenfalls wertvolle

experimentelle Belege für die Beteiligung bestimmter neuronaler Strukturen liefern (s.o.).

2.2 Sensomotorische Aufgaben: Zeige- und Wurfbewegungen

In der vorliegenden Arbeit wurde die Prismenadaptation bei zwei sensomotorischen Aufgaben

– Zeige- bzw. Wurfbewegungen – psychophysikalisch untersucht.

Zeigebewegungen im peripersonalen Raum

Bei der Zeige-Aufgabe (Fig. 2.1a) bestand die Aufgabe der Versuchsperson darin, an einem

Tisch sitzend zielgerichtete visuell-geführte Zeigebewegungen zu einem bestimmten Ziel

auszuführen und dabei das Ziel unter visueller Fixation immer so genau wie möglich zu

treffen. Die Versuchsperson konnte ihren Arm zu Beginn der Bewegung nicht sehen, so dass

die Arm-Trajektorie im Wesentlichen nur auf Basis der visuellen Information über die

räumliche Position des Ziels in Bezug zur Versuchsperson geplant werden konnte. Auch

während der Trajektorie konnte keine visuelle Korrektur erfolgen, da der Bewegungspfad für

die Versuchsperson aufgrund einer undurchsichtigen Tischplatte unsichtbar war (Ausnahme:

Studie 2); es handelte es sich im Übrigen um eine ballistische Bewegung. Am Ende der

Bewegung konnte die Versuchsperson die Spitze des Zeigefingers in Bezug zum Ziel sehen

und erhielt somit stets visuelle Rückmeldung über die räumliche Genauigkeit der Bewegung

(Fehlersignal). Die einzelnen Bewegungen wurden in rascher Folge ausgeführt und die

Versuchsperson konnte aufgrund der visuellen Rückmeldung die Bewegungen schrittweise

korrigieren.

Da sich das Ziel innerhalb des räumlichen Arbeitsbereichs befand, der mit dem Arm direkt

erreicht und damit aktiv exploriert werden kann, handelte sich um Bewegungen im Nahraum,

d.h. im peripersonalen Raum, in dem die sensomotorische Kontrolle von Armbewegungen

aufgrund des dreidimensionalen Sehens sehr präzise ist (siehe auch Previc, 1998). Der

peripersonale Raum wird auch als „action space“ bezeichnet, wodurch betont werden soll,

dass in diesem räumlichen Bereich bewegungsrelevante Aktivität eine große Rolle spielt. Die


Mehrzahl der Bewegungen erfolgt im Nahraum unter visueller Kontrolle – hieraus ergibt sich,

dass Zeigebewegungen im Nahraum bei Versuchspersonen in der Regel hochgradig trainiert

und abgestimmt sind. Um die generelle Genauigkeit von Zeigebewegungen auf ein visuelles

Ziel im Nahraum zu messen, wurde in den Experimenten jeweils auch eine sog. Baseline-

Messung (ohne Prismenbrille; s.u.) vorgenommen.

Die Genauigkeit der Zeigebewegungen wurde mit Hilfe eines PC-kontrollierten Messsystems

der Firma Zebris Medical (Isny, Deutschland) erfasst, das den räumlichen Abstand zwischen

Ziel und Zeigefinger in allen drei Raumdimensionen durch Analyse der

Laufzeitverzögerungen von Ultraschallsignalen mit einer Genauigkeit von ca. 1 mm

berechnen konnte. Da die prismatische Versetzung jeweils in der horizontalen Ebene erfolgte,

wurde entsprechend der horizontale Abstand zwischen Ziel und Zeigefinger am Ende der

Trajektorie ermittelt.

Fig. 2.1 Skizze des experimentellen Aufbaus der (A) Zeige- und (B) Wurf-Aufgaben.

Wurfbewegungen im extrapersonalen Raum

Neben Zeigebewegungen wurden auch Wurfbewegungen untersucht, wobei die Aufgabe der

Versuchsperson darin bestand, einen Ball so genau wie möglich zu einem Ziel an einer 2 m

entfernten Leinwand zu werfen. Dabei sollte das Ziel immer visuell fixiert werden; bei den

Würfen handelte es sich um „seitliche“ Oberhand-Würfe wie sie beispielsweise auch von

Martin et al. (1996a; 1996b; 2002) sowie Fernandez-Ruiz & Diaz (1999) untersucht wurden.

Die Versuchsperson erhielt visuelle Rückmeldung über die Genauigkeit des aktuellen Wurfes,

da der Ball an der mit Klettmaterial beschichteten Leinwand hängen blieb; somit konnten die

Würfe – analog zu den Zeigebewegungen – schrittweise korrigiert werden.


Anders als bei der Zeige-Aufgabe befand sich das Ziel bei der Wurf-Aufgabe jenseits des

räumlichen Bereichs, der mit den Armen direkt erreicht werden kann, d.h. es handelte sich

hier um eine motorische Aufgabe im Fernraum (extrapersonaler Raum), in dem

wahrnehmungsbezogene räumliche Information ein wichtige Rolle spielt (vgl. Previc, 1998).

Wurfbewegungen weisen gegenüber Zeigebewegungen einen höheren Grad an motorischer

Komplexität auf; hinzu kommt, dass das Werfen nicht zum „klassischen“ Alltags-

Bewegungsrepertoire einer Versuchsperson gehört und dieses Bewegungsmuster damit auch

nicht so hochgradig trainiert ist wie das der Zeigebewegungen; aufgrund dessen begannen die

Wurf-Experimente jeweils mit einer kurzen Trainings- bzw. Gewöhnungsphase. Im

Anschluss hieran erfolgte die Messung der Wurf-Genauigkeit ohne Prismenbrille (Baseline-

Messung). Die räumliche Genauigkeit der Würfe wurde mit einem PC-kontrollierten

optischen System ermittelt, das die horizontale Entfernung zwischen dem Ziel und der

Position des Balls mit einer räumlichen Auflösung von ca. 1 cm feststellen konnte4.

Ablauf

Der Ablauf sowohl der Zeige- als auch der Wurf-Experimente gliederte sich standardmäßig in

drei Phasen bzw. Bedingungen (siehe Redding et al., 2005), wobei je nach Fragestellung ein

hiervon leicht abgewandelter Ablauf realisiert wurde (das gilt insbesondere für Studie 2): a)

eine Prä-Prismenbedingung, in der die Genauigkeit der Bewegungen ohne Prismenbrille

aufgezeichnet wurde (Baseline-Messung), b) eine Prismenbedingung, während der die

Adaptation an die prismatische Versetzung erfolgte und c) eine Post-Prismenbedingung, in

welcher der Nacheffekt gemessen und die De-Adaptation vollzogen wurde. Dabei wurden pro

Bedingung mindestens 30 zielgerichtete Bewegungen ausgeführt, wobei diese Anzahl

insbesondere in der Prismenbedingung der Wurf-Experimente nicht unterschritten werden

sollte, um eine ausreichende Trainings-bedingte Adaptation sicherzustellen. Eine detaillierte

Beschreibung des experimentellen Ablaufs befindet sich im Methoden-Teil der Manuskripte.

4 Nach jedem Wurf wurde ein Digitalphoto von der Leinwand mit der Position des Balls aufgenommen. Die Auswertung der elektronischen Bilddaten erfolgte mit Hilfe einer von Herrn Dipl.-Phys. D. Trenner entwickelten Matlab-basierten Software.


2.3 Datenauswertung

Für jede einzelne Bewegung wurde der horizontale Abstand („horizontaler Fehler“) zwischen

dem Ziel und dem Endpunkt der Bewegung in metrischen Einheiten bestimmt und als

Funktion der Anzahl der Bewegungen in der jeweiligen Bedingung graphisch aufgetragen.

Bei den Zeigebewegungen wurde der horizontale Abstand zwischen Ziel und Zeigefinger auf

dem höchsten Punkt der Trajektorie ermittelt, da sich Ziel und Zeigefinger in diesem Fall auf

einer Höhe befanden (Tischkante als gemeinsame Begrenzung) und die Bewegung somit

nicht mehr fortgesetzt werden konnte. Bei den Wurfbewegungen war der Endpunkt der

Bewegung durch die Position des Balls auf der Leinwand definiert; auch hier wurde

ausschließlich der Abstand vom Ziel zum Zentrum des Balls in der horizontalen Ebene

bestimmt.

Die Rohdaten einer Versuchsperson wurden darüber hinaus individuell einer sog. „Baseline-

Korrektur“ unterzogen, um eine Normalisierung der Daten zu erreichen. Dafür wurde das

arithmetische Mittel der horizontalen Fehler der Bewegungen in der Prä-Prismenbedingung

gebildet und von jedem einzelnen Datenpunkt subtrahiert. Dieses Verfahren wurde auch von

Clower & Boussaoud (2000) angewandt und hat den Vorteil, dass der Datensatz individuell

um eine eventuelle Vorzugsrichtung („Bias“) der Bewegung bei einer bestimmten Aufgabe

korrigiert wird, was eine bessere Vergleichbarkeit der Effekte zwischen Versuchspersonen

ermöglicht. Gerade bei der Wurf-Aufgabe war dieser „Bias“ von Versuchsperson zu

Versuchsperson unterschiedlich stark, wodurch eine Normalisierung der Daten notwendig

erscheint. Alle weiteren Analysen wurden auf Basis der Baseline-korrigierten Daten

durchgeführt.

In der Datenanalyse lag neben dem zeitlichen Verlauf von Adaptation und De-Adaptation ein

besonderer Focus auf der Größe von Prismen- bzw. Nacheffekt. Für die Ermittlung der Größe

des Prismeneffekts wurde der horizontale Fehler als Funktion der ersten vier Bewegungen der

Prismenbedingung aufgetragen und es wurde eine lineare Regressionsgerade angelegt; der

Schnittpunkt der Regressionsgeraden mit der y-Achse wurde als Maß für die Größe des

initialen Prismeneffekts verwendet. Entsprechend wurde bei der Ermittlung des Nacheffekts

vorgegangen. Das verwendete mathematische Verfahren berücksichtigt, dass Prismen- bzw.

Nacheffekt nicht bereits nach der ersten Bewegung vollständig verschwunden sind, sondern

eine schnelle schrittweise Reduktion des horizontalen Fehlers während der ersten

Bewegungen erfolgt.

Motivation und Zusammenfassung der Studien 20

3. Motivation und Zusammenfassung der Studien

3.1 Motivation der Studien

Das Ziel der vorliegenden Arbeit bestand darin, bestimmte funktionelle Aspekte der

Prismenadaptation bei gesunden menschlichen Versuchspersonen psychophysikalisch zu

untersuchen um Antworten auf die Frage zu liefern, mit welchen plastischen Mechanismen es

das Gehirn erreicht, seine funktionelle Organisation schnell und reversibel neuen

Bedingungen anzupassen. Dafür wurde das Paradigma der Prismenadaptation gewählt, da es

sich besonders gut eignet, schnelle sensomotorische Adaptationsprozesse beim Menschen mit

nicht-invasiven psychophysikalischen Methoden zu charakterisieren.

Studie 1: Vollständigkeit des Adaptationsprozesses

In Studie 1 wurde die Vollständigkeit des Adaptationsprozesses bei zwei verschiedenen

Aufgaben (Zeigen vs. Werfen) und zwei verschiedenen Richtungen der prismatischen

Versetzung (links vs. rechts) nach ausgedehntem sensomotorischen Training untersucht. Die

Motivation für diese Studie geht auf Beobachtungen aus Pilot-Experimenten zu

Wurfbewegungen zurück, bei denen die Versuchspersonen am Ende der Prismenadaptation

(nach 30 Bewegungen) einen deutlichen horizontalen Restfehler in Richtung der

prismatischen Versetzung aufwiesen. Ein ähnlich hoher Restfehler von Wurfbewegungen ist

beispielsweise auch in den Ergebnissen von Fernandez-Ruiz & Diaz (1999, Fig. 1)

auszumachen, wobei dieser Effekt in der genannten Studie jedoch nicht diskutiert wird.

Ausgehend von dieser Beobachtung wurde eine Studie konzipiert, die die Vollständigkeit des

Adaptationsprozesses nach ausgedehntem Training systematisch prüfen sollte. Die Anzahl der

Bewegungen während der Prismenbedingung wurde von 30 auf 120 bzw. 240 (Kontroll-

Experiment) erhöht, um ein ausgedehntes Training der entsprechenden Aufgabe zu

gewährleisten. Für den Fall, dass die Vollständigkeit der Adaptation und damit die

Genauigkeit, mit der sensomotorische Koordinaten im Verlauf der Adaptation neu

miteinander abgeglichen werden, nur vom Ausmaß des Trainings abhängt, sollten sich die

Bewegungen im Verlauf des Adaptationsprozesses einem mittleren Fehler von „Null“

angleichen. Die Vollständigkeit der Prismenadaptation wurde bei zwei Aufgaben untersucht,

um hochgradig trainierte Bewegungen im Nahraum (Zeigen) mit weniger stark trainierten und

komplexeren Bewegungen im Fernraum (Werfen) miteinander zu vergleichen.


Studie 2: Aufgaben-Spezifität der Prismenadaptation

Die Konzeption von Studie 2 war durch die Frage motiviert, inwieweit es zu einer

Generalisierung der Prismenadaptation von einer trainierten auf eine untrainierte

sensomotorische Aufgabe kommt. Das Ausmaß der Generalisierung spiegelt die Spezifität des

Adaptationsprozesses für den aktuellen Aufgabenkontext wider. Das Generalisierungsmuster

liefert somit wichtige Erkenntnisse über die Art der Informationsverarbeitung (siehe Poggio

& Bizzi, 2004). In Studie 2 wurde die Generalisierung des Prismen- bzw. Nacheffekts von

einer Zeige-Aufgabe auf eine Wurf-Aufgabe gemessen. Eine vollständige Generalisierung auf

die Wurf-Aufgabe würde auf einen „globalen“ Adaptationsprozess unabhängig vom

Aufgabenkontext hindeuten. Umgekehrt würde eine schwache bzw. ausbleibende

Generalisierung zeigen, dass die adaptiven Veränderungen im Gehirn jeweils spezifisch für

die aktuell ausgeführte Aufgabe vorgenommen werden. Einen Hinweis hierauf lieferte bereits

die Studie von Martin et al. (1996b). Parallel hierzu wurde in Studie 2 untersucht, welchen

Einfluss die Art der sensorischen Rückmeldung während der Ausführung der Zeige-Aufgabe

auf die Generalisierung der Adaptation zur Wurf-Aufgabe hat. Die Versuchsperson erhielt im

ersten Experiment nur (terminale) visuelle Rückmeldung über die Zeigebewegung am Ende

der Bewegung, während im zweiten Experiment der komplette Bewegungspfad von der

Versuchsperson visuell verfolgt werden konnte (kontinuierliche Rückmeldung). Bereits von

Uhlarik & Canon (1971) wurde vorgeschlagen, dass die Adaptation je nach Art der

Rückmeldung in unterschiedlichen sensorischen Subsystemen vollzogen werde; dieser

Mechanismus würde folglich ein unterschiedliches Generalisierungsmuster in Abhängigkeit

von der Art der sensorischen Rückmeldung vorhersagen.

Studie 3: Räumliche Generalisierung des Nacheffekts

Die Frage nach dem räumlichen Generalisierungsmuster des Nacheffekts stand in Studie 3 im

Mittelpunkt. Der Nacheffekt wurde als kritische Messvariable gewählt, da dieser weniger

stark von kognitiven Einflüssen überformt ist; es wurden ausschließlich Zeigebewegungen

untersucht. Anders als in Studie 2 kam es nach erfolgter Prismenadaptation nicht zu einem

Wechsel der sensomotorischen Aufgabe, sondern es wurde getestet, inwieweit der Nacheffekt

auf nicht-trainierte Zielpositionen im Raum generalisiert. Dabei wurde in zwei Experimenten

die Art des sensomotorischen Trainings während der Prismenadaptation systematisch variiert:

Entweder wurden die Zeigebewegungen während der Adaptation nur zu einem Ziel in

geblockter Form durchgeführt (Experiment 1) oder das Training erfolgte abwechselnd zu zwei


verschiedenen Zielen im Raum (Experiment 2). In Experiment 2 wurde insbesondere

untersucht, wie die Generalisierung des Nacheffekts auf Ziele bei räumlichen Interpolations-

bzw. Extrapolationsaufgaben ausfällt. Studie 3 war folglich durch die Frage motiviert, ob die

Form des sensomotorischen Trainings während der Prismenadaptation einen Einfluss auf das

räumliche Generalisierungsmuster ausübt. Darüber hinaus liefert das Generalisierungsmuster

des Nacheffekts Erkenntnisse über die Art der adaptiven Veränderungen der räumlichen

Repräsentationen. Die Untersuchung orientierte sich dabei inhaltlich an den Studien von

Bedford (1993) sowie Redding & Wallace (2006a).

3.2 Zusammenfassung von Studie 1

In Studie 1 wurde die Vollständigkeit des Adaptationsprozesses bei Zeige- bzw.

Wurfbewegungen unter Verwendung links- bzw. rechtsversetzender Prismen bei vier

unabhängigen Gruppen rechtshändiger gesunder Versuchspersonen untersucht. Jedes

Experiment bestand dabei aus drei Bedingungen (Prä-, Prismen- und Post-Bedingung), in

denen jeweils 120 zielgerichtete Bewegungen ausgeführt wurden, um ein ausgedehntes

Training der sensomotorischen Aufgabe zu gewährleisten.

Erwartungsgemäß trat in allen vier Gruppen in der Prismenbedingung ein ausgeprägter

horizontaler Fehler in Richtung der prismatischen Versetzung auf, der durch Training deutlich

reduziert wurde. Nach dem Entfernen der Prismen trat ein Nacheffekt in der Gegenrichtung

auf, der in allen Gruppen durch Training im weiteren Verlauf der Post-Prismenbedingung

vollständig verschwand. Die Vollständigkeit des Adaptationsprozesses (Prismenbedingung)

hing dabei nicht von der Richtung der prismatischen Versetzung, sondern von der Art der

sensomotorischen Aufgabe ab. Während bei der Zeige-Aufgabe am Ende der

Prismenbedingung ein horizontaler Restfehler statistisch nicht nachgewiesen werden konnte,

trat bei der Wurf-Aufgabe nach 120 Bewegungen ein signifikanter horizontaler Restfehler

auf. Bei beiden Aufgaben nahm die Reduktion des horizontalen Fehlers während der

Prismenbedingung einen asymptotischen Verlauf, wobei allerdings bei der Wurf-Aufgabe ein

Restfehler zu beobachten war, der durch das Anlegen einer Exponentialfunktion an die Daten

quantifiziert wurde. Während folglich bei Zeigebewegungen ein nahezu vollständiger

Adaptationsprozess mit einer kompletten Kompensation der prismatischen Versetzung zu

beobachten war, deuten die Ergebnisse für die Wurfbewegungen auf einen unvollständigen

Adaptationsprozess mit einem inhärenten Restfehler hin. Dies konnte durch ein Kontroll-

Experiment, bei dem die Anzahl der Wurfbewegungen während der Prismenbedingung auf


240 verdoppelt wurde, bestätigt werden. Selbst unter diesen nochmals verlängerten

Adaptationsbedingungen war ein Restfehler statistisch nachweisbar, was stark darauf

hindeutet, dass bei Wurfbewegungen neben der reinen Anzahl von Bewegungen noch andere

Faktoren eine Rolle für die Adaptation spielen. Einer dieser Faktoren ist die allgemeine

Variabilität bei der Ausführung der Aufgabe: Für die Wurfbewegungen fand sich eine

signifikante positive Korrelation zwischen der allgemeinen Variabilität der Wurfbewegungen

und der Größe des Restfehlers am Ende der Prismenbedingung. Je höher die Variabilität,

desto größer der verbleibende Restfehler, d.h. umso unvollständiger die Adaptation. Diese

lineare Beziehung konnte nur bei der Wurf-Aufgabe nachgewiesen werden.

Die Ergebnisse von Studie 1 zeigen, dass das Gehirn bei der Ausführung von

Zeigebewegungen im Nahraum die sensomotorischen Koordinaten im Verlauf der

Prismenadaptation sehr präzise funktionell miteinander abgleichen kann, wodurch kein

Restfehler am Ende der Adaptation nachzuweisen ist. Die genaue adaptive Abstimmung der

Sensomotorik setzt ein hohes Maß an funktioneller Plastizität voraus, was wiederum in der

Verhaltensrelevanz von präzisen Zeigebewegungen im Nahraum begründet liegen könnte.

Dagegen scheint bei Wurfbewegungen im Fernraum die allgemeine Variabilität die

Vollständigkeit des Adaptationsprozesses zu begrenzen. Dieses könnte damit

zusammenhängen, dass das (neuronale) Fehlersignal, welches durch die Verrechnung von

motorischen Fehlern innerhalb eines gewissen Zeitfensters generiert wird, um die

Bewegungen zu korrigieren, aufgrund der großen Variabilität ein ungünstiges Signal-zu-

Rausch-Verhältnis aufweist und es somit zu einer unvollständigen Bewegungskorrektur mit

einem Restfehler kommt.


In Studie 2 wurde getestet, ob Prismen- bzw. Nacheffekt von einer Zeige-Aufgabe auf eine

Wurf-Aufgabe generalisieren. Das Ausmaß der Generalisierung wurde bei zwei unabhängigen

Gruppen rechtshändiger gesunder Versuchspersonen ermittelt, die während der Zeige-

Adaptation jeweils unterschiedliche sensorische Rückmeldungen erhielten. Im ersten

Experiment war visuelle Information über die Genauigkeit der Zeigebewegung nur am Ende

der Trajektorie verfügbar; dagegen war im zweiten Experiment der gesamte Pfad der

Zeigebewegung während der Adaptation sichtbar. Im Anschluss an die Adaptation an

rechtsversetzende Prismen durch Ausführung der Zeige-Aufgabe wurde die Generalisierung

a) des Prismen- bzw. b) des Nacheffekts auf die Wurf-Aufgabe getestet.


Die Ergebnisse beider Experimente zeigen ein einheitliches Bild, das auf eine hohe Aufgaben-

Spezifität der Prismenadaptation hinweist (vgl. Martin et al., 1996b). Behielten die

Versuchspersonen nach erfolgter Zeige-Adaptation die Prismen aufgesetzt und sollten direkt

im Anschluss Wurfbewegungen zum Ziel ausführen, trat bei dieser untrainierten Aufgabe ein

ausgeprägter horizontaler Fehler in Richtung der prismatischen Versetzung auf. Die

Reduktion dieses seitlichen Fehlers durch das Trainieren der Wurf-Aufgabe erfolgte

asymptotisch und war von einem konventionellen Adaptationsprozess nicht zu unterscheiden.

