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8 CONCLUSION: THE ROLE OF SIMULATION IN MOTOR COGNITION

8 CONCLUSION: THE ROLE OF SIMULATION IN MOTOR COGNITION

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Section III

Motor Learning and Performance



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10



The Arbitrary Mapping

of Sensory Inputs

to Voluntary and

Involuntary Movement:

Learning-Dependent

Activity in the Motor

Cortex and Other

Telencephalic Networks

Peter J. Brasted and Steven P. Wise



CONTENTS

Abstract

10.1 Introduction

10.1.1 Types of Arbitrary Mapping

10.1.1.1 Mapping Stimuli to Movements

10.1.1.2 Mapping Stimuli to Representations Other than

Movements

10.2 Arbitrary Mapping of Stimuli to Reflexes

10.2.1 Pavlovian Eye-Blink Conditioning

10.2.2 Pavlovian Approach Conditioning

10.2.2.1 Learning-Related Activity Underlying Pavlovian

Approach Conditioning

10.2.2.2 Understanding Pavlovian Approach Behavior as a

Type of Arbitrary Mapping

10.3 Arbitrary Mapping of Stimuli to Internal Models

10.4 Arbitrary Mapping of Stimuli to Involuntary Response Habits

10.5 Arbitrary Mapping of Stimuli to Voluntary Movement

10.5.1 Learning Rate in Relation to Implicit and Explicit Knowledge

0-8493-1287-6/05/$0.00+$1.50

© 2005 by CRC Press LLC



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10.5.2 Neuropsychology

10.5.2.1 Premotor Cortex

10.5.2.2 Prefrontal Cortex

10.5.2.3 Hippocampal System

10.5.2.4 Basal Ganglia

10.5.2.5 Unnecessary Structures

10.5.2.6 Summary of the Neuropsychology

10.5.3 Neurophysiology

10.5.3.1 Premotor Cortex

10.5.3.2 Prefrontal Cortex

10.5.3.3 Basal Ganglia

10.5.3.4 Hippocampal System

10.5.3.5 Summary of the Neurophysiology

10.5.4 Neuroimaging

10.5.4.1 Methodological Considerations

10.5.4.2 Established Mappings

10.5.4.3 Learning New Mappings

10.5.4.4 Summary

10.6 Arbitrary Mapping of Stimuli to Cognitive Representations

10.7 Conclusion

References



ABSTRACT

Studies on the role of the motor cortex in voluntary movement usually focus on

standard sensorimotor mapping, in which movements are directed toward sensory

cues. Sensorimotor behavior can, however, show much greater flexibility. Some

variants rely on an algorithmic transformation between a cue’s location and that of

a movement target. The well-known “antisaccade” task and its analogues in reaching

serve as special cases of such transformational mapping, one form of nonstandard

mapping. Other forms of nonstandard mapping differ from both of the above: they

are arbitrary. In arbitrary sensorimotor mapping, the cue’s location has no systematic

spatial relationship with the response. Here we explore several types of arbitrary

mapping, with emphasis on the neural basis of learning these behaviors.



10.1 INTRODUCTION

Many responses to sensory stimuli involve reaching toward or looking at them.

Shifting one’s gaze to a red traffic light and reaching for a car’s brake pedal exemplify

this kind of sensorimotor integration, sometimes termed standard sensorimotor

mapping.1 Other behaviors lack any spatial correspondence between a stimulus and

a response, of which Pavlovian conditioned responses provide a particularly clear

example. The salivation of Pavlov’s dog follows a conditioned stimulus, the ringing

of a bell, but there is no response directed toward the bell or, indeed, toward anything

at all. Like braking at a red traffic light, Pavlovian learning depends on an arbitrary



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relationship between a response and the stimulus that triggers it. That is, it depends

on arbitrary sensorimotor mapping.1 Some forms of arbitrary mapping involve

choosing among goals or actions on the basis of color or shape cues. The example

of braking at a red light, but accelerating at a yellow one, serves as a prototypical

(and sometimes dangerous) example of such behavior. In the laboratory, this kind

of task goes by several names, including conditional motor learning, conditional

discrimination, and stimulus–response conditioning. One stimulus provides the context (or “instruction”) for a given response, whereas other stimuli establish the

contexts for different responses.2 Arbitrary mapping enables the association of any

dimensions of any stimuli with any actions or goals.

The importance of arbitrary sensorimotor mapping is well recognized — a great

quantity of animal psychology revolves around stimulus–response conditioning —

but the diversity among its types is not so well appreciated. Take, once again, the

example of braking at a red light. On the surface, this behavior seems to depend on

a straightforward stimulus–response mechanism. The mechanism comprises an

input, the red light, a black box that relates this input to a response, and the response,

which consists of jamming on the brakes. This surface simplicity is, however,

misleading. Beyond this account lies a multitude of alternative neural mechanisms.

