ideomotor coding: a transcranial magnetic stimulation study · ii ideomotor coding: a transcranial...
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Ideomotor Coding: A Transcranial Magnetic Stimulation Study
by
Connor Reid
A thesis submitted in conformity with the requirements
for the degree of Master of Science
Graduate Department of Exercise Sciences
University of Toronto
Copyright © by Connor Reid 2013
ii
Ideomotor Coding: a transcranial magnetic stimulation study
Connor Reid
Master of Science
Graduate Department of Exercise Science
University of Toronto
2013
Abstract
Ideomotor theory holds that motor plans producing action and the sensory effects of the
actions are cognitively represented in a functionally similar way. The response-effect (R-E)
association is considered bidirectional and automatic in nature. The current research project was
designed to test the hypothesized bidirectional nature of R-E associations by determining if
motor codes were activated following perception of an effect. The automaticity of motor code
activation was investigated via TMS–induced motor evoked potentials (MEPs) following the
presentation an after-effect. To this end, participants completed a training phase in which they
learned a specific R-E association. During the testing phase, the effects were presented prior to
the imperative and TMS stimuli. Behavioural results replicated previous research; participants
preferred to execute the response associated with the presented effect. MEP data, however, did
not support the initial hypothesis. These results are discussed with relation to ideomotor theory
and experimental design.
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Acknowledgments
I would like to thank my supervisor, Dr. Timothy N. Welsh, for his guidance and support
throughout the past two years. I admire and appreciate the enthusiasm with which you approach
the supervisory role, and want to thank you for making this an experience a positive one. I
would like to thank Dr. Luc Tremblay for the significant role he played in shaping my interest in
research during my undergraduate and graduate studies. I would also like to express gratitude to
Dr. Susanne Ferber and Dr. Matthias Niemeier for their helpful comments and suggestions
regarding my thesis.
I would also like to thank Jim and Janis Reid, and Michelle Wood for their support, love and
patience throughout this process. Lastly, I want to thank all of the members of the Action and
Attention Laboratory and the Perceptual-Motor Behaviour Laboratory; especially Gerome
Manson for his help in experimental design, and Kimberley Jovanov for her assistance in data
collection.
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Table of Contents
1 Introduction.................................................................................................................................1
1.1 The ideomotor principle ......................................................................................................2
1.2 Behavioural Evidence for Ideomotor Theory ......................................................................4
1.2.1 A Two-stage Model of Voluntary Action Control ..................................................7
1.3 Cortical Structures Involved in the R-E Associations .......................................................12
1.4 Transcranial Magnetic Stimulation ...................................................................................14
1.5 Cerebral Laterality in Response Planning .........................................................................16
1.6 Experimental Aims and Rationale .....................................................................................17
2 Chapter Two: Experiment 1......................................................................................................20
2.1 Methods .............................................................................................................................20
2.1.1 Participants ............................................................................................................20
2.1.2 Procedure ...............................................................................................................21
2.1.3 Dependent Measures..............................................................................................24
2.2 Data Analysis and Results .................................................................................................25
2.2.1 Reaction Time........................................................................................................26
2.2.2 Response Frequency ..............................................................................................27
2.3 Discussion..........................................................................................................................28
3 Experiment 2.............................................................................................................................29
3.1 Methods .............................................................................................................................31
3.1.1 Participants ............................................................................................................31
3.1.2 Equipment..............................................................................................................32
3.1.3 Procedure ...............................................................................................................32
3.1.4 Dependent Measures..............................................................................................37
3.2 Data Analysis and Results .................................................................................................38
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3.2.1 Reaction Time........................................................................................................39
3.2.2 Response Frequency ..............................................................................................44
3.2.3 Normalized MEPs..................................................................................................45
4 Discussion.................................................................................................................................48
4.1 Behavioural Results ...........................................................................................................49
4.2 Neurophysiological Results ...............................................................................................50
4.2.1 Cortical Structures Involved in the R-E Relationship. ..........................................51
4.2.2 Considerations Related to Stimulated Hemisphere. ..............................................54
4.2.3 Task-Related Considerations .................................................................................55
5 Conclusions...............................................................................................................................57
References .....................................................................................................................................59
Appendices ....................................................................................................................................63
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List of Figures
1.1 A two-stage model of voluntary action control (adapted from Elsner & Hommel, 2001)
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
1.2 Response-effect mapping, and a visual description of valid and invalid trials in
Experiment 1 of Kunde et al., (2002) (adapted from original article). . . . . . . . . . . . . . . 11
2.1 Experimental button board. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