Die Größe des „zweiten“ Prismeneffekts nach dem Aufgaben-Wechsel glich dabei der Größe

des Standard-Prismeneffekts für die Wurf-Aufgabe. Dabei trat der Prismeneffekt nach dem

Aufgaben-Wechsel unabhängig von der Art der sensorischen Rückmeldung während der

vorangegangenen Zeige-Adaptation auf, folglich führte keine der beiden

Rückmeldungsformen zu einer stärkeren Generalisierung auf die neue Aufgabe. Auch beim

Nacheffekt trat keine Generalisierung von der Zeige- zur Wurf-Aufgabe auf: Setzten die

Versuchspersonen nach der Zeige-Adaptation die Prismen ab und führten dann

Wurfbewegungen aus, war bei der neuen Aufgabe kein Nacheffekt zu beobachten, was darauf

hindeutet, dass auch der Nacheffekt unter den gegebenen Bedingungen nicht generalisiert.

Die Ergebnisse von Studie 2 legen den Schluss nahe, dass die plastischen Veränderungen, die

im Zusammenhang mit der Prismenadaptation auftreten, hochgradig spezifisch für den

Kontext bzw. die aktuelle sensomotorische Aufgabe vorgenommen und nicht ohne weiteres

von einem Bewegungskontext auf einen neuen übertragen werden können. Darüber hinaus

führte keine den beiden Formen von sensorischer Rückmeldung (terminal vs. kontinuierlich)

zu einer stärkeren Generalisierung auf die neue Aufgabe. Andererseits gibt es experimentelle

Belege dafür (vgl. Redding & Wallace, 2006a; Uhlarik & Canon, 1971), dass bei terminaler

Rückmeldung die adaptiven Veränderungen insbesondere die visuelle Codierung betreffen,

was eine stärkere Generalisierung der Adaptation von einer Aufgabe auf die andere unter

diesen Bedingungen vorhersagen würde. Die Ergebnisse des Experiments mit terminaler

Rückmeldung sind mit dieser Sichtweise nicht in Einklang zu bringen, da auch in diesem Fall

keine Generalisierung auf die neue Aufgabe nachweisbar war. Die ausgeprägte Aufgaben-

Spezifität der Prismenadaptation, die sich in Studie 2 zeigt, ist möglicherweise auch darauf

zurückzuführen, dass es sich bei Zeige- bzw. Wurfbewegungen um sehr unterschiedliche

Bewegungsfamilien handelt, was eine Generalisierung erschwert.



In Studie 3 wurde die räumliche Generalisierung des Nacheffekts auf verschiedene

Zielpositionen bei zwei unterschiedlichen Formen von sensomotorischem Training

untersucht. Hierfür wurden zwei unabhängige Gruppen rechtshändiger gesunder

Versuchspersonen gebildet. In Experiment 1 erfolgte das sensomotorische Training während

der Prismenadaptation immer in geblockter Form zu einer von drei möglichen Zielpositionen

und im Anschluss wurde die Generalisierung des Nacheffekts auf eine nicht-trainierte

Zielposition getestet. In Experiment 2 führten die Versuchspersonen dagegen während der

Prismenadaptation Zeigebewegungen zu zwei verschiedenen Zielpositionen im Raum aus,

wodurch ein spezifischer Arbeitsbereich adaptiert wurde. In direktem Anschluss an dieses

gemischte Training wurde die Generalisierung des Nacheffekts entweder auf ein Ziel jenseits

des adaptierten räumlichen Bereichs (Extrapolationsaufgabe) oder auf ein Ziel innerhalb des

adaptierten Bereichs (Interpolationsaufgabe) gemessen.

Das Generalisierungsmuster des Nacheffekts nach Training in geblockter Form zeigt

unabhängig von der adaptierten Zielposition eine nahezu vollständige Generalisierung des

Nacheffekts auf nicht-trainierte Ziele im Raum. Wurde nach der Prismenadaptation zu einem

bestimmten Ziel die Größe des Nacheffekts an einem anderen Ziel getestet, so trat auch hier

ein Nacheffekt auf, was auf eine räumliche Generalisierung des Nacheffekts nach geblocktem

sensomotorischen Training hinweist. Dieses Generalisierungsmuster zeigt an, dass die

Adaptation an die prismatische Versetzung auch räumliche Positionen betrifft, die nicht direkt

während der Prismenadaptation trainiert wurden. Darüber hinaus deutet die lineare

Generalisierung des Nacheffekts zu untrainierten Zielen darauf hin, dass die räumlichen

Repräsentationen im Verlauf der Prismenadaptation in ihrer Gesamtheit verschoben bzw.

angeglichen werden, was gut mit den Ergebnissen von Bedford (1993) vereinbar ist. Nach

gemischtem sensomotorischen Training zeigt sich ein komplexeres Generalisierungsmuster

des Nacheffekts, wobei das Ausmaß der Generalisierung von der Position des getesteten Ziels

abhängt: Während der Extrapolations-Nacheffekt für das linke Ziel größer als der

entsprechende Standard-Nacheffekt war, verhielt es sich beim Extrapolations-Nacheffekt für

das rechte Ziel umgekehrt. Bei einer Interpolationsaufgabe zum zentralen Ziel fiel der

Generalisierungs-Nacheffekt ebenfalls geringer als der Standard-Nacheffekt aus. Die

Ergebnisse von Experiment 2 lassen darauf schließen, dass es im sensomotorischen System

infolge des gemischten Trainings nach der Prismenadaptation zu einer leichten aber

systematischen Unterschätzung der räumlichem Distanz zum Ziel kommt, durch die je nach


Richtung, in der das Ziel liegt, die Größe des Generalisierungs-Nacheffekts erhöht bzw.

erniedrigt wird. Dabei scheint die Richtungsinformation einen stärkeren Einfluss auf die

Größe des Nacheffekts zu haben als die Art der räumlichen Aufgabe (Extrapolation vs.

Interpolation). Studie 3 bekräftigt damit, dass die Prismenadaptation räumliche

Repräsentationen im Gehirn verändert, wobei auch die Form des sensomotorischen Trainings

einen spezifischen Einfluss auf die Art dieser Veränderungen hat.

Fazit 27

4. Fazit

Menschliche Versuchspersonen weisen eine bemerkenswert schnelle Fähigkeit auf,

zielgerichtete Zeige- oder Wurfbewegungen anzupassen, wenn es durch Prismen zu einer

Manipulation der sensomotorischen Kopplung kommt. Die Fähigkeit zur Prismenadaptation

setzt die funktionelle Plastizität des sensomotorischen Systems voraus und das experimentelle

Paradigma der Prismenadaptation eignet sich gut dazu, verhaltensdynamische Prozesse

psychophysikalisch zu untersuchen.

Die funktionellen Charakteristika des Adaptationsprozesses hängen von Faktoren wie der

Variabilität bei der Ausführung einer zielgerichteten Bewegung (Studie 1), der

sensomotorischen Aufgabe, die während der Adaptation ausgeführt wird (Studie 2) und dem

räumlichen Kontext der Aufgabe sowie der Art des sensomotorischen Trainings ab (Studie 3).

Der Adaptationsprozess ist dabei spezifisch für die aktuell ausgeführte Aufgabe und

generalisiert nicht auf eine Bewegung aus einer anderen Bewegungsfamilie; dagegen kommt

es zu einer räumlichen Generalisierung der Adaptation auf neue Ziele, sofern dieselbe

sensomotorische Aufgabe (Zeigen) ausgeführt wird.

Der Prozess der Prismenadaptation weist bereits auf Verhaltensebene ein hohes Maß an

Komplexität auf; um sowohl die funktionellen als auch die strukturellen Grundlagen der

Prismenadaptation besser zu verstehen, wäre die Kombination von psychophysikalischen und

neurophysiologischen bzw. bildgebenden Methoden ein viel versprechender Ansatz. Bei der

experimentellen Untersuchung darf in keinem Fall die Komplexität des Adaptationsprozesses

unterschätzt werden, was sich auch in einem abschließenden Zitat von Redding et al. (2005,

S. 440) widerspiegelt: „Prism adaptation is not a simple process“. Wie wahr.

Studie 1: Vollständigkeit des Adaptationsprozesses 28

5. Studie 1 Incomplete visuomotor adaptation despite extensive training

Sven Wischhusen & Manfred Fahle

Abstract

Prism adaptation demonstrates that visuomotor representations in the brain are rapidly

adjusted when prisms induce a displacement of the visual world. We investigated the speed

and extent of prism adaptation after extensive visuomotor training. Human subjects had to

perform visually-guided throwing or pointing movements towards a target before, during and

after wearing prism goggles that shifted the visual world laterally either to the right or left. In

each condition of each task, 120 movements were performed to ensure extensive training. Our

results indicate that prism adaptation was not complete when subjects performed throwing

movements since throws still deviated laterally at the end of the adaptation period; even after

an extended training of 240 throws, the remaining lateral deviation amounted to 29 mm. That

is, training did not yield complete adaptation for throwing movements. When subjects

performed pointing movements the remaining lateral deviation at the end of the adaptation

period failed to reach significance. In both tasks, removal of the prisms led to an aftereffect

which completely disappeared in the course of further training. The findings of incomplete

prism adaptation are discussed in terms of movement variability in combination with an

adaptive neural control system exhibiting a finite capacity for evaluating movement errors.

Introduction

Prism adaptation served as an experimental paradigm to study the mechanisms of adaptation

in neural representations of the physical world as a response to changes in sensory signals.

This adaptation demonstrates plasticity in the adult human brain, as do priming, perceptual,

and sensorimotor learning (Ahissar & Hochstein, 2004; Fahle, 2002).

Phenomenology of prism adaptation

Suitable prisms deflect the ray paths laterally and shift the retinal images of the visual world

causing a deviation between the felt direction of gaze versus position of arm: Subjects

wearing prism goggles initially fail to execute accurate goal-directed movements (e.g.

pointing, reaching, or throwing) towards a visual target because their sensory and motor


coordinate systems do not correspond properly (Martin et al., 1996b; 2001; 2002; Norris et

al., 2001). The movements’ lateral error is proportional to the magnitude of the prismatic

deflection applied, although it is a common observation that initial prism effects are smaller

than expected according to the optics of the prisms (e.g. Redding & Wallace, 2003b; Redding

& Wallace, 2004). Within a few trials under visual feedback, the movements’ lateral error is

reduced and trajectories recover high spatial accuracy. That is, subjects adapt to the optical

displacement of the visual world, a process of sensorimotor adaptation termed “prism

adaptation” (e.g. Bedford, 1999; Fernandez-Ruiz & Diaz, 1999; Harris, 1963; 1965; 1980;

Held & Freedman, 1963; Redding et al., 2005; Redding & Wallace, 2003a).

After removal of the prisms, on the other hand, movements initially deviate in the direction

opposite to the prismatic displacement, indicating a negative aftereffect which completely

vanishes in the course of further visuomotor practice if feedback is provided (e.g. Fernandez-

Ruiz & Diaz, 1999; Harris, 1965; 1980; Newport et al., 2006; Redding et al., 2005; Weiner et

al., 1983; Welch et al., 1974). The occurrence of an aftereffect is considered to prove “true”

adaptation because it indicates a spatial realignment of sensorimotor representations through

adaptation rather than a purely cognitive adaptation (Newport & Jackson, 2006). According to

the model of Redding & Wallace (2002) two closely related processes operate during prism

adaptation: first, a strategic recalibration mechanism based on cognitive control leading to

rapid error reduction during prism exposure and second a rather slow spatial realignment

mechanism yielding correspondence between different sensorimotor reference frames. During

prism adaptation, sensorimotor representations are rapidly adjusted in an experience-

dependent way to ensure high precision of eye-hand coordination which is essential to interact

with objects in space, followed by a slower process of spatial realignment.

The process of prism adaptation demonstrates that even in the adult brain sensorimotor

representations can maintain a rather high degree of plasticity in order to adjust neural

representations to altered environmental conditions. In this respect, similarities exist with the

effects of perceptual learning (see Fahle, 2008, in press; Gilbert et al., 2001).

Neural substrates of prism adaptation

Although a large number of studies on prism adaptation have been conducted in both humans

and non-human primates, the neural mechanisms and underlying neural substrates remain to

be elucidated. Converging experimental evidence from both monkeys (e.g. Baizer et al., 1999;

Kitazawa & Yin, 2002) and humans (e.g. Luaute et al., 2006; Martin et al., 1996a; 2002;

Pisella et al., 2005; Weiner et al., 1983) suggests a crucial role of the cerebellum during the


adaptation process, which is consistent with the view that the cerebellum is a major

subcortical structure for motor learning and movement adaptation (for reviews see Doyon &

Benali, 2005; Marr, 1969; Robinson, 1995; Shadmehr & Wise, 2005).

Furthermore, two studies on a patient with bilateral damage to the posterior parietal cortex

(PPC) found specific deficits in the ability to adapt to the optical displacement induced by

prisms, suggesting that the PPC is involved in the adaptive spatial updating of sensorimotor

representations (Newport et al., 2006; Newport & Jackson, 2006). In line with these findings,

a PET study on prism adaptation by Clower et al. (1996) reported adaptation-related

activation in a focal region of the PPC contralateral to the reaching limb confirming the

functional role of the PPC in the integration and alignment of different sensory (e.g. visual

and proprioceptive) input signals for motor output (Scherberger & Andersen, 2003; Shadmehr

& Wise, 2005; but cf. Redding et al., 2005). In an animal study, Kurata & Hoshi (1999)

demonstrated that monkeys with temporary inactivation of the ventral premotor cortex (PMv)

had deficits in prism adaptation. All the brain areas mentioned are known to be involved in

motor control.

In addition, a study on long-term adaptation (over several months) to a left-right reversal of

the visual field in monkeys found functional changes of neurons’ properties in primary visual

cortex (V1) indicating that long-term adaptation to reversal of the visual field may involve

large-scale reorganization – probably entirely through recalibration – even on a very early

level of visual cortical processing (Sugita, 1996).

In summary, prism adaptation involves a functional realignment of different sensory input

signals which is likely accomplished by plasticity of an extended cortico-cerebellar network

in the brain, with recalibration possibly achieved primarily in cerebral cortex and realignment

realized primarily in cerebellum (Redding et al., 2005).

Speed and extent of prism adaptation

In most studies examining prism adaptation in humans, the number of trials during the

adaptation period varied between 20 and 40 movements (e.g. Fernandez-Ruiz et al., 2000;

2003; 2004; Fernandez-Ruiz & Diaz 1999; Kitazawa et al., 1995; Martin et al., 1996a; 1996b;

Roller et al., 2001). Typically, this period of visuomotor training was sufficient for adaptation

to take place since error reduction occurred and aftereffects were observed upon removal of

the prisms. However, when we conducted pilot experiments in which subjects had to throw a

ball towards a visual target while wearing prism goggles, movements deviated laterally in the

direction of the prismatic displacement even at the end of the adaptation period comprising 30


trials. That is, although subjects were able to adjust their throws on a trial by trial basis and

movements gradually approached the target, throwing accuracy at the end of the prism

condition was clearly worse than in the baseline condition due to an incomplete compensation

of the prism effect.

We wondered whether this incompleteness of adaptation in the throwing task was due to an

insufficient number of trials during the adaptation period and therefore increased the number

of trials substantially to ensure extensive visuomotor training. A remaining lateral deviation of

movements in the direction of the prismatic displacement following an extensive period of

training would indicate that the remaining error was not caused primarily by an insufficient

number of trials. Rather, different amounts of adaptation could result from different extents of

neural plasticity in the task-related sensorimotor representations.

In order to control for effects of task-specificity, completeness of prism adaptation was

examined in two different visuomotor tasks, namely pointing and throwing. These two tasks

test movements of different skill level, and of different distances. Hence, investigating both

tasks allows to compare the completeness of prism adaptation to near space, a high level skill,

with a low level skill to far space. The results indeed highlight important differences between

adaptation under these different conditions.

Our results demonstrate a clearly incomplete adaptation process. Spatial deviation remained

significant in the Throwing Experiment even after extensive adaptation. On the other hand, the

remaining lateral deviation in the Pointing Experiment failed to reach significance indicating

complete adaptation. To the best of our knowledge, this incompleteness of adaptation has so

far not received any attempt at explanation. We here conclude that sensorimotor

representations for pointing exhibit more experience-dependent plasticity in order to ensure

high precision of visually-guided movements in the peripersonal workspace. More

importantly, the prismatic displacement is not completely compensated even after extensive

training for throwing movements. This remaining error indicates a limited integration capacity

of the neural processes underlying this type of plasticity.

Methods

Experimental setup and procedure

In the Throwing Experiment, subjects’ task was to throw softballs (24 g, 5.0 cm diameter) as

accurately as possible towards a visual target on a 1.5 m x 1.5 m wide wall. The target was a

blue spot (2.0 cm diameter) attached to the wall at a height of 156 cm. Subjects stood upright


with their mid-sagittal plane aligned with the target at a viewing distance of 2.0 m (Fig. 5.1a).

With their head being unrestrained, subjects always had an unobstructed binocular view of the

target. The experiment was conducted under daylight illumination.

The wall was layered with Velcro material and the softball adhered to the wall after each

throw. In order to assess spatial accuracy of the throws, a photo was taken after each throw

using a digital camera which was kept at a fixed location during the entire experiment. A

Matlab-based program (Matlab release 12.1) was used to readout the jpeg-files generated by

the camera and to compute the horizontal and vertical distances between the target and the

position of the ball in a metric system (cm) by means of trigonometry. Spatial accuracy was

around 1 cm.

The wedge prisms of high optical quality (Carl Zeiss, Oberkochen/Germany) used shifted the

visual image laterally by 17 deg. either to the right (base-left prisms, 30 diopters) or left

(base-right prisms). Subjects had to perform overhand throws always using the right arm

while fixating the visual target and were instructed not to look at their arm when throwing in

order to avoid on-line corrections of the pre-planned movement. After a brief instruction,

subjects were asked to perform about 10 test throws to get used to the task.

The Throwing Experiment consisted of three conditions in the following order: i) pre-prism

condition (PRE; baseline measurement, prisms off), ii) prism condition (PRISM; adaptation,

prisms on) and iii) post-prism condition (POST; aftereffect, prisms off). In each condition,

120 throws had to be performed to ensure extensive training of the visuomotor task.

Throwing movements were moreover studied in an additional Control Experiment in which

the number of trials per condition was modified. Specifically, after a PRE condition of 60

throws, subjects had to execute 240 throws while wearing a prism goggle (PRISM condition);

the POST condition thereafter included 90 throws. This experiment was conducted only with

rightward shifting prisms and aimed to evaluate the effects of a further extended adaptation

period on the completeness of prism adaptation.

The spatial offset between the target and the impact of the ball was clearly visible after each

throw, hence immediate visual feedback about the precision of the throw was provided.

Between conditions, subjects had to keep the eyes closed in order to prevent habituation and

to minimize spatial reorientation which could decrease both the magnitude of the prism effect

and the aftereffect.


Fig. 5.1 A) Experimental setup of the Throwing Experiment in which subjects stood upright in front of a Velcro-layered wall at a distance of 2 m. Subjects’ body midline was centered with the target. The task was to throw a ball to the target. After each throw, a photo was taken using a digital camera. B) In the Pointing Experiment, subjects were sitting at a table and performed pointing movements towards a visual target which was fixed at the table’s edge. Subjects could not correct their movement on-line once it had started because of the table top being opaque but received direct visual feedback about their index finger’s position at the end of the trajectory. A PC-driven ultrasound measuring unit was placed in front of the table for assessing the movements’ spatial accuracy. Target and subject’s index finger were equipped with an ultrasound marker (microphone). C) Experimental groups tested.

In the Pointing Experiment, subjects had to perform speedy but accurate ballistic pointing

movements towards a visual target always using the right arm (Fig. 5.1b). During the

experiment, subjects were sitting at a table with their mid-sagittal plane aligned with the target

which was a small white disk fixed at the table’s edge at a distance of 65 cm from the subject.

Since the table-top was opaque, subjects could not see and hence not correct their movements

on-line once the movement had started. Consequently, the trajectory of the arm had to be

planned purely feed-forward on the basis of visual information about the target location in

space. Subjects viewed the target binocularly and had visual feedback about the position of

the index finger in relation to the target only at the end of the arm movement and could

therefore adjust the trajectory on a trial by trial basis, based on this trial to trial knowledge of

their results.

The movements’ accuracy was assessed using a PC-driven ultrasound measuring system

operating with high spatial resolution based on the travelling time of ultrasound pulses (Zebris

Medical, Isny/Germany). Ultrasound signals were sent out by an ultrasound measuring unit

and recorded by ultrasound microphones being attached to both the target and the subject’s


index finger. By means of a computer program, the horizontal distance between the index

finger and the target position was quantified for the endpoint of each individual movement

(measuring rate: 100 Hz).

Similar to the Throwing Experiment, the Pointing Experiment consisted of a PRE, PRISM,

and POST condition, each with 120 movements. Subjects we instructed to fixate the target

and to keep the eyes closed between conditions in order to prevent visual reorientation in

space. The wedge prisms used shifted the visual image laterally by 17 deg. either to the right

or left.

Experimental groups

Five experimental groups of right-handed human subjects were formed (Fig. 5.1c). For the

Throwing Experiment, two groups of 8 subjects each were studied: Group 1 (1 male, 7 female;

mean age 23.5 years) was exposed to rightward shifting prisms while group 2 (3 male, 5

female; mean age 23.4 years) was exposed to leftward shifting prisms. For the Pointing

Experiment, another two groups of 10 subjects each were formed. Members of group 3 (3

male, 7 female; mean age 23.9 years) were exposed to rightward shifting prisms while

members of group 4 (1 male, 9 female; mean age 24.1 years) wore leftward shifting ones in

the PRISM condition. In the Control Experiment, another 10 subjects (5 male, 5 female; mean

age 24.5 years) were exposed to rightward shifting prisms.

Subjects reported no history of brain or eye disorders and had normal or corrected-to-normal

visual acuity. Prior to participation, subjects gave informed consent in accordance with the

“Declaration of Helsinki” without knowledge of the exact purpose of the study. This type of

experiments was approved by the ethics committee of Bremen University.

Data analysis

We calculated the horizontal distance between the endpoint of the movement (Throwing

Experiment: position of the ball on the wall; Pointing Experiment: top of index finger at the

end of the trajectory) and the target for each movement in each condition and subject.