Using the mechanism described above, a person makes a braking response in the

context of the red light regardless of the predicted outcome of that action3 and

without any consideration of alternatives.2 Such behaviors are often called habits,

but experts use this term with varying degrees of rigor. Experiments on rodents

sometimes entail the assumption that all stimulus–response relationships are habits.4,5

But other possibilities exist. Braking at a red light could reflect a voluntary decision,

one based on an attended decision among alternative actions2 and their predicted

outcomes.3 In addition, the same behavior might also reflect high-order cognition,

such as a decision about whether to follow the rule that traffic signals must be obeyed.

Because the title of this book is Motor Cortex in Voluntary Movements, this

chapter’s topic might seem somewhat out of place. However, the motor cortex —

construed broadly to include the premotor areas — plays a crucial role in arbitrary

sensorimotor mapping, which Passingham has held to be the epitome of voluntary

movement. In his seminal monograph, Passingham2 defined a voluntary movement

as one made in the context of choosing among alternative, learned actions based on

attention to those actions and their consequences. We take up this kind of arbitrary

mapping in Section 10.5, in which we discuss the premotor areas involved in this

kind of learning. In addition, we summarize evidence concerning the contribution

of other parts of the telencephalon — specifically the prefrontal cortex, the basal

ganglia, and the hippocampal system — to this kind of behavior. Because of the

explosion of data coming from neuroimaging methods, Section 10.5 also contains

a discussion of that literature and its relation to neurophysiological and neuropsychological results. Before dealing with voluntary movement, however, we consider

arbitrary sensorimotor mapping in three kinds of involuntary movements — conditioned reflexes (Section 10.2), internal models (Section 10.3), and habits (Section 10.4).

Finally, we consider arbitrary mapping in relation to other aspects of response

selection, specifically those involving response rules (Section 10.6). For a fuller

consideration of arbitrary mapping, readers might consult Passingham’s monograph2



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and previous reviews, which have focused on the changes in cortical activity that

accompany the learning of arbitrary sensorimotor mappings,6 the role of the hippocampal system7,8 and the prefrontal cortex9 in such mappings, and the relevance of

arbitrary mapping to the life of monkeys.10



10.1.1 TYPES



OF



ARBITRARY MAPPING



10.1.1.1 Mapping Stimuli to Movements

Stimulus–Reflex Mappings. Pavlovian conditioning is rarely discussed in the context of arbitrary sensorimotor mapping. Also known as classical conditioning, it

requires the association of a stimulus, called the conditioned stimulus (CS), with a

different stimulus, called the unconditioned stimulus (US), which is genetically

programmed to trigger a reflex response, known as the unconditioned reflex (UR).

Usually, pairing of the CS with the US in time causes the induction of a conditioned

response (CR). For a CS consisting of a tone and an electric shock for the US, the

animal responds to the tone with a protective response (the CR), which resembles

the UR. The choice of CS is arbitrary; any neutral input will do (although not

necessarily equally well). The two types of Pavlovian conditioning differ slightly.

In one type, as described above, an initially neutral CS predicts a US, which triggers

a reflex such as eye blink or limb flexion. This topic is taken up in Section 10.2.1.

In another form of Pavlovian conditioning, some neural process stores a similarly

predictive relationship between an initially neutral CS and the availability of substances like water or food that reduce an innate drive. Unlike the reflexes involved

in the former variety of Pavlovian conditioning, the latter involves the triggering of

consumatory behaviors such as eating and drinking. For example, animals lick a

water spout after a sound that has been associated with the availability of fluid from

that spout. This kind of behavior sometimes goes by the name Pavlovian-approach

behavior (a topic taken up in Section 10.2.2). Both kinds of arbitrary sensorimotor

mapping rely on the fact that one stimulus predicts another stimulus, one that triggers

an innate, prepotent, or reflex response.

Stimulus–IM Mappings. Stimuli can also be arbitrarily mapped to motor programs. For example, Shadmehr and his colleagues (this volume11) discuss the evidence

for internal models (IMs) of limb dynamics. These models involve predictions —

computed by neural networks — about what motor commands will be needed to

achieve a goal (and also about what feedback should occur). The IMs are not

examples of arbitrary sensorimotor mapping per se. Arbitrary stimuli can, however,

be mapped to IMs, a topic taken up in Section 10.3.

Stimulus–Response Mappings in Habits. When animals make responses in a

given stimulus context, that response is more likely to be repeated if a reinforcer,

such as water for a thirsty animal, follows the action. This fact lies at the basis of

instrumental conditioning. According to Pearce,12 many influential learning theories

of the past 100 years or so13–15 have held that after consistently making a response

in a given stimulus context, the expected outcome of the action no longer influences

an animal’s performance. The instrumental conditioning has produced an involuntary

movement, often known as a habit or simply as a stimulus–response (S–R) association.



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Note, however, that many S–R associations are not habits. When used strictly, the

term “habit” applies only to certain learned behaviors, those that are so “overlearned”

that they have become involuntary in that they no longer depend on the predicted

outcome of the response.3 It is also important to note that the response in an S–R

association is not a standard sensorimotor mapping. That is, it need not be directed

toward either the reinforcers, their source (such as water spouts and feeding trays),

or the conditioned stimuli. The response is spatially arbitrary. We take up this kind

of arbitrary mapping in Section 10.4.