2.2 Schematic of pre- and post-test procedures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . 23
2.3 Mean reaction times separated by time and compatibility. Error bars indicate standard
error of the mean. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .26
2.4 Mean response frequency separated by time and compatibility. Error bars indicate
standard error of the mean. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
3.1 Schematic representation of the vertex of the scalp and the approximate location of
motor cortex (A) (adapted from Conforto et al., 2002). . . . . . . . . . . . . . . . . . . . . . . . . . 35
3.2 Schematic of Experiment 2 pre- and post-test trials. . . . . . . . . . . . . . . . . . . . . . . . . . . . .36
3.3 Mean reaction time separated by StimTime. Error bars indicate standard error of the
mean. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
3.4 Mean reaction time separated by Active Hand and Compatibility. Error bars indicate
standard error of the mean. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
3.5 Mean reaction time separated by Task and StimTime. Error bars indicate standard error
of the mean. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .42
3.6 Mean reaction time separated by Task and Compatibility. Error bars indicate standard
error of the mean. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .43
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3.7 Mean response frequency separated by Time and Compatibility. Error bars indicate
standard error of the mean. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
3.8 Mean MEP separated by StimTime. Error bars indicate standard error of the mean. . . .45
3.9 Mean MEP values separated by Time, Active Hand, and Compatibility. Error bars
indicate standard error of the mean. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
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List of Appendices
Appendix A: Medical history questionnaire ……………………………………………………62
Appendix B: Participant and testing session information ……………………………………....70
Appendix C: Experiment 1 mean values ……………………………………………………….73
Appendix D: Experiment 2 mean values ……………………………………………………….74
1
1 Introduction
Humans are exposed to countless stimuli every day. Although many of these stimuli do not
require a response, others require voluntary action. When a stimulus is identified that requires a
response, the actor must select, prepare, and then execute an appropriate goal-directed
movement. The appropriate response is the one that effectively brings about some desired
outcome. From this perspective, the stages of information processing appear to be very
unidirectional in nature, beginning with the identification of a stimulus that requires action, and
ending with an actor executing a response. The conventional view of information processing is
that stimulus identification, response selection, and response programming are separate stages
which are distinct from one another. This approach also holds that the stages of information
processing are serial in nature, in that one stage cannot begin until the previous stage has been
completed successfully (see Schmidt & Lee, 2011, for a review). This approach has contributed
greatly (and will continue to contribute) to research methods in the field of motor control and
experimental psychology. There are, however, alternative accounts of information processing
which do not subscribe as rigidly to serial processing, but rather suggest that certain stages of
information processing mutually affect one another.
One such alternative account of information processing is known as ideomotor or
common coding theory (e.g., Prinz, 1997). Ideomotor theory suggests that stimuli, responses,
and their associated response outcomes may not simply be sequential components of a series of
processing events, but are rather a group of interdependent processes which are cognitively
represented in a functionally similar way to one another. The main tenet of ideomotor coding is
that the representations of specific movements are tightly bound to the perceptual codes
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representing the effect that the response generates in the environment. The purpose of the
present research was to test this core tenet by examining response selection biases and
neurophysiological measures of motor system activation following the presentation of effects
that have been associated with responses. Before outlining the specific goals and hypotheses of
the experiments in the current study, a review of ideomotor coding and the neurophysiological
technique used in the present study (transcranial magnetic stimulation – TMS) will be presented.
1.1 The ideomotor principle
Authors such as James (1890), Lotze (1852), and Harleß (1861) initially described the
ideomotor concept by suggesting that in order to select and perform a purposeful action, an actor
must first consider the action effect (consequence) he/she wishes to achieve. When an actor
considers an intended action effect, a common code is thought to be activated consisting of
action effect features, and the associated motor program capable of initiating the action itself.
Thus, early ideomotor concepts forwarded the notion that, due to the common coding of actions
and effects, the conceiving of an effect activates the associated motor code that would bring
about that effect.
More recent models (e.g., Elsner & Hommel, 2001; Prinz, 1997) have built upon this
notion and suggest that these common codes are developed through a learning process in which
producing actions results in perceptual feedback (from multiple modalities), and that repeating
these actions strengthens the cognitive association between the action produced, and the
perceptual feedback the actor receives. The end result is that through experience, the planned
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action becomes cognitively associated with its expected perceptual consequences, and that
actors execute actions with the expectation that they will receive this afferent information upon
movement completion (a goal-directed movement). Although these processes were originally
considered over a century ago, the ideomotor approach has been altered and updated, and
remains a topic of current interest.
Notably, Prinz’s (1997) ideomotor or common coding theory provided a concrete
framework to explain the link between perceived events and planned actions. The theory holds
that afferent information provided by environmental stimuli are cognitively represented as event
codes. This information is used to prepare the motor system to mobilize effectors to execute a
response (cognitively represented as action codes). The critical aspect of ideomotor theory is
that although event codes consist of afferent information and action codes consist of efferent
motor plans, they cognitively share a common representational domain. Because of this
common coding system, it is predicted that there is a bidirectional relationship between effects
and actions such that the activation of one code necessarily activates the other code. This
bidirectional activation facilitates accurate and efficient response selection because it: 1) allows
one to activate the appropriate response by conceiving of a desired effect; or 2) one can predict
the outcome of a specific action when a given action code is activated. By way of example, one
can activate the action code for pressing the brake pedal on a car by conceiving of the desire to
slow the car down, and one can predict that the car they are driving will slow down by
activating the action code to press the brake. Critically, it is only through a number of
experiences (e.g., during driving lessons) in which the action generates a specific effect that this
coupling or binding between actions and effects occur.