For further analysis, the data were baseline corrected: that is, we subtracted the mean of

deviations in the PRE condition from each data point (see also Clower & Boussaoud, 2000).

Baseline correction was conducted for each condition of each subject individually. The mean

of the PRE condition mirrors a subject’s general task-related visuomotor accuracy and

indicates a potential spatial bias of the movements. This bias averaged -0.7 cm (± 0.2 SEM) in

the Throwing Experiment, -0.8 cm (± 0.1 SEM) in the Pointing Experiment, and -0.3 cm (±


0.3 SEM) in the Control Experiment. The baseline correction normalized the data by

removing any spatial bias which could mask the effects of the prismatic displacement on the

movements’ accuracy and also allowed a better comparison between different subjects since

each set of data was normalized individually. A third advantage was the possibility of

conventional statistical analysis, i.e. to test the data against the value zero corresponding to

the individually normalized target of the task. Consequently, all data shown are baseline

corrected.

In order to analyze the data in terms of completeness of the adaptation process, we divided

each condition (PRE, PRISM, POST) into blocks of 30 subsequent throws each and calculated

the mean amount of target deviation for each block and every subject individually. Blocks

were averaged across subjects and tested against the value of zero (i.e. no deviation from

normalized target) using a two-sided t-test. In the analysis, we focused on the last block of the

PRISM and POST conditions since this value reflects the remaining lateral deviation.

Specifically, a last block of the PRISM condition differing significantly from zero indicates a

remaining lateral deviation at the end of the adaptation period hence suggesting incomplete

adaptation.

Results

Time course of prism adaptation in the Throwing and Pointing Experiment

Averaged data of experimental groups 1-4 are presented in Fig. 5.2 and Fig. 5.3. The lateral

deviation of movements’ endpoints from the target is plotted as a function of trial number in

the PRE, PRISM, and POST conditions, where negative values represent a leftward deviation

and positive values indicate a rightward deviation.

In the PRE condition, the lateral deviation from the target was close to zero in all four

experimental groups suggesting accurate motor performance. At the beginning of the PRISM

condition, movements deviated according to the direction of the prismatic deflection

introduced. Group 1 (throwing task, rightward shifting prisms) showed an initial prism effect

of +42.8 cm (± 4.2) decreasing to +4.3 cm (± 2.6) (Fig. 5.3a, upper panel). The negative

aftereffect averaged -38.8 cm (± 2.0) and declined to +3.5 cm (± 1.2). The decrease of

throwing movements’ lateral deviation in the course of both the PRISM and the POST

condition was statistically highly significant as revealed by a paired two-sided t-test

comparing trial 1 and trial 120 (p < .001).


Fig. 5.2 Lateral deviation of movements from the target in the PRE, PRISM and POST condition as a function of movement number in the (A) Throwing Experiment and the (B) Pointing Experiment for the rightward shifting prisms groups (upper panel) and the leftward shifting prisms groups (lower panel). Positive values on the ordinate indicate a rightward deviation from the target whereas negative values denote a leftward one (units in Throwing Experiment: cm; Pointing Experiment: mm). All data shown are baseline-corrected (means and SEM).

Group 2 (throwing task, leftward shifting prisms) exhibited an initial prism effect (throw 1) of

-41.1 cm (± 2.2 SEM) which was reduced to -3.2 cm (± 2.4) at the end of the PRISM

condition (throw 120) (Fig. 5.3a, lower panel). Upon removal of the prisms (POST condition,

throw 1), throwing movements initially deviated by +36.7 cm (± 3.7) to the right indicating a

negative aftereffect which was reduced to -0.8 cm (± 2.4) at the end of the POST condition

(throw 120). Again, the reduction of lateral deviations was highly significant in both

conditions (p < .001).

In the group of subjects wearing the rightward shifting prisms in the Pointing Experiment

(group 3), the prism effect declined from +166.5 mm (± 12.6) to -13.3 mm (± 7.9) in the

PRISM condition and the aftereffect diminished from -58.1 mm (± 11.0) to -14.2 mm (± 6.7)


(Fig. 5.3b, upper panel). Error reduction was significant in both the PRISM condition (p <

.001) and the POST condition (p < .01).

In group 4 (pointing task, leftward shifting prisms), the prism effect amounted to -78.8 mm (±

22.4) decreasing to -12.4 mm (± 8.4) (Fig. 5.3b, lower panel). Upon removal of the prisms,

the aftereffect reached +117.3 mm (± 11.1) and declined to -5.2 mm (± 6.1) at the end of the

POST condition. In both conditions, the decrease of the pointing movements’ lateral deviation

in the course of training was statistically significant (PRISM condition: p < .01; POST

condition: p < .001).

Fig. 5.3 Mean lateral deviation from the target of the first movement (black bars) and the last movement (white bars) in the PRISM and POST condition of the (A) Throwing Experiment and the (B) Pointing Experimentfor the rightward shifting prisms groups (upper panel) and the leftward shifting prisms groups (lower panel) (means and SEM). Asterisks indicate a statistically significant difference of the lateral deviation between the first movement and the last movement as revealed by a paired t-test.

To sum up, each experimental group showed a marked lateral deviation of movements in the

direction of the prismatic displacement once the prisms were introduced. The lateral error was

significantly reduced (Throwing Experiment) or even removed (Pointing Experiment) in the

course of visuomotor training. Conversely, upon removal of the prisms, an aftereffect in the

opposite direction emerged which likewise disappeared in the course of the POST condition.


Completeness of prism adaptation: block analysis

To assess whether complete adaptation was accomplished through practice in the Throwing

and Pointing Experiments, we divided each condition into blocks of 30 subsequent

movements and calculated the mean lateral deviation from the target for each block

individually. Averaged data are shown in Fig. 5.4.

Fig. 5.4 Block analysis of movements’ mean lateral deviation from the target in the PRE, PRISM and POST conditions in the (A) Throwing Experiment and the (B) Pointing Experiment for the rightward shifting prisms groups (upper panel) and the leftward shifting prisms groups (lower panel). For each subject, each condition was divided into four blocks of 30 subsequent movements and block means were calculated. Data shown represent group averages (means and SEM). Asterisks indicate blocks differing significantly from zero as revealed by a t-test.

In group 1 (throwing task, rightward shifting prisms; Fig. 5.4a, upper panel) no significant

lateral deviation was found for any block of the PRE condition (p > .05). However, in the

PRISM condition that followed, each block differed highly significantly from zero (p < .001)

and the block-averaged lateral deviation was explicit even in block 4 where it reached +5.0

cm (± 0.9). In the POST condition, the lateral deviation amounted to -10.8 cm (± 1.0) in block


1 and -2.6 cm (± 0.5) in block 2 yielding a significant difference from zero (block 1: p < .001;

block 2: p < .01). In contrast, the mean lateral deviation of blocks 3 and 4 was very close to

zero (+0.1 cm in both blocks) and statistical analysis did not show a significant difference

from zero (p > .05).

In group 2 (throwing task, leftward shifting prisms; Fig. 5.4a, lower panel), the first block of

the PRE condition differed significantly from zero (p < .05) which was presumably due to a

larger movement variability at the beginning of the condition. In the remaining three blocks of

the PRE condition, movements’ mean lateral deviation was negligible. In the PRISM

condition, the mean of block 1 reached -12.6 cm (± 1.1 SEM), sharply decreasing to -3.6 cm

(± 1.0) in block 2, further decreasing to -1.8 cm (± 0.8) in block 3 and increasing to -2.3 cm (±

0.7) in block 4. All blocks were found to differ significantly from zero (block 1: p < .001;

block 2: p < .01; block 3: p < .05; block 4: p < .05). In the POST condition, the average

aftereffect was +11.5 cm (± 1.2) in block 1 and decreased to +2.6 cm (± 0.8) in block 2,

reached +0.4 cm (± 0.6) in block 3 and +0.2 cm (± 0.4) in block 4. While block 1 (p < .001)

and block 2 (p < .05) differed significantly from zero, this was not the case for the last two

blocks of the POST condition (p > .05).

Both groups of the Throwing Experiment showed an identical pattern of results: in the PRISM

condition, the mean lateral deviation decreased across blocks but a significant lateral

deviation was still present in the last block suggesting that subjects did not regain baseline-

like motor accuracy in the course of training. Conversely, in the POST condition only the first

two blocks differed significantly from zero and throwing movements did not deviate laterally

in the last two blocks. Here, subjects’ visuomotor performance returned to the pre-prism

accuracy.

In group 3 (pointing task, rightward shifting prisms; Fig. 5.4b, upper panel), no block of the

PRE condition differed significantly from zero (p > .05) and the mean lateral deviation was

marginal. In the PRISM condition, block 1 reached +20.6 mm (± 6.9) and showed a

significant difference from zero (p < .05) whereas in the other blocks the averaged lateral

deviation was small and did not differ significantly from zero (p > .05). In the POST

condition, only the first block differed significantly from zero (-18.3 mm ± 5.3; p < .01) while

the remaining blocks did not (p > .05)

Group 4 (pointing task, leftward shifting prisms; Fig. 5.4b, lower panel) showed a similar

pattern of results as the former group. The results of the four blocks of the PRE condition

were close to the normalized target position – although blocks 1 and 4 yielded a significant


difference from zero (block 1: p < .05; block 4: p < .01). In the PRISM condition, the

averaged lateral deviation of pointing movements decreased stepwise from block 1 (-30.6 mm

± 9.4) to block 4 (-4.9 mm ± 3.3). While the results of the first three blocks differed

significantly from zero (block 1: p < .01; block 2: p < .001; block 3: p < .05), this did not

apply for block 4 (p > .05). In the POST condition, only block 1 with a mean lateral deviation

of +13.3 mm (± 4.3) differed significantly from zero (p < .05), whereas the remaining blocks

were close to zero and without a significant deviation (p > .05).

In the PRISM condition, both groups of the Pointing Experiment showed a similar pattern of

results: while the first blocks exhibited a considerable lateral deviation due to the prismatic

deflection introduced, the last block of 30 pointing movements did not differ significantly

from zero. That is, subjects’ pointing accuracy returned to a pre-prism exposure level in the

course of the adaptation period. This result represents the most important difference to the

Throwing Experiment in which a significant lateral deviation remained even at the end of the

PRISM condition. Furthermore, within the course of the POST condition, pointing

movements rapidly reached baseline-like accuracy since the lateral deviation was no longer

significantly different from zero in blocks 2-4. This is essentially identical to the results of the

Throwing Experiment.

Control Experiment: extended visuomotor training in the PRISM condition

Similar to the Throwing Experiment, subjects had to perform throwing movements in the

Control Experiment (Fig. 5.5). In the PRISM condition, the number of throws was doubled to

240 trials in order to evaluate the effect of an extended training period on the completeness of

the adaptation process. In the PRE condition (60 throws), the lateral deviation of throws was

close to zero (Fig. 5.5a). When the prisms were introduced (PRISM condition), the first throw

deviated strongly by +49.1 cm (± 1.7) to the right but subjects decreased their movements’

lateral errors significantly (p < .001; paired two-sided t-test comparing throw 1 and 240) on a

trial by trial basis during the PRISM condition, i.e. they adapted. Removal of the prisms

(POST condition) led to an aftereffect of -43.7 cm in the first throw but the lateral deviation

of throws was significantly (p < .001) reduced by throw 90. An exponential decay function

fitted to the averaged data of the PRISM condition showed an offset of +2.9 cm (Tab. 5.1).

The adaptation process observed in the Control Experiment was slightly slower than in the

conventional Throwing Experiment.


Fig. 5.5 Control Experiment. A) Mean lateral deviation of throws in PRE, PRISM, and POST condition as a function of trial number (means and SEM). B) Block analysis of throws’ mean lateral deviation in the PRE, PRISM and POST condition (means and SEM). For each subject, each condition was divided into blocks of 30 throws and block means were calculated. These were averaged across subjects and tested against the value zero using a t-test. Asterisks indicate blocks differing significantly from zero.

Data of the Control Experiment were also analyzed block-wise (Fig. 5.5b). A paired two-

sided t-test revealed that all eight blocks of the PRISM condition differed significantly from

zero (block 1: p < .001; block 2: p < .01; block 3-8: p < .05). Most importantly, the last block

(block 8, throws 211-240) with a mean lateral deviation of +2.4 cm (± 1.0) differed

significantly from zero indicating incomplete adaptation. That is, even at the end of an

extended period of visuomotor training throws still deviated significantly from the target.

Interestingly, in the last four blocks of the PRISM condition the averaged lateral deviation of

throws was quite similar in magnitude (block 5: +3.1 cm; block 6: +3.0 cm; block 7: +3.0 cm;

block 8: +2.4 cm) suggesting that training in the second half of the PRISM condition did not

give rise to a more complete adaptation process. These results substantiate the findings of the

shorter Throwing Experiment in which incomplete adaptation had been observed after 120

throws under prism exposure.


Correlation between throwing variability and completeness of adaptation

To evaluate the impact of the individual visuomotor performance on the amount of the

adaptation, we analyzed the correlation between each subject’s variance of movements and

the remaining lateral deviation at the end of the PRISM condition in the Throwing and the

Pointing Experiment. For both experiments data from the rightward and the leftward shifting

prisms groups were pooled separately to increase statistical power.

Fig. 5.6 A) Throwing Experiment, mean of the last 10 movements of the PRISM condition as a function of the variance of the last 10 movements of the PRE condition for the leftward shifting prisms group (filled symbols) and the rightward shifting prisms group (open symbols). For analysis, data of both groups were pooled to increase statistical power (n = 16). Each data point represents data of one subject. Statistical analysis revealed a significant correlation of the two parameters (p < .01). B) Identical plot for the pooled data obtained in the Pointing Experiment(n = 20). Here, correlation analysis failed to reach a level of significance (p > .05).

Fig. 5.6 shows the mean lateral deviation of the last 10 movements of the PRISM condition

(in absolute values) as a function of the variance of the last 10 movements of the PRE

condition which is a good indicator of a subject’s variability in our visuomotor task. We

conceived that a highly precise motor performance yields a low trial by trial variability (i.e. in

mathematical terms: a low variance). In the Throwing Experiment (Fig. 5.6a), a significant

positive correlation (Pearson correlation coefficient: r = +0.635, p < .01) between the two

parameters was found. The slope of the linear regression line was 0.076. That is, the higher


the general variability of throws in the PRE condition, the higher was the remaining lateral

deviation of throws in the PRISM condition, and vice versa. Thus, the amount of remaining

error of an individual seems to be related to this individual’s throwing variability. In contrast,

no significant correlation existed in the Pointing Experiment (p > .05; Fig. 5.6b). Here, the

movements’ variance was only weakly correlated with the amount of adaptation (r = +0.231)

and the slope of the corresponding linear regression line was shallow (0.013).

Tab. 5.1 Averaged data of the PRISM and POST condition from each experimental group were fitted with an exponential decay function of the form . Whereas a1 represents an estimate of the spatial error of the initial movement, a2 indicates the speed of the adaptation (PRISM) and de-adaptation (POST) process and a3 gives an estimate of the remaining spatial offset of the movements at the end of the condition.

Discussion

In the present study, we examined the effects of extensive training of a visuomotor task on the

completeness of prism adaptation in human subjects and found that adaptation was

incomplete in the Throwing Experiment. Adaptation in the Pointing Experiment was more

complete, with no significant error remaining at the end of the (much faster) adaptation

process. The amount of prism adaptation therefore depended on the precise visuomotor task

performed but was unrelated to the direction of the visual world’s lateral displacement

induced by the prisms. That is, both the rightward and the leftward shifting prisms produced

incomplete adaptation in the Throwing Experiment. The results of the Control Experiment in

which the number of throws during prism exposure was doubled to 240 are consistent with the

findings of the Throwing Experiment: Even after 240 throws a significant lateral deviation

was present strongly indicating that after a rather fast period of improvement, even a very

large number of throws does not produce a perfect adjustment of sensory and motor

coordinate systems. Even after this extensive practice of 240 throws the mean remaining error

was as large as almost 30 mm, a deviation that can be easily perceived – and should be

corrected.

312)( aeaxf xa +=


Accurate pre-exposure visuomotor performance was evident in all groups since the average

lateral deviation of both throwing and pointing movements was small in the PRE condition.

Introducing the prisms initially shifted movements away from the target but subjects rapidly

recovered visuomotor accuracy in the course of training. During exposure, the movements’

lateral deviation decayed exponentially and this process of error reduction is supposed to rely

on a rapidly operating strategic recalibration mechanism and a slower realignment mechanism

as suggested by the model of Redding & Wallace (2002). In all groups studied, the reduction

of the movements’ lateral deviation within the PRISM condition was pronounced and

statistically reliable (see Fig. 5.3) suggesting that the strategic recalibration mechanism

worked well. As expected and well documented by earlier studies, a distinct negative

aftereffect in the direction opposite to the prismatic displacement occurred as soon as the

prisms were removed. In all groups, the negative aftereffect completely disappeared in the

course of training, consistent with the view that newly acquired visuospatial coordinations are

more labile (Fernandez-Ruiz & Diaz, 1999).

Speed and extent of prism adaptation depend on the visuomotor task

Precise pre-exposure visuomotor performance, a pronounced prism effect and a significant

error reduction during exposure as well as the appearance of a negative aftereffect are well

documented results in the prism adaptation literature – so what is the main novel finding of

our study?

As to be expected, (near) complete prism adaptation took place in the Pointing Experiment.

The most surprising result is that even extensive training did not yield complete adaptation for

throwing movements. Although subjects were able to reduce their movements’ lateral error in

the course of the PRISM condition, they did not reach pre-exposure accuracy levels even

through extensive throwing training. Rather, throwing movements deviated systematically in

the direction of the prismatic displacement throughout the adaptation period – irrespective of

whether this period covered 120 or even 240 throws. Hence, prism adaptation was clearly

incomplete for throwing movements.

An exponential decay function fitted to the averaged data (Tab. 5.1) of the Throwing and

Control Experiment shows that the results of the PRISM condition asymptotically approach

not zero deviation but maintain a certain “persisting deviation” that is related to a subject’s

variability of results. The offset of the decay function amounted to +58 mm (r² = 0.93) in the

rightward shifting prisms group and to -25 mm (r² = 0.92) in the leftward shifting prisms


groups. In the Control Experiment, after 240 throws the decay function still exhibited an

offset of +29 mm (r² = 0.96). At first glance, this does not seem to be a large effect but note

that +29 mm is the value the function is approaching to for an infinite number of throws – a

value which is clearly offset relative to the target.

In contrast, the same mathematical procedure applied to the PRISM condition data of the

Pointing Experiment yielded an offset of only -3 mm (r² = 0.92) for the rightward shifting

prisms group and -7 mm (r² = 0.90) for the leftward shifting prisms group. These small

deviations failed to reach significance.

Which other factors are conceived to affect the adaptation process? Kitazawa et al. (1995)

have shown that both the rate and the amount of prism adaptation (measured as the magnitude

of the aftereffect) critically depend on the availability of visual feedback information after the

completion of the movement. In humans, a delay of > 50 ms between the end of a reaching

movement and the onset of visual feedback significantly reduced both the rate and the amount

of prism adaptation. Therefore, the adaptation mechanism primarily accesses visual feedback

information within a temporal window of ~ 50 ms after movement completion. If visual

feedback is delayed by more than 50 ms, the adaptation process becomes slower and less

complete, i.e. aftereffects decrease (but note that aftereffects are still observed). These results

were confirmed in a monkey study by Kitazawa & Yin (2002). Apart from the fact that the

Kitazawa et al. study measured the amount of prism adaptation indirectly by taking the

magnitude of the aftereffect, the task-related difference in the completeness of the adaptation

process observed in our data cannot easily be explained by means of delayed visual feedback

information about the outcome of the movement since immediate visual feedback was always

provided in both tasks. Subjects perceived the spatial offset between the endpoint of the

movement and the target as soon as the movement was completed, hence there was no delay

of visual information apart from the “flight time” of the balls in the Throwing Experiment.

This lack of feedback information during the flight time is unlikely to explain incomplete

prism adaptation in the Throwing Experiment.

In a recent study, Michel et al. (2007) compared the magnitude of the negative aftereffect in

two groups of human subjects: The first group was adapted to prisms in a stepwise manner

from 2 deg. to 10 deg. optical displacement while the second group was adapted in a single

step to a 10 deg. optical displacement. While the first group was not aware of the progressive

prismatic shift during exposure to the prisms, the second group experienced the abrupt shift of

the visual world when exposed to the prisms. Most importantly, the negative aftereffect was


significantly larger in the “unaware” (multiple step) group as compared to the “aware” (single

step) group. This led to the conclusion that unawareness of prismatic exposure enhances

adaptation while awareness is suggested to play a detrimental role on the adaptation process.

Following this line of argumentation, complete adaptation might be accomplished by active

extensive training of a visuomotor task while leaving the subjects unaware of the prismatic

shift induced. In our experiments, we employed a horizontal shift of the visual world by 17

deg. either to the right or to the left and this large and easily detectable amount of visual

displacement made subjects aware of the prismatic shift. This applies for the Throwing

Experiment as well as for the Pointing Experiment and hence a difference in the “state of

awareness” of the prismatic shift cannot explain why complete adaptation was only observed

in the Pointing Experiment where error reduction during the PRISM condition led to

visuomotor accuracy similar to the PRE condition. That is, although subjects viewed the

target as laterally displaced through the prisms, their pointing movements became as precise

as without prisms during the course of training. In contrast, error reduction during prism

exposure in the Throwing Experiment did not reach pre-exposure levels of visuomotor

accuracy.

Plasticity of visuomotor representations

One possible explanation for the task-related difference in the completeness of prism

adaptation could be different extents of neural plasticity in the task-related visuomotor

representations. The amount of practice-induced reorganization of visuomotor representations

may critically depend upon the spatial requirements in the task-related workspace.

Generally, the near (peripersonal) space of a person within arms’ reach is primarily concerned

with highly skilled motor activities (that is why peripersonal space is also termed “action

space”) whereas the (extrapersonal) space beyond arms’ reach is mainly devoted to perception

(Previc, 1998). It has been shown that prism adaptation can affect neural representations of

both peripersonal and extrapersonal space (Berberovic & Mattingley, 2003).

In our experiments, subjects’ workspace differed according to the task performed: while

throwing movements were executed within extrapersonal space, the pointing movements

covered peripersonal space. A precise eye-hand coordination in peripersonal space is of high

behavioral relevance and requires the continuous and spatially fine-tuned adjustment of the

underlying visuomotor representations.