Stimulus–Response Mappings in Voluntary Movement. Section 10.5 takes

up arbitrary stimulus–response associations that are not habits, at least as defined

according to contemporary animal learning theory.3

10.1.1.2 Mapping Stimuli to Representations Other

than Movements

Stimulus–Value Mappings. Although we focus here on arbitrary sensorimotor mappings, there are many other kinds of arbitrary mappings. Stimuli can be arbitrarily

mapped to their biological value. For example, stimuli come to adopt either positive

or negative affective valence, i.e., “goodness” or “badness,” as a function of experience. This kind of arbitrary mapping is relevant to sensorimotor mapping because

stimulus–value mappings can lead to a response,16–19 as discussed in Section 10.2.2.2.

Stimulus–Rule Mappings. In addition to stimulus–response and stimulus–value

mappings, stimuli can be arbitrarily mapping onto more general representations. For

example, a stimulus could evoke a response rule, a topic explored in Section 10.4.

Note that we focus here on the arbitrary mapping of stimuli to rules, not the

representation of a rule per se, as reported previously in both the spatial20–22 and

nonspatial22–24 domains.

Stimulus–Meaning Mappings. In Murray et al.,10 we argued that evolution coopted an existing arbitrary mapping ability for speech and language. Stimuli map

to their abstract meaning in an arbitrary manner. For example, the phonemes and

graphemes of language elicit meanings that usually have an arbitrary relationship

with those auditory and visual stimuli. And this kind of arbitrary mapping leads to

a type of response mapping not mentioned above. In speech production, the relationship between the meaning a speaker intends to express and the motor commands

underlying vocal or manual gestures that convey that meaning reflects a similarly

arbitrary mapping.

Given these several types of arbitrary mappings, what is known about the neural

mechanisms that underlie their learning?



10.2 ARBITRARY MAPPING OF STIMULI TO REFLEXES

Cells in a variety of structures show learning-related activity for responses that

depend upon Pavlovian conditioning, including the basal ganglia,25–28 the

amygdala,29–31 the motor cortex,32 the cerebellum,33 and the hippocampus.34 Why are

there so many different structures involved? Partly, perhaps, because there are several



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types of Pavlovian conditioning. One type relies mainly on the cerebellum and its

output mechanisms.33 In response to potentially damaging stimuli, such as shocks,

taps, and air jets, this type of conditioned response involves protective movements

such as eye blinks and limb withdrawal. Another type, called Pavlovian approach

behavior, depends on parts of both the basal ganglia and the amygdala, and involves

consumatory behaviors such as eating and drinking. Although there are other types

of Pavlovian conditioning, such as fear conditioning and conditioned avoidance

responses, we will focus on these two.



10.2.1 PAVLOVIAN EYE-BLINK CONDITIONING

The many studies that describe learning-related activity in the cerebellar system

during eye-blink conditioning and related Pavlovian procedures have been well

summarized by Steinmetz.33 The reader is referred to his review for that material.

In addition, a number of studies have shown that cells in the striatum, the principal

input structure of the basal ganglia, show learning-related activity during such

learning. For example, a specific population of neurons within the striatum, known

as tonically active neurons (TANs), have activity that is related in some way to

Pavlovian eye-blink conditioning. At first glance, this result seems curious: Pavlovian

conditioning of this type, which recruits protective reflexes, does not require the

basal ganglia but instead depends on cerebellar mechanisms.33 TANs, which are

believed by many to correspond to the large cholinergic interneurons that constitute

~5% of the striatal cell population,26,35,36 respond to stimuli that are conditioned by

association with either aversive stimuli37,38 or with primary rewards.25–28 TANs also

respond to rewarding stimuli.37,39 However, studies that have recorded from TANs

while monkeys performed instrumental tasks40 tend to report less selectivity for

reinforcers than in the Pavlovian conditioning tasks discussed above,41,42 and it has

been suggested that reward-related responses may reflect the temporal unpredictablility of rewards.37 One current account of the function of TANs is that they serve

to encode the probability that a given stimulus will elicit a behavioral response.

Blazquez et al.38 recorded from striatal neurons in monkeys during either appetitive

or aversive Pavlovian conditioning tasks. In addition to finding that responses to

aversive stimuli (air puffs) and reinforcers (water) can occur within individual TANs,

they also noted that as monkeys learned each association (CS-air puff or CS-water),

more TANs became responsive to the CS. Further analysis of the population

responses of TANs revealed that they were correlated with the probability of occurrence of the conditioned response.

Given that eye-blink conditioning depends on the cerebellum rather than the

striatum,33 why would cells in the striatum reflect the probability of generating a

protective reflex response? The most likely possibility, according to Steinmetz,33 is

that the basal ganglia uses information about the performance of these protective

reflexes in order to incorporate them into ongoing sequences of behavior. Thus,

recognizing the diversity of Pavlovian mechanisms can help us understand the

learning-dependent changes in striatal activity. As is always the case with neurophysiological data, a cell’s activity may be “related” to a behavior for many reasons,

only one of which involves causing that behavior.



Copyright © 2005 CRC Press LLC



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