When the prisms are introduced, precise eye-hand coordination is suddenly disrupted and

pointing movements initially exhibit a distinct lateral deviation. An “internal” error signal (see


next section) triggers the updating of visuomotor representations for pointing, a process

requiring neural plasticity. The experience-dependent adjustment of visuomotor

representations progresses until visuomotor performance is as accurate as it was before the

displacement of the visual world.

The incompleteness of prism adaptation observed especially for the throwing movements in

extrapersonal space may be attributed to a lesser extent of plasticity in the corresponding

visuomotor representation possibly due to a less direct coupling between visual feedback

regarding external objects (the position of the ball on the wall) versus body parts (position of

the hand) or else to the difference between a high level skill (pointing) and a low level one

(throwing). To be clear: there was substantial adaptation to the prismatic deflection during the

Throwing Experiment since both error reduction and aftereffects were observed. The main

difference to the Pointing Experiment is that the completeness of spatial compensation during

prism exposure was clearly less pronounced in the Throwing Experiment. Therefore, the

visuomotor representations for throwing movements were not as fast and precisely adjusted

by visual feedback as it was the case for the pointing representations.

We cannot completely exclude the possibility that a further increase in the number of

throwing trials during exposure could in principle lead to complete prism adaptation, but as

demonstrated in the Control Experiment, even doubling the number of training throws did not

lead to complete adaptation and deviations did not even converge towards zero remaining

error. Instead, the asymptotic adaptation curves are clearly offset from zero (Tab. 5.1).

Throwing variability limits complete prism adaptation if the neural integration capacity is

finite

In general, even skilled or well-practiced movements vary from trial to trial, yielding a certain

degree of movement variability which may result from variability during the execution of a

specific movement (e.g. van Beers et al., 2004) or from variability during motor preparation

or from both. Churchland et al. (2006) demonstrated in a monkey single-cell study that a

substantial amount (> 50 %) of movement variability resulted from neural variability during

movement preparation in cortical motor areas.

We found a significant positive correlation between the individual’s (general) throwing

variability and the remaining lateral deviation of throws at the end of the PRISM condition

(see Fig. 5.6). With increasing movement variability, the remaining lateral error increased in a

linear way. Conversely, the lower the variability of movements the lower was the remaining


lateral error at the end of the adaptation period. What may be the functional relevance of this

observation?

We hypothesize that the size of the remaining error critically depends upon a neural error

signal that subjects have to generate by integrating throwing errors over a number of

sequential trials. In individuals exhibiting a high degree of throwing variability, the

“averaged” error signal is corrupted by a large proportion of noise and thus the remaining

lateral deviation at the end of the adaptation period is large. On the other hand, individuals

with a lower variability generate an error signal with a better signal-to-noise ratio and as a

consequence, the adjustment of throwing movements is spatially more fine-tuned resulting in

a smaller remaining lateral deviation at the end of the adaptation period.

However, this variability as such would only slow down adaptation but cannot by itself

explain the large residual error. It is important in this context that each individual’s

(sensorimotor) system has a finite integration capacity to integrate throwing errors within a

temporal interval in order to form an error signal. The results are compatible with a neural

system with a limited “memory” that tries to optimize behavior by adapting specific

parameters. If we adopt the reasonable assumption that the system has a limited integration

capacity over time, given a chosen confidence level and limited number of throws (n), the

variance of throws ( ²) determines the point in time at which adaptation stops since the system

is no longer “sure” that additional adaptation is required. This is the case if the confidence

interval calculated on the basis of ² and n includes zero deviation. On the basis of a given

confidence level (i.e. .05), “n” can be calculated by the following formula where x is the

mean lateral deviation over n throws:

If the individual’s integration capacity is small, only few trials can be averaged to form the

error signal and the – in mathematical terms – “standard error” of this signal is quite large.

Conversely, individuals with a larger integration capacity integrate the error signals over a

larger number of trials. Since the proportion of noise within an average decreases as a

function of the square root of the number of trials, the internal error signal is less corrupted by

noise and the adjustment of throwing movements is more accurate. Therefore, the remaining

lateral deviation at the end of the adaptation period would be less pronounced in subjects with

a large integration capacity.

This model fits very well with recent experiments on eye-hand-coordination in balancing a

(virtual) stick. Patzelt et al. (2007) were able to model human control dynamics in much detail

2²2��

��

�=

xn δ


for this complex system by assuming that the memory of humans for on-line adaptation is

rather short (in their case in the second range). They conclude that the human nervous system

employs adaptive motor control using only a very limited memory of past observations for

parameter adaptation – well in line with our results in the Throwing Experiment.

On the basis of our experiments, we can only speculate about the neural generators of a

movement-related error signal. However, Kitazawa et al. (1998) reported that in the

cerebellum complex spikes of Purkinje cells convey information about the relative error of

reaching movements. Besides that, Greger & Norris (2005) have shown that even the simple

spike firing of cerebellar neurons was modulated by the spatial accuracy of a goal-directed

movement. The error-related neural signal originating in the cerebellum might trigger the

functional adjustment of visuomotor representations (both realignment and recalibration) in

the course of prism adaptation.

In the present study, we demonstrate that the completeness of prism adaptation depends on the

visuomotor task tested. Whereas extensive training of pointing movements led to a near

complete compensation of the prismatic shift, prism adaptation was incomplete when subjects

executed goal-directed throwing movements and a significant lateral deviation was observed

even at the end of the adaptation period. The incompleteness of adaptation during throwing

movements may be attributed to visuomotor variability coupled with a limited capacity to

integrate errors over time and thus to evaluate the remaining mean error. Failing to realize the

remaining error obviously limits the extent of compensation through training. This

phenomenon may well be present in other types of adaptation processes.

Acknowledgments

Parts of this study were presented on a poster at the “5th Forum of European Neuroscience”

(FENS), Vienna/Austria, July 2006. The authors would like to thank D.C. Högl for the

assistance in collecting the data and D. Trenner for supplying the computer program for

assessing the data. We are also grateful to C. Grimsen for the valuable comments and

suggestions on the interpretation of the data. The authors declare that they have no competing

financial interests. Supported by grant 01GQ0705 (Bernstein programme) of the German

Federal Ministry of Education and Research (BMBF).

Studie 2: Aufgaben-Spezifität der Prismenadaptation 50

6. Studie 2 Task-specificity of prism adaptation: no transfer from pointing

to throwing


Abstract

Adaptation to a lateral shift of the visual world induced by prisms involves the experience-

dependent adjustment of neural representations according to task demands. The present study

examined the task-specificity of prism adaptation under different visual feedback conditions

in humans. First, subjects adapted to the prisms by performing pointing movements;

thereafter, the transfer of prism adaptation and aftereffect to an untrained throwing task was

tested. During adaptation in the pointing task, visual feedback was provided either at the

terminus of the movement (Exp. 1) or during its entire trajectory (Exp. 2). In both feedback

conditions, neither prism adaptation nor the aftereffect transferred to the untrained throwing

task. Switching to the throwing task evoked a second adaptation process when subjects kept

on wearing the prisms; removing the prisms after adaptation in the pointing task did not

produce an aftereffect in the throwing task. The same pattern of results was observed when

both task and arm trained were switched after prism adaptation indicating a lack of

intermanual transfer. The acquired visuomotor remapping was not accessible after the switch-

over to the novel task suggesting a strong task-specificity of prism adaptation irrespective of

the type of visual feedback.

Introduction

In a changing environment, the brain’s functional organization has to be continuously

adjusted to match the requirements of the physical world. The retention of neural plasticity in

the adult human brain becomes manifest in priming, perceptual learning, and adaptation

(Ahissar & Hochstein, 2004; Fahle, 2002). In the present study, prism adaptation was used as

an experimental approach to study i) the mechanisms adjusting visuomotor representations

according to prior experience and ii) the factors governing the generalization of visuomotor

adaptation.


Prism adaptation as an example of visuomotor adaptation

Suitable optical wedge prisms lead to a lateral deflection of the ray paths on the retina causing

a perceived horizontal shift of the visual world. As a consequence of the prism-induced

disparity between the direction of gaze and the felt arm position subjects wearing prism

goggles initially execute inaccurate visually guided movements which deviate in the direction

of the prismatic displacement. Under normal conditions, however, human subjects rapidly

adapt to the lateral displacement of the visual world: within a limited number of movements

under visual feedback, the lateral error is gradually reduced and movements recover high

spatial accuracy in the course of further practice. This process of re-establishing a functional

correspondence between sensory and motor coordinate systems is designated “prism

adaptation” (e.g. Bedford, 1999; Fernandez-Ruiz & Diaz, 1999; Harris, 1963; 1965; Martin et

al., 1996b; Welch, 1978).

When the prisms are removed subsequent to adaptation, movements initially deviate in the

direction opposite to the prismatic displacement, indicating a negative aftereffect which

completely disappears in the course of further practice (e.g. Fernandez-Ruiz & Diaz, 1999;

Fernandez-Ruiz et al., 2004; Harris, 1965; Newport et al., 2006; Norris et al., 2001; Redding

et al., 2005; Weiner et al., 1983; Welch et al., 1974). The occurrence of an aftereffect

indicates the experience-dependent adjustment of visuomotor representations in the course of

prism adaptation and therefore proves “true” visuomotor adaptation rather than an adaptation

process primarily based on cognitive control (Newport & Jackson, 2006).

During prism adaptation, visuomotor representations are adjusted according to task demands

in order to ensure a high precision of eye-hand coordination which is essential to manually

interact with objects in space. The adjustment of visuomotor representations is functionally

based on two closely related but separable mechanisms operating during adaptation: i) a

strategic control mechanism leading to a rapid sequential reduction of movement errors

during prism exposure and ii) a spatial realignment mechanism functionally re-linking sensory

and motor coordinate systems (for a theoretical framework see Redding et al., 2005; Redding

& Wallace, 2003a).

Activity of a cortico-cerebellar network during prism adaptation

What is known about the underlying neural processes during prism adaptation? Converging

experimental evidence suggests a contribution of different brain areas to the adaptation

process. Studies conducted in both monkeys (e.g. Baizer et al., 1999; Kitazawa & Yin, 2002)

and human neurological patients (e.g. Luaute et al., 2006; Martin et al., 1996a; 2002; Morton


& Bastian 2004; Pisella et al., 2005; Weiner et al., 1983) point to a specific role of the

cerebellum during prism adaptation. It is well established that the cerebellum in general plays

an important role in motor control and adaptation (Marr, 1969; Robinson, 1995; Thach et al.,

1992). Specifically, the spatial realignment mechanism yielding correspondence between

sensory and motor coordinate systems in the course of prism adaptation is mainly a cerebellar

function (Redding et al., 2005). Consistent with this fact, a reduction of aftereffects in human

cerebellar patients has been reported (Weiner et al., 1983) – but reduced aftereffects were also

observed in human patients suffering from basal ganglia disorders (Fernandez-Ruiz et al.,

2003).

Furthermore, the ability to adapt to a prismatic displacement of the visual world is explicitly

impaired in patients with damage to the posterior parietal cortex (PPC) (Newport et al., 2006;

Newport & Jackson, 2006), a cortical module being important for the planning and on-line

control of goal-directed visuomotor behavior (Buneo & Andersen, 2006). Neuroimaging

evidence for the involvement of the PPC during prism adaptation is supplied by a PET study

conducted by Clower et al. (1996) who found adaptation-related activation of the PPC

contralateral to the reaching limb. This suggests that the PPC is involved in the updating of

visuomotor representations in the course of adaptation to laterally displaced vision. Kurata &

Hoshi (1999) demonstrated that monkeys with a pharmacological inactivation of the ventral

premotor cortex (PMv) were impaired in adapting to the prismatic displacement suggesting a

contribution of frontal motor areas during visuomotor adaptation.

A prism-induced left-right reversal of the visual field, which is a highly artificial manipulation

of the visuomotor input-output relationship, has been shown to trigger neural modifications

even in early sensory cortical areas, such as primary visual cortex (V1): in monkeys wearing

left-right reversing prism goggles, a portion of V1 neurons began to respond to visual stimuli

presented in the ipsilateral visual field after a few months suggesting that this type of

adaptation is mediated by plastic processes in early visual processing (Sugita, 1996).

Psychophysical and functional MRI data from human subjects provide additional evidence for

neural modifications in early visual cortex in response to a reversed visual world (Miyauchi et

al., 2004; Tanaka et al., 2007).

Specificity of prism adaptation

The rapid adaptive remapping of visuomotor representations during prism exposure requires

the execution of a particular visuomotor task, for example goal-directed pointing or throwing

movements. In this respect, an important issue is whether a newly acquired visuomotor


mapping – the “result” of prism adaptation – transfers (generalizes) to another task which

differs from the exposure task. Generalization means to apply a function from previous

experience to a new situation. The understanding of the neural mechanisms underlying

generalization is essential for studying adaptive processes both in the sensory and motor

domains (Poggio & Bizzi, 2004).

Using the prism adaptation paradigm, a number of psychophysical studies have addressed the

task-specificity of the adaptation process and the conditions under which generalization from

one task to another occurs. For example, Martin et al. (1996b) demonstrated the specificity of

the negative aftereffect for the trained arm with no intermanual transfer to the untrained arm.

In a second experiment, the transfer of the aftereffect from overhand throws (exposure task) to

underhand throws (post-exposure task) was tested. Here, no aftereffect occurred when

subjects performed underhand throws after having adapted to the prismatic displacement by

executing overhand throws. These results suggest an adaptation process in which movement-

related parameters are adjusted in a task-specific way.

Moreover, Baily (1972) has shown incomplete transfer of prism adaptation from slow to fast

pointing movements. Consistent with this finding, Kitazawa et al. (1997) reported specificity

of prism adaptation for the velocity of reaching movements.

The amount of generalization from a trained task to an untrained one critically depends upon

the similarity between these tasks regarding, for example, movement kinematics, arm trained,

arm posture, velocity of movement, limb weighting etc. With increasing dissimilarity between

these two tasks, generalization decreases, a phenomenon that can be described in terms of a

generalization gradient (Baraduc & Wolpert, 2002; Redding & Wallace, 2006a).

Experimental questions

In the present study, we addressed the task-specificity of prism adaptation by testing the

generalization of a prism-induced visuomotor remapping from a pointing task to a throwing

task. More specifically, human subjects were adapted to a prism-induced rightward shift of

the visual world by executing visually-guided pointing movements. Thereafter, the direct

transfer of i) prism adaptation (prism goggles remain on after adaptation in the pointing task)

and ii) the aftereffect (removing prism goggles after adaptation) to the untrained throwing task

was tested. If the newly acquired visuomotor mapping would completely transfer, a switch-

over to the throwing task should not result in a substantial lateral deviation of throws (i.e.

small/absent prism effect) when keeping on prism goggles. Accordingly, a task-unspecific

adaptation process should yield an aftereffect after switching to the throwing task. On the


other hand, task-specific prism adaptation should produce a large prism effect and an absent

aftereffect upon switch-over to the throwing task. This pattern of results would indicate that

the new visuomotor mapping is not accessible when switching to the untrained task.

In order to investigate the influence of visual feedback availability on the generalization of

prism adaptation to the untrained task, two experiments with different visual feedback

conditions during pointing adaptation were carried out: in the first experiment (Terminal

Vision Experiment) subjects could use the tip of their index finger as a visual feedback signal

only at the terminus of the movement whereas the whole arm trajectory was visible in the

second experiment (Full Vision Experiment). In this context, we asked whether a specific type

of feedback information during adaptation would give rise to different amounts of

generalization from the trained to the untrained visuomotor task.

Methods

Experimental setup and procedure

In two experiments (Terminal Vision Experiment, Exp. 1; Full Vision Experiment, Exp. 2), we

tested the transfer of prism adaptation from a pointing task to a throwing task (Fig. 6.1). First,

subjects underwent an adaptation procedure while performing speedy but accurate ballistic

pointing movements to a visual target always using the right arm. In this pointing task,

subjects were sitting at a table with their body midline centered with the target which was a

small white mark at the table’s edge at a distance of 65 cm. Subjects viewed the target

binocularly.

Before adaptation, subjects always performed 30 pointing movements without wearing prism

goggles in order to familiarize with the task. Thereafter, subjects executed the same number

of pointing movements while wearing prism goggles which shifted the visual word laterally

by 17 deg. to the right (adaptation procedure, pointing task). Thirty pointing movements

during exposure to the prisms had to be performed in order to make sure that subjects adapted

sufficiently to the prismatic displacement (e.g. Newport & Jackson, 2006). The results of pilot

experiments confirmed that a total of 30 pointing movements were adequate for adaptation to

take place since proper aftereffects occurred upon removal of the prisms.

The only difference between the Terminal Vision Experiment and the Full Vision Experiment

was the kind of visual feedback information that subjects received during the pointing task. In

the Terminal Vision Experiment, the table top was opaque and subjects could not see and

hence not correct their trajectory before the movement had finished. In this case, the pointing


movement was planned purely feed-forward on the basis of the visual information about the

target location in space. In this experiment, subjects had visual information about the position

of the index finger in relation to the target only at the end of the arm movement. Because both

visual and proprioceptive feedback is available concurrently only at the terminal part of the

movement, this condition has also been termed “terminal exposure” (Redding et al., 2005; see

also Uhlarik & Canon, 1971).

Fig. 6.1 Experimental setup: In the pointing task, subjects adapted to the lateral displacement of the visual world by executing 30 goal-directed pointing movements while wearing prism goggles. Subjects were sitting at a table and had to point with their right arm as accurate as possible to a target at the table’s edge. Immediately after this adaptation procedure, the transfer of prism adaptation from the pointing task to the untrained throwing task was tested. Subjects stood upright in front of a Velcro-layered wall and had to perform throwing movements to a visual target. The transfer of prism adaptation (prisms on) and the aftereffect (prisms off) was tested either for the ipsilateral (adapted, right) arm and the contralateral (unadapted, left) arm. A digital photo was taken from a fixed position after each throw and stored on a PC for assessing spatial accuracy of the movements.

In contrast, the table top was removed in the Full Vision Experiment and hence subjects had

visual information about the ongoing arm movement during the entire trajectory. This

condition of “concurrent exposure” in which visual and proprioceptive feedback is available

concurrently during the whole movement causes a faster adaptation process (Redding et al.,

2005). Nevertheless, on-line corrections of movements during the Full Vision Experiment

were rather small since subjects fixated the target and did not attend to the arm trajectory.

Immediately after the adaptation procedure in the pointing task, the transfer of prism

adaptation to and the aftereffect in the throwing task were tested. In the throwing task,

subjects had to throw softballs (24 g, 5 cm diameter) as accurately as possible towards a

visual target on a 1.5 m x 1.5 m wide wall. The target was a blue spot (2 cm diameter)

attached to the wall at a height of 156 cm. Subjects stood upright at the same position as in the


pointing task with their mid-sagittal plane aligned with the target wall at a viewing distance of

2 m. The head being unrestrained, subjects always had an unobstructed binocular view of the

target. Subjects were instructed to “Throw, where you see the target” and had to perform

overhand throws while fixating the target without looking at their arm when throwing in order

to prevent on-line corrections of the planned movement. The spatial offset between the impact

of the ball and the target was clearly visible after each throw providing direct visual feedback

about the precision of the throw.

The wall was layered with Velcro material and the softball adhered to the wall after each

throw. In order to assess spatial accuracy of the throws, a photo was taken after each throw

using a digital camera which was kept at a fixed location during the experiments. A Matlab-

based computer program (Matlab release 12.1) was used to readout the electronic images

(.jpeg format) and to compute the horizontal distances between the position of the ball on the

wall and the target in a metric system by means of trigonometry with a spatial accuracy of ~ 1

cm (corresponding to ~ 0.3 deg. of visual angle at the throwing distance of 2 m).

Generalization of prism adaptation and the aftereffect from the pointing task to the throwing

task was tested in four transfer conditions: i) transfer of prism adaptation to ipsilateral arm

(pointing task: right arm, throwing task: adapted right arm), ii) transfer of aftereffect to

ipsilateral arm, iii) transfer of prism adaptation to contralateral arm (pointing task: right arm,

throwing task: unadapted left arm) and iv) transfer of aftereffect to contralateral arm. Note

that these denotations do not necessarily imply that any effects did actually transfer but

simply represent an unambiguous labeling of conditions.

Before each transfer condition, subjects adapted to the prismatic displacement in the pointing

task (adaptation procedure, see above); to test transfer of prism adaptation to the throwing

task, subjects had to throw balls while wearing prism goggles. Conversely, to test transfer of

the aftereffect, subjects adapted during the pointing task and removed the prism goggles

directly before the throwing task. Each transfer condition consisted of 30 trials and was

followed by the same number of throws without prism goggles in order to de-adapt subjects.

The order of transfer conditions was pseudo-randomized across subjects. To minimize spatial

reorientation which may decrease the magnitude of both effects, subjects kept the eyes closed

between conditions.

The “contralateral” conditions served as controls: after adaptation in the pointing task using

the right arm, the transfer to the untrained throwing task was tested with the unadapted left

arm. Neither a transfer of prism adaptation nor of the aftereffect to the throwing task was


expected due to the lack of intermanual transfer of prism adaptation under controlled

conditions (e.g. Baizer et al., 1999; Kitazawa et al., 1997; Martin et al., 1996b).

At the end of the experiment, separate measurements of right and left arm’s throwing

performance were conducted (standard conditions). For these measurements, subjects had to

perform 30 throws before (PRE), during (PRISM) and after (POST) wearing prisms goggles.

These recordings of conventional prism adaptation and aftereffect (without switching tasks)

served to compare the time course and magnitude of effects in the standard conditions with

the time course and magnitude of effects in the transfer conditions.

Experimental groups

For the Terminal Vision Experiment, eight healthy right-handed human subjects (3 male, 5

female) aged 22-26 years (mean 23.6 years) were recruited (Terminal Vision Group). Another

eight subjects (3 male, 5 female) aged 21-26 years (mean 23.6 years) participated in the Full

Vision Experiment (Full Vision Group). None of the subjects reported a history of

neurological or neuropsychological disorders and all had normal or corrected-to-normal visual

acuity; subjects were naïve to the exact purpose of the study.

The experiments were conducted in accordance with the “Declaration of Helsinki” and

subjects gave informed consent prior to participation. This type of experiments was approved

by the ethics committee of Bremen University.

Data analysis

The horizontal distance between the position of the ball on the wall and the target was

calculated for each individual throw. For further analysis, the data were baseline corrected;

that is, we subtracted the mean of all throws of the PRE condition from each data point of

each condition (see also Clower & Boussaoud, 2000). This was done for each condition with

regard to the corresponding arm and each subject individually. The mean of the PRE

condition mirrors a subject’s general arm-specific throwing performance and indicates a

potential spatial bias of the movements. In the Terminal Vision Experiment, this bias averaged

0.0 cm (± 0.5 SEM) for the right arm and -2.9 cm (± 0.7) for the left arm. A bias of -0.4 cm (±

0.4) in the right arm and -2.6 cm (± 0.6) in the left arm was recorded in the Full Vision

Experiment. The baseline correction normalized the data by removing any spatial bias which

could have masked the effects of prismatic displacement on the movements’ accuracy and

also allowed a better comparison between subjects and arms since each set of data was

normalized individually. Consequently, all data shown are baseline corrected.


In order to assess the magnitude of effects in the standard conditions and the transfer

conditions, we calculated the magnitude of the effects by fitting a linear regression line to the

first four data points of each condition and took the intersection of this regression line with

the ordinate as measure of the (initial) prism effect and aftereffect, respectively. This method

was applied to all data instead of using the result of the first movement because the regression

takes into account that i) prism-induced movement errors decrease over the first trials and do

not completely disappear after the first movement and ii) the decrease of movement errors

over the first few trials is mathematically best modeled by a linear function.

Results

The logic of both experiments was as follows: subjects were prism-adapted by executing

right-arm pointing movements, and immediately thereafter the transfer of prism adaptation or

the aftereffect to the throwing task was tested. In order to evaluate the amount of

generalization from one task to the other, we compared the size of the effects in the “transfer

conditions” with the size of the effects in the “standard conditions”, i.e. with conventional

prism adaptation and aftereffect while performing throwing movements without switching

between tasks.

Time course of effects in the standard conditions

Averaged data of both experimental groups for the right and left arm are presented in Fig. 6.2.

The lateral deviation (in cm) of the endpoints of the throwing movements from the target is

plotted as a function of trial number before (PRE), during (PRISM), and after (POST)

wearing prism goggles. Negative values represent a leftward deviation, positive a rightward

deviation.

Before wearing prism goggles (PRE condition), subjects’ throwing movements only exhibited

a very small lateral deviation in both arms suggesting accurate visuomotor performance. Note

that the variability of throws was somewhat higher in the left arm which is likely due to the

right-handedness of all subjects studied.

Right Arm To wear the prism goggles (PRISM condition) initially led to a marked lateral

deviation of throwing movements in the direction of the prismatic displacement. In the right

arm (Fig. 6.2a) of the Terminal Vision Group the prism effect (throw 1) amounted +41.4 cm

(± 6.2 SEM) and decreased to +10.0 cm (± 1.6) at the end of this condition (throw 30). Upon


removal of the prisms (POST condition), a negative aftereffect of -32.2 cm (± 4.8) occurred

(throw 1) decreasing to -2.1 cm (± 1.7) at throw 30. The reduction of lateral throwing errors

was statistically significant in both conditions (PRSIM: p < .01; POST: p < .001) as revealed

by a paired two-sided student’s t-test comparing throws 1 and 30. The movements’ lateral

deviation recorded in the right arm of the Full Vision Group at the beginning of the PRISM

condition averaged +41.0 cm (± 5.4) and was reduced to +8.6 cm (± 3.0) by throw 30.

Throwing without prisms (POST condition) produced an aftereffect of -24.3 cm (± 4.0) which

almost completely disappeared at the end of the condition (mean -0.7 cm, SEM ± 2.6). The

reduction of movement errors was statistically significant in both conditions (p < .01).

Fig. 6.2 Time course of effects in the standard conditions: Mean lateral deviation (in cm) of throwing movements from the target in the PRE, PRISM and POST condition in the Terminal Vision Group (n = 8; filled diamonds) and the Full Vision Group (n = 8; open circles) for the (A) right arm and the (B) left arm. Negative values indicate a leftward deviation, positive a rightward. All data are baseline corrected (means and SEM).

Left Arm In the left arm (Fig. 6.2b), the Terminal Vision Group showed an initial prism

effect of +31.9 cm (± 4.7) which was reduced to +2.8 cm (± 3.4) at the end of the PRISM

condition. In the first throw of the POST condition, the aftereffect averaged -36.5 cm (± 5.8)

and declined to -0.6 cm (± 3.7) at throw 30. As for the right arm, the gradual reduction of


movement errors was statistically significant in both conditions (PRISM: p < .001; POST: p <

.01). In the left arm of the Full Vision Group, the prism effect reached +41.5 cm (± 3.2),

declining to +10.3 cm (± 4.6) at the end of the PRISM condition. Upon removal of the prism

goggles (POST), an aftereffect of -34.5 cm (± 5.5) occurred which was reduced to -0.4 cm (±

3.7). Again, error reduction within the conditions was statistically significant (p < .01).

Taken together, it is clear that introducing the prisms led to a marked lateral deviation of

throwing movements in the direction of the prismatic displacement (i.e. rightward) but the

movements recovered high spatial accuracy within the PRISM condition, hence subjects

showed prism adaptation. Removal of the prisms evoked a leftward aftereffect, vanishing over

the course of visuomotor practice. These results are in good agreement with the literature.

Time course of effects in the transfer conditions

After prism adaptation in the pointing task using the right arm, subjects kept on wearing the

prism goggles but had to execute throwing movements with the ipsilateral (adapted, right)

arm and the transfer of prism adaptation was tested (Fig. 6.3a, upper panel).

In the Terminal Vision Group, the initial throw after switching between tasks showed a

marked rightward deviation of +35.9 cm (± 6.8) indicating a “second” prism effect; with

practice, the lateral deviation of throws declined to +9.4 cm (± 3.2) at the end of the condition

(throw 30). The Full Vision Group showed the same pattern of results; here, the initial

deviation of +50.1 cm (± 5.2) was reduced to +14.8 cm (± 3.4). In both groups, subjects

passed a “second” adaptation process (resembling conventional prism adaptation, see standard

condition) and the error reduction with practice was statistically significant (Terminal Vision

Group: p < .05; Full Vision Group: p < .001).

To test the transfer of the aftereffect from the pointing to the throwing task in the ipsilateral

(right, adapted) arm, prism goggles were removed after adaptation (Fig. 6.3a, lower panel). In

the Terminal Vision Group, the first throw deviated slightly leftwards by -5.9 cm (± 2.8) and

the subsequent throws were close to the target. In the other group tested, the first throw

deviated by -12.0 cm (± 5.7) and all other throws were close to zero. Although there was no

apparent aftereffect and the throwing movements were quite accurate throughout the

condition, the results of the first and the last throw were statistically different (both groups: p

< .05). Nevertheless, there was no explicit transfer of the aftereffect from pointing to throwing

in the right (ipsilateral) arm which is in line with the finding that prism adaptation did not

transfer to the throwing task at all.


Fig. 6.3 Time course of effects in the transfer conditions: Mean lateral deviation (in cm) of throwing movements as a function of trial number for the Terminal Vision Group (n = 8; filled diamonds) and the Full Vision Group (n = 8; open circles) after prism adaptation in the pointing task. A) Transfer of prism adaptation (upper panel) and aftereffect (lower panel) to the throwing task in the ipsilateral adapted (right) arm. B) In the contralateral conditions, the transfer of prism adaptation and aftereffect to the throwing task was tested in the contralateral unadapted (left) arm.

In the transfer conditions conducted with the contralateral arm, subjects likewise adapted with

their right arm in the pointing task but the transfer of prism adaptation and aftereffect to the

throwing task was then tested in their unadapted (left) arm. When both task and arm tested

were switched after adaptation and subjects kept on wearing the prism goggles, a “second”

adaptation process was observed in both groups (Fig. 6.3b, upper panel). In the Terminal

Vision Group, the initial prism-induced lateral deviation in the contralateral arm reached

+36.0 cm (± 3.3) and declined to +9.6 cm (± 2.5) at the end of the condition. The Full Vision

Group exhibited a prism effect of +50.9 cm (± 3.2) which was reduced to +5.9 cm (± 4.5).

Error reduction of left arm throwing movements during prism exposure was statistically

highly significant in both groups (p < .001).


The aftereffect did not transfer from pointing to throwing in the contralateral arm (Fig. 6.3b,

lower panel), but the first throw deviated by -23.7 cm (± 5.8) in the Terminal Vision Group.

All subsequent throws within this condition were close to zero (throw 30: mean +2.1, SEM ±

2.9). A paired two-sided t-test comparing the first and the last throw of this condition revealed

a significant difference (p < .01). In the Full Vision Group, no transfer of the aftereffect

across task and arm occurred: all throws showed a small lateral deviation (throw 1: mean -0.9

cm, SEM ± 4.9). A direct comparison of throw 1 and throw 30 did not show any significant

difference (p > .05).

Direct comparison between standard conditions and transfer conditions within groups

In a next step, we directly compared the magnitude of the effects in the transfer conditions

with the magnitude of the effects assessed in the standard conditions in the corresponding

arm. Remember that these effects were assessed on the basis of a linear regression line

through the first four data points (see methods).

In the Terminal Vision Group, the prism effect in the standard condition (standard prism

effect) reached +40.1 cm (± 5.6) when throws were executed with the right arm (Fig. 6.4a,

upper panel); when the tasks were switched and subjects threw the ball with the right arm

while wearing prism goggles (transfer condition, ipsilateral arm), another prism effect of

+35.6 cm (± 7.3) occurred. That is, switching the task led to another prism effect although

subjects had already adapted to the optical displacement by executing pointing movements.

The difference between the standard and the transfer prism effect was statistically not

significant (p > .05) as tested by a paired two-sided t-test. The same pattern of results applies

for the Full Vision Group: the right arm’s standard prism effect of +38.4 cm (± 5.0) and the

slightly higher transfer prism effect of +47.0 cm (± 5.2) in the ipsilateral arm did not differ

significantly. These results indicate that switching to the throwing task evoked a prism effect

similar to the conventional prism effect, hence prism adaptation in both groups did not

transfer to the novel task.

In the Terminal Vision Group, right arm throwing after removal of the prisms produced a

standard aftereffect of -32.0 cm (± 4.6) (Fig. 6.4a, lower panel). When the prisms were

removed and the task was switched after adaptation (transfer condition), throwing movements

in the ipsilateral (right) arm did not deviate distinctly and a transfer aftereffect of -7.2 cm (±

3.3) was recorded. In the Full Vision Group, the standard right arm aftereffect averaged -23.9

cm (± 3.0) and the transfer aftereffect in the ipsilateral arm reached -8.0 cm (± 3.7). Whereas

proper right arm aftereffects occurred in the standard conditions in both groups, almost no


aftereffect occurred in the right arm after switching between tasks, hence the aftereffect did

not transfer to the untrained task in the same arm. The differences between standard and

transfer aftereffects were statistically significant (Terminal Vision Group: p < .01; Full Vision

Group: p < .05).

Fig. 6.4 Comparison between standard and transfer conditions within each experimental group (upper panel: standard/transfer prism effect; lower panel: standard/transfer aftereffect). A) Magnitude of the standard effects (black bars) in the right arm and transfer effects (white bars) in the ipsilateral arm of the Terminal Vision Group and the Full Vision Group. B) Magnitude of the standard effects in the left arm and transfer effects in the contralateral arm of both experimental groups. Significant differences between conditions as revealed by a paired t-test are indicated by asterisks. Means and SEM of 8 subjects per group.

As a control, both task and arm tested were switched after adaptation (transfer conditions,

contralateral arm). In the standard condition, the left arm’s prism effect reached +34.0 cm (±

5.2) in the Terminal Vision Group (Fig. 6.4b, upper panel). When the task was switched and

subjects had to throw with the contralateral (unadapted, left) arm while wearing prism

goggles, a transfer prism effect of +35.0 cm (± 3.1) emerged; the two conditions did not differ

significantly (p > .05). In the other group studied, the contralateral transfer prism effect of


+47.3 cm (± 3.8) was higher than the left arm’s prism effect as measured in the standard

condition (mean +39.7 cm, SEM ± 2.3) but this difference did not reach statistical

significance (p > .05). In both groups, switching task and arm tested evoked a “second” prism

effect in almost the same manner as in the standard condition, hence the adaptation did not

generalize across tasks and arms and subjects had to undergo another adaptation process.

The standard aftereffect in the left arm of the Terminal Vision Group (Fig. 6.4b, lower panel)

reached -36.3 cm (± 4.4); after removal of the prisms and switching both task and arm tested,

contralateral throwing movements initially showed a leftward deviation of -18.3 cm (± 3.7)

which is about 50 % of the left arm’s standard aftereffect. Yet, the difference between the two

conditions was statistically significant (p < .01), indicating no more than a partial transfer of

the aftereffect across tasks and arms. In the Full Vision Group, the left arm’s standard

aftereffect was -31.6 cm (± 3.8). When both task and arm tested were switched (transfer

aftereffect, contralateral arm), throwing movements showed hardly any deviation from the

target (mean -0.6 cm, SEM ± 4.6). The difference between these conditions was statistically

highly significant (p < .001). To sum up, neither prism adaptation nor the aftereffect

transferred to the untrained task in the unadapted arm.

Comparison between Terminal Vision Group and Full Vision Group

A direct comparison of the standard effects and transfer effects between experimental groups

is presented in Fig. 6.5. The standard effects for both groups were comparable: an unpaired

two-sided student’s t-test did not reveal any significant differences – neither for the prism

effect nor for the aftereffect in the right or left arm (p > .05). The same applies for the transfer

effects in the ipsilateral arm: the magnitude of the prism effect after switching tasks did not

differ significantly between both groups (p > .05). In line with these results, the transfer

aftereffects were equally small in both groups, hence there was no difference in the amount of

transfer between the groups studied. Prism adaptation and the aftereffect simply did not

transfer across tasks in the ipsilateral arm.

However, when comparing the magnitude of the transferred prism effect in the contralateral

arm, a significant difference between groups appeared (p < .05). Whereas the transferred

prism effect amounted to +35.0 cm (± 3.1) in the Terminal Vision Group, the Full Vision

Group exhibited a significantly higher effect of +47.3 cm (± 3.8). In the Terminal Vision

Group, the transferred aftereffect in the contralateral arm reached +18.3 cm (± 3.7) whereas

the same condition yielded a marginal effect of -0.6 cm (± 4.6) in the Full Vision Group. The

difference between groups was statistically significant (p < .01).


Fig. 6.5 Direct between-group comparison of the (A) standard effects and the (B) transfer effects. Black bars represent the Terminal Vision Group and white bars stand for the Full Vision Group. Significant differences between groups as revealed by an unpaired t-test are indicated by asterisks. Means and SEM of 8 subjects per group.

Discussion

Adaptation to a lateral displacement of the visual world induced by prisms requires the

execution of a particular task in order to trigger the experience-dependent remapping of

visuomotor representations. In the present study, we examined whether a prism-induced

visuomotor remapping acquired in one task is transferred to another task. Subjects adapted in

a pointing task and the transfer effects of both prism adaptation and the aftereffect to an

untrained throwing task were tested. Our results show a strong task-specificity of the

adaptation process since neither prism adaptation nor the aftereffect transferred across tasks.

Furthermore, the type of visual feedback provided during adaptation in the pointing task had

no differential impact on the pronounced task-specificity. The experiment with visual

feedback on the movement’s precision at the terminal part of the movement (Exp. 1) as well

as the experiment with full visibility of the trajectory during adaptation (Exp. 2) lacked

generalization of prism adaptation from the trained to the untrained task.

Specifying visual feedback conditions

In our study, the availability of visual and proprioceptive feedback (i.e. sensory information

from receptors in the muscles, and joints) during movement execution varied according to

experiments: in the Terminal Vision Experiment, proprioceptive information about the moving

limb was available during the entire movement whereas visual information was available only


at the terminal part of the movement (terminal exposure). Hence, both visual and

proprioceptive feedback information coincided only at the end of the movement representing

the most important difference to the Full Vision Experiment where both sensory modalities

were concurrently available during the entire movement (concurrent exposure).

It has been suggested (e.g. Redding & Wallace, 1988; Uhlarik & Canon, 1971) that the extent

of adaptive remapping of each modality during the adaptation process depends on the specific

prism-exposure conditions: under terminal exposure, spatial localization of the arm relies

more on proprioception of the arm since visual information is only available at end of the

movement; hence, visual coordinates are remapped (“adapted”) whereas proprioceptive

coordinates remain unchanged. Conversely, during concurrent exposure vision forms the

dominant sensory input and proprioceptive coordinates are remapped in the course of

adaptation (of course, in the end, also the visual “spatial” information relies partly on

proprioception of the eye position).

This view has important implications for the generalization of prism adaptation from one task

to another as examined in our study. An adaptive remapping of the visual system taking place

under terminal exposure would predict a transfer of prism adaptation across tasks since the

remapping of visual coordinates would – once completed – affect motor planning irrespective

of the task. On the contrary, adaptation of the proprioceptive system of the arms (especially

with concurrent exposure) would be arm- and task-specific since only the current task-specific

configuration of the moving limb is adapted. Whereas the model described above predicts

lack of generalization to the untrained task only under concurrent exposure, our results show

task-specific prism adaptation irrespective of the type of visual feedback. What may be the

reason for this deviation from the model’s predictions?

Task-specificity and direction-dependent weighting of sensory inputs

For the planning and control of goal-directed limb movements, both visual and proprioceptive

input signals about arm position are combined and weighted to generate an estimate of limb

localization in space (Bays & Wolpert, 2007). However, in the horizontal plane the precision

of visual and proprioceptive localization varies with the direction being considered: whereas

proprioception provides more precise spatial information in depth (i.e. in a radial direction

from the observer) than in azimuth (i.e. in a direction orthogonal to that), the opposite applies

for vision which is more precise in azimuth than in depth (van Beers et al., 2002) and this is

supposed to result in a direction-dependent weighting of sensory inputs for optimal

integration (Bays & Wolpert, 2007).


It has been shown experimentally that spatial localization in depth relies more on

proprioception whereas spatial judgments in azimuth are computed on the basis of visual

information. Thus, for judgments involving the azimuth vision is weighted stronger than

proprioception leading to adaptation of arm-muscle proprioception (van Beers et al., 2002).

According to this model, the direction of an experimental manipulation is the essential factor

for the type of adaptation. In the case of laterally displacing prisms, a conflict of visual and

proprioceptive sensory inputs is introduced in azimuth which causes adaptation of the

modality with the lower spatial resolution in that direction, i.e. proprioception. This type of

adaptation, affecting the felt arm position is specific for the current configuration of the

moving limb, in other words, it is task- and trajectory-dependent. Since the type of arm

trajectory during a pointing movement clearly differs from a throwing movement,

proprioceptive adaptation of the pointing trajectory does not transfer to a throwing trajectory.

A simple way of explaining the pronounced task-specificity irrespective of the type of visual

feedback observed in our study is to attribute a large portion of the adaptation process to a

remapping of the proprioceptive system as a consequence of the flexible direction-dependent

weighting of visual and proprioceptive input signals. This would imply that it is not the type

of exposure condition (concurrent vs. terminal) which determines the type of adaptation

(proprioceptive vs. visual) but instead the direction of the visual-proprioceptive conflict

(azimuth vs. depth) is the crucial factor for the type of adaptation.

Task- and trajectory-specific prism adaptation

In a related study, Marotta et al. (2005) reported task-specific prism adaptation to a left-right

reversal of the visual field; this severe artificial manipulation of the relationship between

visual input and motor output is apparently compensated for on the basis of task-specific

transformations. In our study, however, even a moderate lateral shift of the visual world by 17

deg. resulted in a task-specific adaptation process agreeing well with previous studies

addressing the specificity of prism adaptation. In particular, Martin et al. (1996b) reported that

prism adaptation did not transfer from overhand throws to underhand throws in the same arm.

In their study, subjects executed overhand throws during prism adaptation. After removal of

the prisms, they executed underhand throws and no aftereffect occurred. However, the authors

attribute this task-specificity mainly to motor adaptation and an adaptive change in the

relationship between the direction of gaze and the direction of throw. Other studies as well

have shown that adaptation is very specific for the critical task-related motor parameters like


arm posture (Baraduc & Wolpert, 2002), velocity of arm movements (Kitazawa et al., 1997),

or the weight of the limb moving (Fernandez-Ruiz et al., 2000).

In this context, it is important to keep in mind that switching from a trained to an untrained

task always involves a complex alteration of motor parameters, hence task-specific adaptation

can also be interpreted as a trajectory-specific adaptation; switching the task is closely related

to an alteration of movement parameters, hence a novel trajectory has to be planned.

Therefore, it is indisputable that the adaptation process must involve a strong motor

component as suggested by the studies mentioned (e.g. Baraduc & Wolpert, 2002; Martin et

al., 1996b). It is very likely that the sensorimotor system employs both proprioceptive and

motor adaptation mechanisms in order to rapidly restore a correspondence between sensory

and motor coordinate systems. The amount of adaptation within the sensory (i.e. visual, and

proprioceptive) and motor system may vary according to the exact spatial and temporal

requirements of a given task.

Further aspects: speed of adaptation and lack of intermanual transfer

Subjects adapting to the prism-induced displacement of the visual world by executing

pointing movements could not rely on their acquired visuomotor remapping when they had to

perform throwing movements. In the untrained task, subjects had to adapt anew when wearing

prisms and passed a second adaptation process although they had already adapted to the

prisms immediately before. The time course and speed of the second adaptation process after

switching between tasks was very similar to the conventional adaptation process (see Fig. 6.2

and Fig. 6.3) suggesting that the visuomotor remapping formed during pointing adaptation

could not be retrieved for the throwing task – it was functionally not accessible for the

untrained task. This conclusion is derived from the experimental finding that no aftereffect

occurred when the prisms were removed and the tasks were switched.

Moreover, we fitted an exponential decay function of the form

312)( aeaxf xa +=

to the individual data of both the standard and transfer prism conditions in order to assess the

speed of the adaptation process which is reflected by the parameter a2. A paired two-sided t-

test did not reveal significant differences between conditions suggesting that the visuomotor

remapping acquired during pointing did not even facilitate (i.e. speed up) the adaptation

process after switching between tasks. Rather, the speed of adaptation was the same as that of

the conventional adaptation process. This holds true for both experimental groups and

underlines the pronounced task-specificity irrespective of the type of visual feedback.


After switching both task and arm tested (contralateral conditions), subjects showed a second

adaptation process when they kept on wearing the prisms which was expected since most

studies find that the adaptation process is restricted to the exposed arm (e.g. Baizer et al.,

1999; Baraduc & Wolpert, 2002; Kitazawa et al., 1997; Martin et al., 1996b). In both

experimental groups, the initial prism effect after switching both task and arm tested was as

large as the conventional left arm prism effect and subjects reduced the movements’ lateral

errors gradually with comparable speed. Due to the lack of intermanual transfer and the strong

task-specificity of prism adaptation it is not surprising that there was no transfer when both

variables were changed (i.e. task and arm tested). Again, these results highlight the strong

specificity of the acquired visuomotor remapping and confirm that neural adjustments

underlying the adaptation process do not occur within the visual system since this would yield

a transfer across both task and arm.

In this context, we do not want to keep secret odd results observed in five of eight subjects of

the Terminal Vision Group: after adaptation in the pointing task using the right arm, these

subjects exhibited an aftereffect in the throwing task in the unadapted arm (see Fig. 6.3b,

lower panel, first black diamond). It was, however, only the first throw which deviated

laterally whereas the other throws were close to the target. These results would imply that the

aftereffect transferred across both task and arm but not across tasks using the same arm! Since

this can hardly be the case we infer that this effect may rather reflect cognitive strategies

employed by some of our subjects, and indeed, one should never forget that in these types of

adaptation experiments cognitive strategies can, in principle, interact with the automatic and

pre-conscious adaptation mechanisms that constantly update the relationship between

sensorimotor representations of the physical world.

Conclusions

The central goal of this study was to assess whether prism adaptation during pointing

movements transfers to untrained throwing movements. By systematically varying the

exposure conditions during adaptation (terminal vs. concurrent visual feedback) we wanted to

investigate whether specific types of exposure conditions would lead to higher or lower

amounts of generalization across tasks. Our results strongly suggest task-specific prism

adaptation irrespective of the type of visual feedback during exposure. The specificity of the

adaptation process can hardly be explained in terms of an adaptive remapping of visual

coordinates in the course of practice. Rather, we propose that the task-specificity can be


explained as a result of an adaptive proprioceptive remapping. Since the prism-induced

manipulation occurs in azimuth where vision has a higher spatial resolution, visual inputs are

weighted more heavily and proprioceptive inputs are adapted in a task-dependent way in order

to rapidly restore accurate eye-hand coordination. However, it is clear that adaptive changes

may also occur within the motor system; both sensory and motor adaptation mechanisms

might operate in a dynamic and mutual manner. From a biological perspective, “local” task-

specific adaptation seems to be the optimal (and more saving) strategy for the brain to adjust

neural representations in response to short-term changes of the physical world or the own

body.

Acknowledgments

Parts of this study were presented on a poster at the workshop on “Preemptive Perception” at

the Hanse Institute for Advanced Study, Delmenhorst/Germany, October 2005. The authors

would like to thank D.C. Högl for assistance in collecting the data and D. Trenner for the

programming work. The authors declare that they have no competing financial interests.

Supported by grant 01GQ0705 (Bernstein programme) of the German Federal Ministry of

Education and Research (BMBF).

Studie 3: Räumliche Generalisierung des Nacheffekts 71

7. Studie 3 Effects of training conditions on spatial generalization of prism

adaptation


Abstract

Prism adaptation is often very specific to the exact experimental context of the particular

visuomotor task. Here, we investigated whether the type of visuomotor training (i.e. blocked

vs. mixed) during prism adaptation affects the pattern of spatial generalization. In Experiment

1, subjects adapted to a lateral shift of the visual world by executing pointing movements to a

single target in rapid succession (blocked training) and generalization of the aftereffect to an

untrained target was tested. Aftereffects mostly transferred to other target positions indicating

pronounced generalization across space. In Experiment 2, subjects adapted by pointing

alternately to two target locations, a form of mixed training. Generalization of aftereffects to

targets located beyond the adapted visuomotor workspace depended upon the direction tested;

pointing to a target within the adapted workspace yielded smaller aftereffects. Results are

discussed in terms of a scaled spatial representation as a consequence of prism adaptation

through mixed training.

Introduction

Neural representations of the physical world are continuously shaped through experience to

assure adequate behavior in a dynamic environment. Updating the brain’s spatial

representations in response to altered external conditions requires neural plasticity of the

structures involved (Steven & Blakemore, 2004). Perceptual learning (e.g. Ahissar &

Hochstein, 2004; Fahle, 2002; 2004) and visuomotor adaptation demonstrate the preservation

of human brain plasticity during adulthood even on rather elementary levels of processing.

Here, we tested whether the form of visuomotor training during prism adaptation would

influence the pattern of spatial generalization of the adaptive behavior.

Prism adaptation demonstrates visuomotor plasticity

Prism adaptation is a form of visuomotor adaptation in which subjects adapt to a prism-

induced perturbation of the visual world – usually a lateral shift – while executing goal-


directed visually guided movements to a specific target (for reviews see e.g. Bedford, 1999;

Harris, 1965; Redding et al., 2005). The (wedge) prisms in front of the subjects’ eyes

introduce deviations between the perceived direction of the target and the position of the arm

(Martin et al., 1996b; 2002). As a result, movements initially deviate markedly from the target

in the direction of the prism-induced optical shift (prism effect). Typically, visual feedback

regarding the arm movement is provided signaling the difference between the actual and the

desired endpoint of the movement. The resultant error signal serves to adjust the movements

on a trial by trial basis (“error reduction phase”) leading to increasingly accurate arm

movements under prism exposure. As a result, movements recover high spatial accuracy in

the course of the adaptation process (Redding et al., 2005).

When the prisms are removed subsequent to adaptation, movements initially deviate laterally

in the direction opposite to the prismatic shift. This negative aftereffect decreases rapidly

during the course of continuing practice with feedback (e.g. Fernandez-Ruiz & Diaz, 1999;

Fernandez-Ruiz et al., 2000; 2004; Redding et al., 2005). Functionally, the aftereffect

demonstrates the adaptive re-mapping of sensory (i.e. visual and proprioceptive) and motor

coordinates in the course of prism adaptation suggesting short-term plasticity of the

underlying neural structures. The course of de-adaptation following removal of the prisms is

somewhat faster than the prism adaptation process because the visuomotor system recovers

rapid access to the stored original representation for eye-hand coordination (Fernandez-Ruiz

& Diaz, 1999). Furthermore, the aftereffect suggests that the adaptation process is not

primarily of cognitive origin because if it were, removal of the prisms should almost

immediately lead to unbiased pre-exposure like visuomotor behavior.

Neuroanatomical findings

Mirroring the complexity of prism adaptation, a variety of brain areas – cortical as well as

subcortical – have been identified as contributing to the adaptation process. Consistent with

the view that the cerebellum is an important neural substrate for motor skills (e.g. Hikosaka et

al., 2002; Thach et al., 1992), several studies conducted with humans (Martin et al., 1996a;

2002; Morton & Bastian, 2004; Pisella et al., 2005; Weiner et al., 1983) and non-human

primates (Baizer et al., 1999; Kitazawa & Yin, 2002) indicate that cerebellar structures are

involved in the adaptation process. In addition, contributions of frontal motor areas like

ventral premotor cortex (Kurata & Hoshi, 1999) and “classical” motor structures like the basal

ganglia (Fernandez-Ruiz et al., 2003) have been demonstrated experimentally.


In addition, strong evidence indicates that parietal cortical areas also contribute to prism

adaptation (Clower et al., 1996; Newport et al., 2006; Newport & Jackson, 2006) compatible

with the role of parietal cortex in sensorimotor integration (Andersen & Buneo, 2003; Buneo

& Andersen, 2006). A number of studies even report ameliorating effects of prism adaptation

on hemispatial neglect, a neuropsychological disorder following unilateral damage of parietal

cortex (e.g. Luaute et al., 2006; Redding & Wallace, 2006b; Rode et al., 2003; Rossetti et al.,

1998; Serino et al., 2006). Obviously, spatial representations in the parietal lobe undergo

plastic changes during prism adaptation. Moreover, left-right reversing prisms strongly

manipulating visuomotor coordination change representations in early visual areas suggesting

that neural plastic processes may occur even in early sensory (e.g. visual) cortices (Miyauchi

et al., 2004; Sugita, 1996; Tanaka et al., 2007). To sum up, prism adaptation seems to be

achieved by an extended network of motor, sensorimotor, and sensory brain areas

contributing to sensorimotor plasticity to different extents depending on the requirements of a

given visuomotor task.

Psychophysical findings: Specificity versus generalization

The prism adaptation paradigm is well suited to study the short-term brain mechanisms

adjusting sensorimotor representations according to specific task demands. An important issue

concerns the specificity of the adaptation process: Is the acquired visuomotor mapping

specific to the precise training conditions as is usually the case in perceptual learning (cf.

Fahle, 2005) or does it generalize to untrained conditions? This pattern of generalization can

provide important information about the underlying processing system (Poggio & Bizzi,

2004).

Several studies on prism adaptation highlight a specific adaptation process where the amount

of generalization critically depends on the similarity between training (adaptation) and testing

conditions. For example, prism adaptation during overhand throwing movements did not

generalize when underhand throws were subsequently tested (Martin et al., 1996b). Similarly,

adaptation was found to be specific for movement velocity during prism exposure.

Generalization decreased as the difference in velocities between trained and tested movement

increased (Kitazawa et al., 1997). Furthermore, Fernandez-Ruiz et al. (2000) showed that

prism adaptation only generalized when limb weight was identical for training and testing

conditions. In an experiment using a virtual-reality setup closely related to the “classical”

prism adaptation paradigm, Baraduc & Wolpert (2002) demonstrated the specificity of the

adaptation process for starting limb posture. As the tested posture increasingly differed from


the initially trained posture generalization decreased constituting a generalization gradient. In

these examples the adaptation mechanism precisely incorporated the specific task-related

parameters during prism exposure. The more the conditions differed between training and

testing, the less did the system employ the “adaptive strategy” for the novel conditions.

Besides this type of local adaptation yielding an associative generalization gradient along a

given dimension, experimental evidence exists for a more global type of adaptation. For

example, Bedford (1989; 1993) and Redding & Wallace (2006a) both demonstrated by means

of a simple pointing task that adaptation generalized to untrained target locations in space

suggesting a rigid shift in the mapping of all points in the spatial maps involved in the task, a

form of linear generalization. That is, adaptation to a specific target transferred to other

targets in space although these had not been trained. Similarly, a study in which subjects were

adapted to hemiprisms (i.e. prisms covering only the upper or lower visual hemifield) found

that the system initially modified visuomotor transformations globally in the whole spatial

representation, i.e. it performed a rigid linear shift; yet, with differential feedback the system

was also able to locally adjust the visuomotor map (Fernandez-Ruiz et al., 2006). These two

processes (global vs. local adjustment) seem to operate on different time scales

Experimental questions

The present psychophysical study on prism adaptation was motivated by the question whether

or not the pattern of spatial generalization in a visually guided pointing task is influenced by

the type of visuomotor training. Since the aftereffect is less affected by cognitive strategies, it

was taken as the critical measure and spatial generalization was tested at one of three possible

target locations.

In the first experiment, subjects adapted to the prism-induced lateral shift by pointing thirty

times to a visual target in space. Thereafter the prisms were removed and the generalization of

the aftereffect to an untrained target was tested. During adaptation, subjects pointed

sequentially to a single visual target in rapid succession, a form of “blocked training”. In case

of local adaptation an associative generalization gradient (cf. Bedford, 1993; Redding &

Wallace, 2006a) is expected to emerge, decreasing with spatial distance between targets

trained and tested. In contrast, extensive generalization across targets in space would indicate

a rigid linear shift of the entire visuomotor map as the underlying cause of this adaptation

process.

The second experiment investigated whether a “mixed training” procedure during prism

adaptation would give rise to a different pattern of spatial generalization. To test this question,


subjects pointed alternately to two targets in space during prism adaptation, a form of mixed

training. After adaptation, generalization of the aftereffect to the untrained target was

measured. Due to the mixed training, different parts of the visuomotor workspace were

adapted since the pointing movements to two separate targets covered a relatively wide range

of directions. This type of experimental design made it therefore possible to differentiate

between conditions in which generalization was tested in a target located beyond (i.e.

extrapolation) versus within (i.e. interpolation) the adapted workspace. In this respect, we

asked whether a specific type of workspace adaptation would lead to different amounts of

generalization.

Methods

Task, setup, and procedure

The visuomotor task required subjects to perform accurate visually-guided pointing

movements towards a distant target using the right arm. Subjects were sitting at a table and

executed ballistic movements to one of three targets located at the table’s edge at a viewing

distance of 65 cm. The three targets (left, central, and right) were spatially separated by a

distance of 25 cm from each other (Fig. 7.1a). To ensure that subjects could reach each of the

three targets equally well, the distal part of the right shoulder faced the central target.

Subjects were instructed to point as accurately as possible to the perceived target location.

They could not visually track their movement after its start due to a nontransparent table-top.

Consequently, the trajectories were largely planned feed-forward on the basis of the perceived

target position relative to the body. At the end of the movement, however, subjects saw the tip

of their index finger and so received terminal visual feedback about the precision of the

movement. This type of feedback condition has been termed “terminal exposure” (cf. Redding

et al., 2005). The movements’ spatial accuracy was assessed using a PC-controlled measuring

system (Zebris Medical, Isny/Germany) based on the travelling time of ultrasound pulses

which were emitted by three senders and picked up by microphones attached to the index

finger and the targets. A computer program calculated the distance between the finger and the

target in all three spatial directions. The spatial resolution of the measuring system was < 1

mm. The high quality wedge prisms (Carl Zeiss, Oberkochen/Germany) used were mounted

into conventional spectacle frames and produced a perceived lateral shift of the visual world

by ~ 17 deg. to the left (i.e. base-right prisms; 30 diopters); subjects always viewed the target

binocularly.


Fig. 7.1 A) Experimental setup: Subjects were sitting at a table and had to perform pointing movements to one of three targets at the table’s edge. Terminal visual feedback about the precision of the executed movement was provided. The spatial accuracy of the movements was assessed using a PC-controlled ultrasound measuring device. Conditions tested in (B) Experiment 1 and (C) Experiment 2; L = left target, C = central target, R = right target; for details see text.

Experiment 1 In Experiment 1, spatial generalization of the aftereffect from a trained

target (prism adaptation) to an untrained target was examined. Each experimental block (Fig.

7.1b) consisted of two conditions with 30 pointing movements each. At first, subjects adapted

to the prism-induced optical displacement by executing pointing movements to one of the

three targets (“target trained”) in rapid succession. After adaptation, the prism goggles were

removed and generalization of the aftereffect to another target was tested (“target tested”).

This experiment covered a “blocked training” procedure: During prism adaptation, subjects

pointed to a single target in space and the transfer of the aftereffect was assessed for another

single target location.

The generalization of the aftereffect was probed systematically for each target (including

trained = tested target) leading to a total of 9 (3x3) discrete experimental blocks ([trained: left,

central, right] x [tested: left, central, right]). Each block started with an adaptation procedure

and in the following condition, spatial generalization of the aftereffect was tested. In order to

minimize effects of habituation, subjects had to keep their eyes closed between conditions.

Order effects were minimized by counter-balancing the order of blocks tested across subjects.

At the beginning of the experiment, spatial accuracy of the movements without prism goggles

(PRE, baseline condition) was recorded for each target individually. This served to control for

possible effects of target position on the movements’ accuracy and to correct the data for

directional biases (baseline correction; see Data analysis).


Experiment 2 Similar to Experiment 1, spatial generalization of the aftereffect to an

untrained visual target was tested in Experiment 2. However, the basic difference to the first

experiment was that during prism adaptation subjects had to point alternately to two targets

(i.e. mixed training during prism exposure). Each experimental block consisted of two

conditions (Fig. 7.1c); in the first condition, subjects pointed alternately to two targets (30

movements per target trained) while wearing prism goggles. In the following condition (30

pointing movements), the prism goggles were removed and generalization of the aftereffect to

the untrained target was measured (“target tested”).

The spatial configuration of the three targets allowed both an extrapolation task and an

interpolation task. In the extrapolation task, the left (resp. right) and the central target were

trained during adaptation and generalization of the aftereffect to the right (resp. left) target

was tested. This probes the extrapolation of the aftereffect to a visual target located beyond

the adapted visuomotor workspace. Testing extrapolation to the left versus the right target

allowed to compare the effects of an extrapolation in the direction of the aftereffect (i.e.

extrapolation to right target) and in the direction opposite to the aftereffect (i.e. extrapolation

to left target).

The extrapolation task was the counterpart of the interpolation task. In this case, the left and

the right targets were trained alternately during prism adaptation, and generalization of the

aftereffect to the central target was examined. This test of generalization formed an

interpolation task since the central target was located within the adapted visuomotor

workspace. Interpolation of the aftereffect to the central target was tested twice. In one block,

adaptation started with pointing to the left target while in the other block adaptation started

with the right target. To sum up, generalization of the aftereffect to an untrained target was

tested in two extrapolation (left and right target) and two interpolation (2x central target)

blocks. The order of these four blocks was counter-balanced across subjects.

The movements’ spatial accuracy was recorded for each target before (PRE), during

(PRISM), and after (POST) wearing prism goggles. In each condition, 30 pointing movements

had to be performed. These measurements were carried out i) to reveal potential target-related

spatial biases, ii) to trace the temporal courses of prism adaptation (PRISM) and de-adaptation

(POST), and iii) to evaluate the size of the standard aftereffect in each target. In the analysis,

we compared the size of the standard aftereffect with the size of the extrapolation and

interpolation aftereffects for the corresponding target.


Data analysis

For each individual trial, the horizontal distance between the endpoint of the movement and

the target was assessed (in mm) and analyzed as a function of trial number. For further

analysis, a baseline correction was performed. That means, we subtracted the average lateral

deviation of pointing movements of the baseline condition (PRE, no prisms) of a specific

target from each data point of the corresponding target. This normalization procedure,

inspired by Clower & Boussaoud (2000), was performed on each subject’s data individually.

Why is normalization desirable? The mean of the baseline condition reflects a subject’s

general visuomotor performance with regard to a specific target and reveals a potential target-

related directional bias. Removing this target-related bias leads to a normalized set of data and

therefore allows a better comparison of effect sizes between targets and subjects.

Furthermore, baseline correction removes effects which are due to finger-target geometry (i.e.

an inherent rightward deviation of movements when pointing to the right target). In

Experiment 1, the spatial bias averaged -7.4 mm (± 0.7 SEM) in the left target, +16.1 mm (±

0.9) in the central target and +29.4 mm (± 1.0) in the right target. Spatial biases of -4.6 mm (±

0.8) in the left target, +11.0 mm (± 0.6) in the central target and +28.4 mm (± 0.7) in the right

target were recorded in Experiment 2.

To assess the size of aftereffects, a linear regression line was fitted to the first four data points

of each condition and the intersection of the regression line with the y-axis was taken as a

measure of the aftereffect. Why not simply taking the result of the first movement?

Aftereffects do not completely vanish after the first movement but decrease stepwise over the

first few trials. Our method incorporates this early and rapid decrement of lateral errors, and

reduces noise in the data by using four data points rather than a single one. Moreover, the

slope of the regression line indicates the speed of de-adaptation (aftereffect).

Subjects

A total of 20 right-handed human subjects with no reported history of neurological or

ophthalmologial disorders was recruited. In Experiment 1, 10 subjects (5 female, 5 male) aged

23-29 years (mean 25.4 years) participated. Another 10 subjects (5 female, 5 male) aged 21-

29 years (mean 25.1 years) took part in Experiment 2. All subjects had normal or corrected-

to-normal (contact lenses) vision. Subjects gave written informed consent prior to

participation and were naïve to the exact experimental question of the study. All experiments

were carried out in accordance with the “Declaration of Helsinki” and this type of

psychophysical experiments was approved by the ethics committee of Bremen University.


Results

Experiment 1

In Experiment 1, spatial generalization of the aftereffect from a trained to an untrained target

was tested in a blocked training design. Before testing spatial generalization of the aftereffect,

subjects adapted to the prism-induced shift of the visual world by executing pointing

movements to a specific target (left, central, or right).

Fig. 7.2 Experiment 1. A) Movements’ lateral deviation (in mm) from the left (white circles), central (black diamonds), and right target (grey circles) as a function of movement number during prism exposure. Negative values on the y-axis represent a leftward deviation from the target whereas positive values stand for a rightward deviation. B) Adaptation performance (i.e. difference of lateral deviations between movement 1 and movement 30) in each target trained. Adaptation performance differed highly significantly from 0 (p < .001, ***) as revealed by a t-test. Means and SEM of 10 subjects.

The temporal course of prism adaptation to the three targets is shown in Fig. 7.2a where the

lateral deviation of pointing movements is plotted as function of trial number. The initial

prism-induced lateral errors (movement 1) averaged -84.2 mm (± 6.9) for the left target, -73.4

mm (± 6.0) for the central target and -80.7 mm (± 8.3) for the right target. By movement

number 30, the lateral errors were reduced to -11.3 mm (± 2.6) for the left target, -7.2 mm (±

3.2) for the central target and -11.9 mm (± 2.5) for the right target. A one-way ANOVA for

repeated measures did not reveal a significant main effect (p > .05) of target position on the

movements’ initial lateral errors, hence deviations were comparable across targets. The same

was true for the deviations of movement number 30 (i.e. the end-level of deviations during the


course of adaptation). This observation of comparable start- and end-levels of movements’

lateral errors during prism exposure irrespective of the target trained is a basic prerequisite to

test the generalization of the aftereffect to other targets since it ensures that subjects adapted

to each target in the same manner and with equal strength.

Likewise, the adaptation performance (i.e. the difference between lateral errors of movement

number 1 and movement number 30; Fig. 7.2b) during prism-exposure did not differ

significantly across targets (p > .05; one-way ANOVA for repeated measures). Testing the

adaptation performance against the value 0 (a value of 0 would indicate no adaptation) using a

t-test revealed a highly significant (p < .001) reduction of lateral errors during prism exposure.

Hence, the amount of adaptation was similar for all targets trained suggesting that target

position had no differential impact on prism adaptation.

Generalization of aftereffects Subsequent to prism adaptation to a specific target,

generalization of the aftereffect to another target was tested. In three out of nine blocks, the

left target was defined as the target trained during prism exposure and generalization of the

aftereffect to the left, central, and right targets was assessed. In three other blocks, the central

target was trained during adaptation and in the last three blocks the right target was defined as

the target trained. Generalization of the aftereffect was tested for each target constituting nine

experimental blocks (see Fig. 7.1b); results are shown in Fig. 7.3.

Fig. 7.3 Experiment 1. Generalization of aftereffects from a target trained to a target tested. Magnitude of aftereffects in the left, central, and right target (“target tested”) after prism adaptation to the (A) left, (B) central, and (C) right target (“target trained”). Note that these aftereffects were assessed on the basis of a linear function fitted to the first four data points of the condition (see Methods). Means and SEM of 10 subjects.


When the left target was defined as the target trained (Fig. 7.3a) and the aftereffect was tested

for the same target (trained = tested), the aftereffect reached +75.3 mm (± 11.4). Testing the

aftereffect for the central target after training the left target resulted in an aftereffect of +80.3

mm (± 8.5). A smaller aftereffect of +62.8 mm (± 11.0) was recorded for the right target after

left target prism adaptation. A one-way ANOVA for repeated measures yielded no significant

main effect (p > .05) of target position on the magnitude of the aftereffects suggesting

complete generalization of aftereffects to all targets tested following blocked visuomotor

training to the left target.

For prism adaptation to the central target (Fig. 7.3b), pointing to the left target after removal

of the prisms yielded an aftereffect of +83.6 mm (± 6.5); the aftereffect for the central target

after adapting with the central target (trained = tested) was slightly smaller (+79.6 mm, ± 9.0).

The aftereffect decreased to +62.5 mm (± 6.1) for testing the right target after adaptation to

the central target. Here, a one-way ANOVA revealed a significant main effect (p < .05) of

target position on the magnitude of the aftereffect indicating a partial generalization of

aftereffects after prism adaptation to the central target.

When the right target was defined as the target trained during prism adaptation (Fig. 7.3c), an

aftereffect of +69.1 mm (± 7.3) was recorded when testing the left target. The aftereffect

increased to +96.3 mm (± 12.8) when it was tested for the central target after right target

prism adaptation. When generalization was assessed for the right target after adapting with the

right target (trained = tested), the aftereffect reached +83.5 mm (± 7.9). A one-way ANOVA

for repeated measures did not show a significant effect (p > .05) of target position on the

magnitude of the aftereffects indicating generalization across target locations tested.

In addition, the size of aftereffects was analyzed as a function of the spatial distance between

the target trained during prism adaptation and the target tested (Fig. 7.4). Data of conditions

were pooled according to the spatial distance between targets trained and those tested. When

the targets trained were identical to those tested (i.e. trained: left, tested: left etc.) the

aftereffect reached on average +79.4 mm (± 7.2). Proceeding one “target step” to the right

after prism adaptation (i.e. +250 mm; trained: left, tested: central; or else trained: central,

tested: right) decreased the aftereffect to +71.4 mm (± 5.6). Further increasing the spatial

distance between targets trained and tested by two “target steps” to the right (i.e. +500 mm;

trained: left, tested: right) reduced the aftereffect even more to +62.8 mm (± 11.0).

In the leftward direction, increasing the spatial distance between the target trained and the

target tested by -250 mm (i.e. one “target step” to the left; trained: right, tested: central; or


else trained: central, tested: left) increased the aftereffect to +89.9 mm (± 8.4). However,

when the spatial difference between targets trained and tested was as large as -500 mm (i.e.

two “target steps” to the left; trained: right, tested: left), the aftereffect dropped markedly to

+69.1 mm (± 7.3). Although there was an apparent stepwise trend within this set of data, a

one-way ANOVA for repeated measures did not show a significant main effect (p > .05) of

the spatial distance between targets trained and those tested on the magnitude of the

aftereffect, confirming (almost) complete generalization across target locations. To sum up,

under blocked visuomotor training conditions (i.e. a single target is trained during prism

adaptation) the aftereffect generalized to a first approximation linearly to untrained target

locations.

Fig. 7.4 Experiment 1. Magnitude of generalization aftereffects as a function of the spatial distance between the target trained and the target tested. Negative values on x-axis indicate that the target tested (generalization aftereffect) lies leftward from the trained target during prism adaptation whereas positive values denote that the target tested is located rightward from the target trained. Means and SEM of 10 subjects.

Experiment 2

In Experiment 2, subjects adapted by executing pointing movements alternately to two visual

targets in space and after this “mixed training” procedure generalization of the aftereffect to a

target located beyond (i.e. extrapolation task) or within (i.e. interpolation task) the adapted

visuomotor workspace was tested. In order to compare extrapolation and interpolation

aftereffects with the standard aftereffect in each target, the experiment began with recordings

of conventional prism adaptation and de-adaptation (aftereffect) for each target (single-target

pointing).

The lateral deviation of pointing movements as a function of trial number is displayed in Fig.

7.5a (adaptation) and Fig. 7.5b (de-adaptation) for each target. The movements’ initial prism-

induced lateral error (movement number 1) reached -97.0 mm (± 8.6) for the left target, -86.7

mm (± 6.9) for the central target, and -91.7 mm (± 10.9) for the right target. A one-way


ANOVA for repeated measures did not reveal any significant differences between target

positions (p > .05). In the course of prism adaptation, lateral errors were reduced to -12.2 mm

(± 4.3) for the left target, -5.4 mm (± 12.0) for the central target and -6.4 mm (± 6.1) for the

right target (movement number 30). As in Experiment 1, end-levels of prism adaptation were

comparable across targets (ANOVA: no significant main effect; p > .05) indicating that

subjects adapted in the same manner irrespective of target position in space.

Fig. 7.5 Experiment 2. Movements’ lateral deviation (in mm) from the left (white circles), central (black diamonds), and right target (grey circles) as a function of movement number during (A) prism adaptation and (B) de-adaptation (single-target pointing). Negative values on the y-axis represent a leftward deviation from the target whereas positive values stand for a rightward deviation. C) Adaptation performance (i.e. difference of lateral deviations between movement 1 and movement 30) and de-adaptation performance(i.e. difference of lateral deviations between movement 31 and movement 60) in the left (white bars), central (black bars) and right target (grey bars). Adaptation and de-adaptation performances differed highly significantly from 0 (p < .001, ***) as revealed by a t-test. Means and SEM of 10 subjects.

Removing the prisms (de-adaptation, Fig. 7.5b) led to pronounced initial lateral errors to the

right (aftereffect; movement number 31) amounting to +70.1 mm (± 4.2) for the left target,

+99.7 mm (± 10.2) for the central target and +76.7 mm (± 6.8) for the right target. A one-way

ANOVA for repeated measures revealed a significant main effect (p < .01) of target position

on the initial lateral deviation which is likely due to the increased aftereffect measured for the

central target. The end-levels of de-adaptation (movement number 60) on the other hand were

comparable across targets (ANOVA: no significant main effect; p > .05); lateral errors

reached -2.9 mm (± 1.9) for the left target, +5.5 mm (± 5.5) for the central target and -7.1 mm

(± 4.5) for the right target.


Adaptation performance (i.e. the difference of lateral errors between movement number 1 and

movement number 30) and de-adaptation performance (i.e. the difference of lateral errors

between movement number 31 and movement number 60) did not differ significantly

(ANOVA; p > .05) across targets (Fig. 7.5c) confirming that the improvement through

practice was largely the same irrespective of target position. Yet, adaptation and de-adaptation

performances differed highly significantly from 0 (t-test; p < .001). Together, these findings

confirm that adaptive behaviors were comparable across targets during single-target pointing.

Extrapolation aftereffects During prism adaptation in Experiment 2, subjects pointed

alternately to two target locations. After adapting for a specific range of the visuomotor

workspace generalization of the aftereffect to a target located beyond the adapted workspace

(i.e. extrapolation) was tested. The end-levels of mixed training adaptation for each target (i.e.

the mean lateral deviation of the last 5 movements) were assessed in order to compare the

completeness of the adaptation process. For the right target, the lateral error at the end-level

reached -5.5 mm (± 3.6) and was not significantly different from 0 (t-test; p > .05) whereas

for the central target the end-level of -8.7 mm (± 3.4) differed significantly from 0 (p < .05)

suggesting that adaptation to the central target was slightly incomplete. After adapting to the

right and the central target the extrapolation aftereffect (Fig. 7.6a, left panel) for the left target

reached +95.0 mm (± 4.1) whereas the standard aftereffect for the left target only amounted to

+68.9 mm (± 4.6) and this difference was statistically clearly significant (p < .01) as revealed

by a paired two-sided t-test. Thus, in comparison with the standard aftereffect for the left

target, the extrapolation aftereffect was significantly increased.

An extrapolation aftereffect for the right target was measured after adapting to both the left

and central targets (Fig. 7.6a, right panel). End-levels of mixed training adaptation for both

targets did not differ significantly from 0 (p > .05) indicating complete adaptation. The

extrapolation aftereffect for the right target reached +64.2 mm (± 6.8) whereas the standard

aftereffect for the right target was larger and averaged +78.8 mm (± 6.7). However, statistical

analysis did not show any significant difference between these two conditions (p > .05).

Interpolation aftereffects To measure an interpolation aftereffect, i.e. a possible

generalization of the aftereffect to a target located within the adapted visuomotor workspace,

the left and right targets were trained during prism adaptation and the aftereffect was assessed

for the central target. For the left target, the end-level of mixed training adaptation reached

+3.2 mm (± 2.6) and did not differ significantly from 0 (p > .05). However, the end-level for


the right target amounted to -19.1 mm (± 6.3) and was statistically different from 0 (p < .05)

indicating incomplete adaptation for the right target during mixed training.

The interpolation aftereffect for the central target amounted to +78.2 mm (± 4.5) and was

significantly (p < .05) smaller that the standard aftereffect for the central target (+93.0 mm, ±

8.4) as shown by a paired two-sided t-test (Fig. 7.6a, central panel). That is, the interpolation

task yielded a significantly smaller aftereffect than the standard aftereffect for the central

target.

Fig. 7.6 Experiment 2. A) Magnitude of standard aftereffects (black bars) and extrapolation (white bars) and interpolation (grey bar) aftereffects in the left, central, and right target. Note that these aftereffects were assessed on the basis of a linear function fitted to the first four data points of the condition (see Methods). B) Difference between the extrapolation aftereffect and the standard aftereffect (white bars) and between the interpolation aftereffect and the standard aftereffect (grey bar) in the corresponding target. Means and SEM of 10 subjects.

The standard aftereffect for specific targets was subtracted from the extrapolation and

interpolation aftereffects, respectively for each subject individually to evaluate the differences

between standard and extrapolation/interpolation aftereffects (Fig. 7.6b). The left target

extrapolation aftereffect was +26.1 mm (± 6.3) larger than the left target standard aftereffect


(p < .01; t-test against the value 0). The extrapolation aftereffect for the right target was -14.6

mm (± 10.2) smaller than the standard aftereffect for the right target but this difference was

not statistically significant (p > .05). In case of an interpolation, the aftereffect for the central

target was -14.8 mm (± 5.6) smaller than the central target standard aftereffect and this

difference was statistically significant (p < .05).

Discussion

Prism adaptation demonstrates the rapid experience-dependent updating of sensorimotor

representations when a lateral shift of the visual world is introduced by prisms. In the present

study, we addressed the spatial specificity of the adaptation process under different training

conditions.

Experiment 1: Linear generalization across target locations

In Experiment 1, visuomotor training during prism adaptation occurred as the usual blocked

training. Subjects adapted by pointing to a single visual target and immediately subsequent to

adaptation we tested generalization of the aftereffect to another visual target. The overall

pattern of results was as follows: Aftereffects largely transferred to other target locations

irrespective of whether the left, central, or right target was trained in a blocked fashion during

adaptation. Pointing to a target different from that trained during adaptation did not decrease

the size of the aftereffect. This linear generalization suggests a global type of adaptation

causing a relatively rigid shift of the entire visuomotor mapping which is in line with a

number of previous studies (e.g. Bedford, 1989; 1993; Fernandez-Ruiz et al., 2006; Redding

& Wallace, 2006a).

In the experimental setting used, each of the three visual targets had a distance of 25 cm to its

“neighbor”. Subjects were oriented such that the distal part of the right shoulder faced the

central target in order to ensure that subjects could reach out to each target in a convenient

way. This reduced the risk to obtain asymmetries in pointing behaviors simply due to the

mechanics of the body. Furthermore, our baseline correction method removed directional

biases related to target location. As is obvious from Fig. 7.2, adaptive behaviors did not

depend upon the spatial location of the target hence subjects adapted with equal strength to

each of the three targets. In particular, equal adaptation performances allowed a fair

comparison of the pattern of generalization between targets.


In case of nonlinear generalization, increasing the spatial distance between the targets trained

and tested should lead to a decrease of the aftereffect (i.e. a generalization gradient) indicating

that the adaptation mechanism is specific to the exact spatial context of the task executed. A

decreased or even absent aftereffect in an untrained target therefore would indicate that the

system resorts to the original visuomotor mapping as conditions between training and testing

differ sufficiently. However, since considerable and often not significantly smaller aftereffects

occurred even in targets spatially remote from the target trained generalization seems to be

linear.

It is important to keep in mind that the angular distances between visual targets amounted to

approx. 21 deg. (left to central target, or central to right target). That is, switching to another

target after adaptation necessarily included the execution of a new motor trajectory with

different angular arm posture parameters. Although our study did not record target-related

differences according to arm posture the linear generalization of aftereffects clearly shows

that adaptation was not specific to arm geometry (but see also Baraduc & Wolpert, 2002).

Therefore, it is unlikely that a type of motor adaptation specific to movement-related

parameters during task execution occurred. In other words: The aftereffect generalized across

quite different motor trajectories.

Surprisingly, a small but significant (p = .048) effect of target position on the size of the

aftereffect was revealed when the central target was defined as the target trained during

adaptation suggesting a partial generalization under these conditions (see Fig. 7.3b). A

possible explanation of this effect is that adaptation to the central target was somewhat easier

due to body position and that there was an effect of symmetric target positions with respect to

the body on the size of the aftereffect. However, given the fact that differences between these

aftereffects were quite small the overall pattern of linear generalization nevertheless remains

valid.

Linear generalization across locations due to internal constraints

What does the pattern of linear generalization of aftereffects across different visual locations

tell us about the characteristics of the adaptation process? Prism adaptation by pointing to a

discrete visual target in rapid succession produced a global type of spatial remapping affecting

untrained visual locations in the corresponding spatial map. This rigid transformational shift

suggests that task-related spatial representations in the visuomotor brain were modified as a

whole which is consistent with the results of both Bedford (1989; 1993) and Redding &

Wallace (2006a). A conceivable explanation of this finding is that the brain relies on internal


constraints about the physical world (cf. Bedford, 1989; 1993). Although experience is limited

to a narrow range of the workspace (i.e. pointing to a single target) spatial representations are

updated and shifted as a unit because the brain “assumes” that the represented space is regular

and uniform (a fundamental physical constraint). The prism-induced shift of the visual world

is experienced and compensated for in a local part of the spatial map but since internally

represented physical constraints predict that space is always uniform the spatial remapping

affects all points in space. This means that the rigid linear shift (i.e. global adaptation) results

from adaptation in a local part of the workspace in combination with an internal prediction on

the characteristics of the physical world, i.e. the linearity of space. In another conceptual

framework, this would correspond to a shift in the perceived position of the eyes for the

purpose of arm movements to all types of targets. This result is far from trivial given the lack

of generalization of prism adaptation between different types of movements to the same target

(cf. Baraduc & Wolpert, 2002; Martin et al., 1996b).

A study by Fernandez-Ruiz et al. (2006) in which hemiprisms were used has shown, however,

that topographical modifications in a regional part of the spatial map – as opposed to global

generalization – are also possible under certain conditions. These authors used a different task

than we did (i.e. throwing movements in far space) and a more important difference to our

study is that their subjects received 250 training trials during adaptation. Since the higher

number of training trials allowed more time for interactions, the system was capable of

performing specific local modifications in the spatial map. In our study, visuomotor

experience was restricted to 30 pointing movements in a local part of the workspace; yet

adaptation was global presumably reflecting a tendency to use linear functions as “default” for

the rapid updating of spatial representations (see also Bedford, 1993). Moreover, subjects had

no indication or benefit from using a regional modification of their visuomotor

representations.

Another aspect concerns the localization of adaptive shifts subject to the type of sensory

feedback information during adaptation. There is experimental evidence that under terminal

exposure (i.e. the finger tip is visible only at the end of the trajectory) shifts are larger in the

so-called visual eye-head system than in the proprioceptive hand-head system (see e.g.

Redding & Wallace, 2006a; Uhlarik & Canon, 1971). Our subjects received terminal visual

feedback during prism adaptation. Consequently, an adaptive shift predominantly localized in

visual coding necessarily affects all other points in the spatial map – this mechanism would

also explain the pattern of linear generalization of aftereffects observed in Experiment 1. Both

processes – linear generalization based upon internal physical constraints and the adaptive


visual shift under terminal exposure – may dynamically add to the rapid adaptive

performance.

Experiment 2: Generalization depends upon the direction tested

Experiment 2 addressed the pattern of spatial generalization of the aftereffect to an untrained

target location under another aspect. A fundamental difference to the first experiment was that

subjects did not perform pointing movements to a single target but alternately pointed to two

different target locations during prism adaptation. In particular, this form of mixed training

adaptation sampled a specific range of the subject’s visuomotor workspace. Following

“workspace adaptation” by mixed training the prisms were removed and generalization of the

aftereffect to a target located beyond (i.e. extrapolation) versus within (i.e. interpolation) the

adapted workspace was tested.

The pattern of generalization varied with the type of task (extrapolation vs. interpolation) and

the direction tested. Whereas the extrapolation aftereffect in the left target was larger than the

standard aftereffect in the left target, the extrapolation aftereffect in the right target was

smaller than the standard aftereffect. For interpolation, the aftereffect in the central target was

likewise reduced compared to the standard aftereffect (see Fig. 7.6). Hence, under these

conditions the pattern of spatial generalization of aftereffects was more complex than that

obtained after a blocked training adaptation procedure (Experiment 1). These results indicate

that the size of the aftereffect decreases for targets in the direction of the aftereffect and

increases for targets in the direction opposite to the aftereffect. This phenomenon of varying

sizes of aftereffects according to direction was investigated in detail in another study (cf.

Fahle et al., 2005). It is noteworthy that the effect of prism adaptation seems not to depend on

inter- vs. extrapolation as in the case for example of object recognition (cf. Bulthoff &

Edelman, 1992).

Underestimation of spatial distances following mixed training adaptation

The amount of generalization of the aftereffect to an untrained target following mixed training

adaptation depended upon the direction tested – how can this pattern of results be explained

with regard to the underlying processing? A possible way to interpret the data is to argue that

the visuomotor system underestimated spatial distances as a consequence of the mixed

training adaptation procedure.

Testing generalization of the aftereffect in the left target (i.e. extrapolation) included prism

adaptation by pointing to the central and right target. In order to point to the left target after


adaptation, the visuomotor system has to assess the actual spatial distance and to program a

compensatory trajectory in the leftward direction. However, if the spatial distance to the left

target is underestimated as a consequence of mixed training adaptation, the planned trajectory

to the left will become too short and therefore exhibits a certain rightward offset from the

target. This rightward offset and the standard rightward aftereffect sum up and so the

aftereffect recorded in the left target after mixed training adaptation is larger than the

corresponding standard aftereffect (see Fig. 7.6a, left panel). Underestimating the spatial

distance also accounts for the decreased extrapolation aftereffect in the right target compared

with the standard aftereffect. In this case, underestimation leads to a rightward trajectory

which under-compensates the actual distance to the right target and this effect subtracts from

the standard aftereffect. Hence the extrapolation aftereffect is smaller than the standard

aftereffect (see Fig. 7.6a, right panel).

This difference between extrapolation aftereffect and standard aftereffect was more

pronounced (and statistically significant) in the left than in the right target (see Fig. 7.6b).

This may be a consequence of the subject’s body position in space: Since the right shoulder

faced the central target the whole body was slightly shifted in the direction of the left target

and it is possible that this asymmetry of body position with respect to the targets enforced

underestimation of the distance to the left target.

The interpolation aftereffect in the central target was also smaller than the standard aftereffect

(see Fig. 7.6a, central panel) and this difference can also be explained in terms of an

underestimated spatial distance: The compensatory trajectory to the right was too short for the

actual distance and this effect was subtracted from the standard aftereffect. Interestingly, the

mean of both extrapolation aftereffects (+79.6 mm; ± 5.2) virtually equals the interpolation

aftereffect for the central target of +78.2 mm (± 4.5) suggesting a linear relationship for

underestimating spatial distances.

In visuomotor rotation learning (e.g. Krakauer et al., 2000) the extent of generalization

increases as training involves larger amounts of the workspace. In a psychophysical study on

dynamics learning, however, Mattar & Ostry (2007) have shown that the generalization after

training with two targets flanking the tested target location was as large as after training with

multiple targets suggesting that generalization depended upon interpolation between localized

learning. In our study, the interpolation aftereffect was significantly smaller than the standard

aftereffect in the central target hence adaptation by pointing to the flanking targets (i.e. left,

and right) did not entail full generalization.


The results of Experiment 2 are compatible with the notion that the visuomotor system

underestimates spatial distances as a consequence of the mixed training prism adaptation

procedure and employs a scaled linear function for generalization. In combination with a

rightward workspace shift obtained through mixed training, the adaptation mechanism might

involve a downscaling of spatial representations in order to restore accurate visuomotor

behavior. After adaptation, the downscaled spatial representation is applied to untrained

locations leading to a systematical underestimation of spatial distances.

These results are in line with previous studies on the performance of normals in cognitive

spatial tasks (e.g. line bisection, or number line bisection) after prism adaptation reporting that

especially leftward-shifting prisms affect higher-level spatial representations in the brain due

to hemispheric asymmetry (e.g. Berberovic & Mattingley, 2003; Colent et al., 2000; Loftus et

al., 2008). The role of the mixed training seems to involve an enhancement of the spatial re-

scaling by providing additional visuomotor exploration of the workspace; in contrast, if

training during adaptation is restricted to a single location in the workspace as it was in

Experiment 1, there is no enhancement effect hence generalization is linear and not scaled.

Acknowledgments

The authors declare that they have no competing financial interests. The authors would like to

thank C. Grimsen and S. Straube for the valuable comments on the manuscript.

Abkürzungsverzeichnis 92

Abkürzungsverzeichnis

A1 Primärer auditorischer Cortex

cm Zentimeter

fMRT Funktionelle Magnetresonanztomographie

LIP Laterales intraparietales Areal (engl. lateral intraparietal area)

M1 Primärer motorischer Cortex

mm Millimeter

PET Positronen-Emissions-Tomographie

PMC Prämotorischer Cortex

PMv Ventraler prämotorischer Cortex

PPC Posteriorer parietaler Cortex

PRR Parietale Reich-Region (engl. parietal reach region)

SEM Standardfehler (engl. standard error of the mean)

SMA Supplementär-motorisches Areal

V1 Primärer visueller Cortex

V2 Sekundärer visueller Cortex

VP Versuchsperson

ZNS Zentrales Nervensystem (Gehirn und Rückenmark)

Literaturverzeichnis 93

Literaturverzeichnis

Ahissar, M. & Hochstein, S. (2004). The reverse hierarchy theory of visual perceptual learning. Trends in Cognitive Sciences, 8, 457-464.

Albus, J. S. (1971). A theory of cerebellar function. Mathematical Biosciences, 10, 25-61.

Andersen, R. A. & Buneo, C. A. (2003). Sensorimotor integration in posterior parietal cortex. In A.M.Siegel, R. A. Andersen, H.-J. Freund, & D. Spencer (Hrsg.), Advances in Neurology, Vol.93 The parietal lobes (S. 159-177). Philadelphia, PA: Lippincott Williams & Wilkins.

Andersen, R. A., Meeker, D., Pesaran, B., Breznen, B., Buneo, C., & Scherberger, H. (2004). Sensorimotor transformations in the posterior parietal cortex. In M.S.Gazzaniga (Hrsg.), The cognitive neurosciences (3. Aufl., S. 463-474). Cambridge, MA: MIT Press.

Andersen, R. A., Snyder, L. H., Bradley, D. C., & Xing, J. (1997). Multimodal representation of space in the posterior parietal cortex and its use in planning movements. Annual Review of Neuroscience, 20, 303-330.

Baily, J. S. (1972). Adaptation to prisms: do proprioceptive changes mediate adapted behaviour with ballistic arm movements? Quarterly Journal of Experimental Psychology, 24,8-20.

Baizer, J. S., Kralj-Hans, I., & Glickstein, M. (1999). Cerebellar lesions and prism adaptation in macaque monkeys. Journal of Neurophysiology, 81, 1960-1965.

Baraduc, P. & Wolpert, D. M. (2002). Adaptation to a visuomotor shift depends on the starting posture. Journal of Neurophysiology, 88, 973-981.

Bays, P. M. & Wolpert, D. M. (2007). Computational principles of sensorimotor control that minimize uncertainty and variability. Journal of Physiology, 578, 387-396.

Bedford, F. L. (1989). Constraints on learning new mappings between perceptual dimensions. Journal of Experimental Psychology.Human Perception and Performance, 15, 232-248.

Bedford, F. L. (1993). Perceptual and cognitive spatial learning. Journal of Experimental Psychology.Human Perception and Performance, 19, 517-530.

Bedford, F. L. (1999). Keeping perception accurate. Trends in Cognitive Sciences, 3, 4-11.

Berberovic, N. & Mattingley, J. B. (2003). Effects of prismatic adaptation on judgements of spatial extent in peripersonal and extrapersonal space. Neuropsychologia, 41, 493-503.

Birbaumer, N. & Schmidt, R. F. (2003). Biologische Psychologie. (5. Aufl.) Berlin: Springer.

Blickhan, R. (2001). Motorische Systeme bei Vertebraten. In J.Dudel, R. Menzel, & R. F. Schmidt (Hrsg.), Neurowissenschaft. Vom Molekül zur Kognition (2. Aufl., S. 191-213). Berlin: Springer.


Bulthoff, H. H. & Edelman, S. (1992). Psychophysical support for a two-dimensional view interpolation theory of object recognition. Proceedings of the National Academy of Sciences of the United States of America, 89, 60-64.

Buneo, C. A. & Andersen, R. A. (2006). The posterior parietal cortex: sensorimotor interface for the planning and online control of visually guided movements. Neuropsychologia, 44,2594-2606.

Buonomano, D. V. & Merzenich, M. M. (1998). Cortical plasticity: from synapses to maps. Annual Review of Neuroscience, 21, 149-186.

Churchland, M. M., Afshar, A., & Shenoy, K. V. (2006). A central source of movement variability. Neuron, 52, 1085-1096.

Clower, D. M. & Boussaoud, D. (2000). Selective use of perceptual recalibration versus visuomotor skill acquisition. Journal of Neurophysiology, 84, 2703-2708.

Clower, D. M., Hoffman, J. M., Votaw, J. R., Faber, T. L., Woods, R. P., & Alexander, G. E. (1996). Role of posterior parietal cortex in the recalibration of visually guided reaching. Nature, 383, 618-621.

Colent, C., Pisella, L., Bernieri, C., Rode, G., & Rossetti, Y. (2000). Cognitive bias induced by visuo-motor adaptation to prisms: a simulation of unilateral neglect in normal individuals? Neuroreport, 11, 1899-1902.

Connolly, J. D., Andersen, R. A., & Goodale, M. A. (2003). FMRI evidence for a 'parietal reach region' in the human brain. Experimental Brain Research, 153, 140-145.

Dahmen, J. C. & King, A. J. (2007). Learning to hear: plasticity of auditory cortical processing. Current Opinion in Neurobiology, 17, 456-464.

Doyon, J. & Benali, H. (2005). Reorganization and plasticity in the adult brain during learning of motor skills. Current Opinion in Neurobiology, 15, 161-167.

Fahle, M. (2002). Introduction. In M.Fahle & T. Poggio (Hrsg.), Perceptual learning (S. IX-XX). Cambridge, MA: MIT Press.

Fahle, M. (2004). Perceptual learning: a case for early selection. Journal of Vision, 4, 879-890.

Fahle, M. (2005). Perceptual learning: specificity versus generalization. Current Opinion in Neurobiology, 15, 154-160.

Fahle, M. (2008). Perceptual learning and sensory plasticity. In L.R.Squire (Hrsg.), New encyclopedia of neuroscience (S. ?). Amsterdam: Elsevier (im Druck).

Fahle, M., Wischhusen, S., & Spang, K. M. (2005). Prism adaptation by gain control. Perception, 34 (Supplement), 79.

Fernandez-Ruiz, J. & Diaz, R. (1999). Prism adaptation and aftereffect: specifying the properties of a procedural memory system. Learning & Memory, 6, 47-53.


Fernandez-Ruiz, J., Diaz, R., Aguilar, C., & Hall-Haro, C. (2004). Decay of prism aftereffects under passive and active conditions. Cognitive Brain Research, 20, 92-97.

Fernandez-Ruiz, J., Diaz, R., Hall-Haro, C., Vergara, P., Mischner, J., Nunez, L. et al. (2003). Normal prism adaptation but reduced after-effect in basal ganglia disorders using a throwing task. European Journal of Neuroscience, 18, 689-694.

Fernandez-Ruiz, J., Diaz, R., Moreno-Briseno, P., Campos-Romo, A., & Ojeda, R. (2006). Rapid topographical plasticity of the visuomotor spatial transformation. Journal of Neuroscience, 26, 1986-1990.

Fernandez-Ruiz, J., Hall-Haro, C., Diaz, R., Mischner, J., Vergara, P., & Lopez-Garcia, J. C. (2000). Learning motor synergies makes use of information on muscular load. Learning & Memory, 7, 193-198.

Ghez, C. & Thach, W. T. (2000). The cerebellum. In E.R.Kandel, J. H. Schwartz, & T. M. Jessell (Hrsg.), Principles of neural sciences (4. Aufl., S. 832-852). New York: McGraw-Hill.

Gilbert, C. D., Sigman, M., & Crist, R. E. (2001). The neural basis of perceptual learning. Neuron, 31, 681-697.

Glickstein, M. (2007). What does the cerebellum really do? Current Biology, 17, R824-R827.

Godde, B., Stauffenberg, B., Spengler, F., & Dinse, H. R. (2000). Tactile coactivation-induced changes in spatial discrimination performance. Journal of Neuroscience, 20, 1597-1604.

Goodale, M. A. & Milner, A. D. (1992). Separate visual pathways for perception and action. Trends in Neurosciences, 15, 20-25.

Goodale, M. A. & Westwood, D. A. (2004). An evolving view of duplex vision: separate but interacting cortical pathways for perception and action. Current Opinion in Neurobiology, 14,203-211.

Greger, B. & Norris, S. (2005). Simple spike firing in the posterior lateral cerebellar cortex of Macaque Mulatta was correlated with success-failure during a visually guided reaching task. Experimental Brain Research, 167, 660-665.

Grill-Spector, K. & Malach, R. (2004). The human visual cortex. Annual Review of Neuroscience, 27, 649-677.

Halsband, U. & Lange, R. K. (2006). Motor learning in man: a review of functional and clinical studies. Journal of Physiology (Paris), 99, 414-424.

Harris, C. S. (1963). Adaptation to displaced vision: visual, motor, or proprioceptive change? Science, 140, 812-813.

Harris, C. S. (1965). Perceptual adaptation to inverted, reversed, and displaced vision. Psychological Review, 72, 419-444.

Harris, C. S. (1980). Insight or out of sight?: Two examples of perceptual plasticity in the human adult. In C.S.Harris (Hrsg.), Visual coding and adaptability (S. 95-149). Hillsdale, NJ: Lawrence Erlbaum.


Held, R. & Freedman, S. J. (1963). Plasticity in human sensorimotor control. Science, 142,455-462.

Helmholtz, H. (1867). Handbuch der physiologischen Optik. Leipzig: Leopold Voss.

Hikosaka, O., Nakamura, K., Sakai, K., & Nakahara, H. (2002). Central mechanisms of motor skill learning. Current Opinion in Neurobiology, 12, 217-222.

Hodzic, A., Veit, R., Karim, A. A., Erb, M., & Godde, B. (2004). Improvement and decline in tactile discrimination behavior after cortical plasticity induced by passive tactile coactivation. Journal of Neuroscience, 24, 442-446.

Huk, A. C., Ress, D., & Heeger, D. J. (2001). Neuronal basis of the motion aftereffect reconsidered. Neuron, 32, 161-172.

Ibbotson, M. R. (2005). Physiological mechanisms of adaptation in the visual system. In C.W.G.Clifford & G. Rhodes (Hrsg.), Fitting the mind to the world. Adaptation and after-effects in high-level vision (S. 17-45). Oxford: Oxford University Press.

Karmarkar, U. R. & Dan, Y. (2006). Experience-dependent plasticity in adult visual cortex. Neuron, 52, 577-585.

Kitazawa, S., Kimura, T., & Uka, T. (1997). Prism adaptation of reaching movements: specificity for the velocity of reaching. Journal of Neuroscience, 17, 1481-1492.

Kitazawa, S., Kimura, T., & Yin, P. B. (1998). Cerebellar complex spikes encode both destinations and errors in arm movements. Nature, 392, 494-497.

Kitazawa, S., Kohno, T., & Uka, T. (1995). Effects of delayed visual information on the rate and amount of prism adaptation in the human. Journal of Neuroscience, 15, 7644-7652.

Kitazawa, S. & Yin, P. B. (2002). Prism adaptation with delayed visual error signals in the monkey. Experimental Brain Research, 144, 258-261.

Konczak, J. (2003). Motorisches Lernen. In H.-O.Karnath & P. Thier (Hrsg.), Neuropsychologie (S. 669-676). Berlin: Springer.

Konen, C. S. & Kastner, S. (2008). Two hierarchically organized neural systems for object information in human visual cortex. Nature Neuroscience, 11, 224-231.

Krakauer, J. & Ghez, C. (2000). Voluntary movement. In E.R.Kandel, J. H. Schwartz, & T. M. Jessell (Hrsg.), Principles of neural sciences (4. Aufl., S. 756-781). New York: McGraw-Hill.

Krakauer, J. W., Pine, Z. M., Ghilardi, M. F., & Ghez, C. (2000). Learning of visuomotor transformations for vectorial planning of reaching trajectories. Journal of Neuroscience, 20,8916-8924.

Kurata, K. & Hoshi, E. (1999). Reacquisition deficits in prism adaptation after muscimol microinjection into the ventral premotor cortex of monkeys. Journal of Neurophysiology, 81,1927-1938.


Loftus, A. M., Nicholls, M. E. R., Mattingley, J. B., & Bradshaw, J. L. (2008). Left to right: Representational biases for numbers and the effect of visuomotor adaptation. Cognition (im Druck).

Luaute, J., Michel, C., Rode, G., Pisella, L., Jacquin-Court, Costes, N. et al. (2006). Functional anatomy of the therapeutic effects of prism adaptation on left neglect. Neurology, 66, 1859-1867.

Marotta, J. J., Keith, G. P., & Crawford, J. D. (2005). Task-specific sensorimotor adaptation to reversing prisms. Journal of Neurophysiology, 93, 1104-1110.

Marr, D. (1969). A theory of cerebellar cortex. Journal of Physiology, 202, 437-470.

Martin, T. A., Greger, B. E., Norris, S. A., & Thach, W. T. (2001). Throwing accuracy in the vertical direction during prism adaptation: not simply timing of ball release. Journal of Neurophysiology, 85, 2298-2302.

Martin, T. A., Keating, J. G., Goodkin, H. P., Bastian, A. J., & Thach, W. T. (1996a). Throwing while looking through prisms. I. Focal olivocerebellar lesions impair adaptation. Brain, 119 ( Pt 4), 1183-1198.

Martin, T. A., Keating, J. G., Goodkin, H. P., Bastian, A. J., & Thach, W. T. (1996b). Throwing while looking through prisms. II. Specificity and storage of multiple gaze-throw calibrations. Brain, 119 ( Pt 4), 1199-1211.

Martin, T. A., Norris, S. A., Greger, B. E., & Thach, W. T. (2002). Dynamic coordination of body parts during prism adaptation. Journal of Neurophysiology, 88, 1685-1694.

Mattar, A. A. & Ostry, D. J. (2007). Modifiability of generalization in dynamics learning. Journal of Neurophysiology, 98, 3321-3329.

Menzel, R. (2001). Neuronale Plastizität, Lernen und Gedächtnis. In J.Dudel, R. Menzel, & R. F. Schmidt (Hrsg.), Neurowissenschaft. Vom Molekül zur Kognition (2. Aufl., S. 478-526). Berlin: Springer.

Michel, C., Pisella, L., Prablanc, C., Rode, G., & Rossetti, Y. (2007). Enhancing visuomotor adaptation by reducing error signals: single-step (aware) versus multiple-step (unaware) exposure to wedge prisms. Journal of Cognitive Neuroscience, 19, 341-350.

Miyauchi, S., Egusa, H., Amagase, M., Sekiyama, K., Imaruoka, T., & Tashiro, T. (2004). Adaptation to left-right reversed vision rapidly activates ipsilateral visual cortex in humans. Journal of Physiology (Paris), 98, 207-219.

Mollon, J. D. & Danilova, M. V. (1996). Three remarks on perceptual learning. Spatial Vision, 10, 51-58.

Morton, S. M. & Bastian, A. J. (2004). Prism adaptation during walking generalizes to reaching and requires the cerebellum. Journal of Neurophysiology, 92, 2497-2509.

Newport, R., Brown, L., Husain, M., Mort, D., & Jackson, S. R. (2006). The role of the posterior parietal lobe in prism adaptation: Failure to adapt to optical prisms in a patient with bilateral damage to posterior parietal cortex. Cortex, 42, 720-729.


Newport, R. & Jackson, S. R. (2006). Posterior parietal cortex and the dissociable components of prism adaptation. Neuropsychologia, 44, 2757-2765.

Norris, S. A., Greger, B. E., Martin, T. A., & Thach, W. T. (2001). Prism adaptation of reaching is dependent on the type of visual feedback of hand and target position. Brain Research, 905, 207-219.

Palmer, S. E. (1999). Vision science. Photons to phenomenology. Cambridge, MA: MIT Press.

Patzelt, F., Riegel, M., Ernst, U., & Pawelzik, K. (2007). Self-organised critical noise amplification in human closed loop control. Eingereicht.

Paz, R., Wise, S. P., & Vaadia, E. (2004). Viewing and doing: similar cortical mechanisms for perceptual and motor learning. Trends in Neurosciences, 27, 496-503.

Pisella, L., Rossetti, Y., Michel, C., Rode, G., Boisson, D., Pelisson, D. et al. (2005). Ipsidirectional impairment of prism adaptation after unilateral lesion of anterior cerebellum. Neurology, 65, 150-152.

Pleger, B., Foerster, A. F., Ragert, P., Dinse, H. R., Schwenkreis, P., Malin, J. P. et al. (2003). Functional imaging of perceptual learning in human primary and secondary somatosensory cortex. Neuron, 40, 643-653.

Poggio, T. & Bizzi, E. (2004). Generalization in vision and motor control. Nature, 431, 768-774.

Previc, F. H. (1998). The neuropsychology of 3-D space. Psychological Bulletin, 124, 123-164.

Redding, G. M., Rossetti, Y., & Wallace, B. (2005). Applications of prism adaptation: a tutorial in theory and method. Neuroscience and Biobehavioral Reviews, 29, 431-444.

Redding, G. M. & Wallace, B. (1988). Components of prism adaptation in terminal and concurrent exposure: organization of the eye-hand coordination loop. Perception & Psychophysics, 44, 59-68.

Redding, G. M. & Wallace, B. (2002). Strategic calibration and spatial alignment: a model from prism adaptation. Journal of Motor Behavior, 34, 126-138.

Redding, G. M. & Wallace, B. (2003a). Dual prism adaptation: calibration or alignment? Journal of Motor Behavior, 35, 399-408.

Redding, G. M. & Wallace, B. (2003b). First-trial adaptation to prism exposure. Journal of Motor Behavior, 35, 229-245.

Redding, G. M. & Wallace, B. (2004). First-trial adaptation to prism exposure: artifact of visual capture. Journal of Motor Behavior, 36, 291-304.

Redding, G. M. & Wallace, B. (2006a). Generalization of prism adaptation. Journal of Experimental Psychology.Human Perception and Performance, 32, 1006-1022.


Redding, G. M. & Wallace, B. (2006b). Prism adaptation and unilateral neglect: review and analysis. Neuropsychologia, 44, 1-20.

Robinson, F. R. (1995). Role of the cerebellum in movement control and adaptation. Current Opinion in Neurobiology, 5, 755-762.

Rode, G., Pisella, L., Rossetti, Y., Farne, A., & Boisson, D. (2003). Bottom-up transfer of sensory-motor plasticity to recovery of spatial cognition: visuomotor adaptation and spatial neglect. Progress in Brain Research, 142, 273-287.

Roller, C. A., Cohen, H. S., Kimball, K. T., & Bloomberg, J. J. (2001). Variable practice with lenses improves visuo-motor plasticity. Cognitive Brain Research, 12, 341-352.

Rossetti, Y., Rode, G., Pisella, L., Farne, A., Li, L., Boisson, D. et al. (1998). Prism adaptation to a rightward optical deviation rehabilitates left hemispatial neglect. Nature, 395,166-169.

Schenk, T. (2006). An allocentric rather than perceptual deficit in patient D.F. Nature Neuroscience, 9, 1369-1370.

Scherberger, H. & Andersen, R. A. (2003). Sensorimotor transformation in the posterior parietal cortex. In L.M.Chalupa & J. S. Werner (Hrsg.), The visual neurosciences (S. 1324-1336). Cambridge, MA: MIT Press.

Seitz, A. & Watanabe, T. (2005). A unified model for perceptual learning. Trends in Cognitive Sciences, 9, 329-334.

Serino, A., Angeli, V., Frassinetti, F., & Ladavas, E. (2006). Mechanisms underlying neglect recovery after prism adaptation. Neuropsychologia, 44, 1068-1078.

Shadmehr, R. & Wise, S. P. (2005). The computational neurobiology of reaching and pointing. A foundation for motor learning. Cambridge, MA: MIT Press.

Sterr, A. (2008). Neuronale Plastizität. In S.Gauggel & M. Herrmann (Hrsg.), Handbuch der Neuro- und Biopsychologie (S. 44-53). Göttingen: Hogrefe.

Steven, M. S. & Blakemore, C. (2004). Cortical plasticity in the adult human brain. In M.S.Gazzaniga (Hrsg.), The cognitive neurosciences (3. Aufl., S. 1243-1254). Cambridge, MA: MIT Press.

Sugita, Y. (1996). Global plasticity in adult visual cortex following reversal of visual input. Nature, 380, 523-526.

Tanaka, Y., Miyauchi, S., Misaki, M., & Tashiro, T. (2007). Mirror symmetrical transfer of perceptual learning by prism adaptation. Vision Research, 47, 1350-1361.

Thach, W. T., Goodkin, H. P., & Keating, J. G. (1992). The cerebellum and the adaptive coordination of movement. Annual Review of Neuroscience, 15, 403-442.

Uhlarik, J. J. & Canon, L. K. (1971). Influence of concurrent and terminal exposure conditions on the nature of perceptual adaptation. Journal of Experimental Psychology, 91,233-239.


van Beers, R. J., Haggard, P., & Wolpert, D. M. (2004). The role of execution noise in movement variability. Journal of Neurophysiology, 91, 1050-1063.

van Beers, R. J., Wolpert, D. M., & Haggard, P. (2002). When feeling is more important than seeing in sensorimotor adaptation. Current Biology, 12, 834-837.

Wade, N. J. & Verstraten, F. A. J. (2005). Accommodating the past: a selective history of adaptation. In C.W.G.Clifford & G. Rhodes (Hrsg.), Fitting the mind to the world. Adaptation and after-effects in high-level vision (S. 83-101). Oxford: Oxford University Press.

Weiner, M. J., Hallett, M., & Funkenstein, H. H. (1983). Adaptation to lateral displacement of vision in patients with lesions of the central nervous system. Neurology, 33, 766-772.

Welch, R. B. (1978). Perceptual modification. Adapting to altered sensory environments. New York: Academic Press.

Welch, R. B., Choe, C. S., & Heinrich, D. R. (1974). Evidence for a three-component model of prism adaptation. Journal of Experimental Psychology, 103, 700-705.

Wurtz, R. H. & Kandel, E. R. (2000a). Central visual pathways. In E.R.Kandel, J. H. Schwartz, & T. M. Jessell (Hrsg.), Principles of neural sciences (4. Aufl., S. 523-547). New York: McGraw-Hill.

Wurtz, R. H. & Kandel, E. R. (2000b). Perception of motion, depth, and form. In E.R.Kandel, J. H. Schwartz, & T. M. Jessell (Hrsg.), Principles of neural sciences (4. Aufl., S. 548-571). New York: McGraw-Hill.

LERNEN UND ADAPTATION IM VISUELLEN …elib.suub.uni-bremen.de/diss/docs/00010953.pdf · genannten...

Documents

Transcript of LERNEN UND ADAPTATION IM VISUELLEN …elib.suub.uni-bremen.de/diss/docs/00010953.pdf · genannten...