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1.2 Behavioural Evidence for Ideomotor Theory
Beyond the theoretical details of ideomotor theory, there is growing behavioural
evidence to suggest that actions are cognitively represented in conjunction with their perceptual
consequences. Such behavioural ideomotor research investigates how associations between
actions and their effects are formed, and what factors most influence the formation of these
associations (e.g., Elsner & Hommel, 2001; Greenwald, 1970a, b; Hoffman, Sebald & Stocker,
2001; Hommel, 1996; Kunde, Hoffmann, & Zellmann, 2002; Stock & Hoffmann, 2002). The
following paragraphs contain a review of a selection of the key studies that have provided
behavioural support for the ideomotor notion that when a certain action R (e.g., brake pedal) has
been learned to be associated with action effect E (e.g., car slowing down), the perception of
action effect E prior to the execution of action R increases the speed and probability of action R.
This pattern of behavioural facilitation suggests a strong bidirectional association between
action and effect codes.
Preliminary evidence for the role of effect anticipation in action control was carried out
by Greenwald (1970a, 1970b). Greenwald designed several experiments to investigate the
assumption that anticipation of voluntary action is based upon response-effect (R-E) learning.
Participants responded to auditory or visual stimuli (which were letters or digits) by reproducing
the stimulus by speaking or writing. This research revealed that when the modality of the
stimulus corresponded with the modality of the produced response, reaction times (RTs) were
shorter than when they did not correspond. Specifically, it was found that RTs for written
answers were shorter in response to visual stimuli than auditory stimuli, and that RTs for spoken
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answers were shorter in response to auditory stimuli than visual stimuli. Consistent with
ideomotor theory, facilitation occurred when the modality of the action effects was consistent
with the modality of the imperative stimuli. Greenwald attributed facilitation to the
compatibility between the action, the modality of the effect of the action, and the modality of the
imperative stimulus. For example, the auditory stimulus facilitated verbal RTs because the
auditory stimulus activated the existing bidirectional R-E relationships between sound and
speech, and primed the action (verbal response) relative to when the verbal response was made
to the visual stimulus.
Hommel (1996) provided additional support for ideomotor theory in a novel task
designed to investigate the relationship between actions and their response-contingent events.
This research consisted of a series of experiments, all of which required participants to make
two-choice responses (left and right hand index finger presses of a shift key on a computer
keyboard). Each keypress response was coupled with a unique auditory stimulus. The
characteristics of auditory stimuli varied across experiments; in Experiments 1-2, one tone
played through either a left or right loudspeaker, while in Experiments 3-5, a high-pitched or
low-pitched tone played simultaneously through a left and right loudspeaker (Experiment 3), or
one central loudspeaker (Experiment 4 and 5). These stimuli served as response-contingent
events in that they were presented only after the response was executed. Participants, however,
were informed that the response-contingent auditory stimuli were irrelevant to the task. In all
experiments, participants completed an acquisition phase of 200 practice trials that were
designed to establish a relationship between each response and its respective auditory after-
effect. The specific methods and aims varied in each experiment, but the consistent purpose was
to investigate the coding of actions and their response-contingent events. For example, during
the acquisition phase of Experiment 3, participants pressed a left key (Response 1; R1), in
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response to the appearance of the letter O (Stimulus 1; S1) on a computer screen, or pressed a
right key (Response 2; R2) in response to the appearance of the letter X (Stimulus 2; S2).
Subsequent to a left keypress, a low tone was played (response-contingent action effect, E1, 200
Hz, 100 ms duration), and a right keypress was coupled with the presentation of a high tone
(response-contingent action effect, E2, 500 Hz, 100 ms duration). Thus, during acquisition,
correctly performed trials occurred as follows: S1 R1 + E1, and S2 R2 + E2. In the testing
phase, effect tones were presented simultaneous to the visual imperative stimuli, and
participants were required to respond to the visual stimuli in the same way as they did in the
acquisition block. The execution of the response would result in the immediate playback of its
corresponding effect tone. The key to the studies was that one of two learned effect tones was
randomly played simultaneous to the onset of the visual target. This created two possible
scenarios for each imperative stimulus; trials were said to be either compatible (e.g., S1 + E1
R1 + E1) or incompatible (e.g., S1 + E2 R1 + E1). The experimental hypothesis was that
experience with each R-E mapping would lead to an association between the motor pattern
responsible for executing a response (R1) and the cognitive representation of the response-
contingent action effect (E1). Generally speaking, the experiments revealed that participants had
shorter RTs to initiate a response when pre-cue auditory stimuli were compatible with the
learned key/tone mapping, than when they were incompatible. This research demonstrated: 1)
that task-irrelevant response-contingent auditory stimuli are automatically integrated into
cognitive codes associated with that response; and, 2) due to the bidirectional relationship
between action and effect codes, perceiving a learned action effect activated an associated action
code. These two characteristics of action-effect associations are thought to contribute to the
rapid retrieval of a motor program capable of executing the associated action. What was unclear
from this research, however, was whether the effects of this relationship translate beyond
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perceptual and response initiation efficiencies (as reflected in RT) to affect response selection
and programming.
1.2.1 A Two-stage Model of Voluntary Action Control
Based upon the behavioural evidence suggesting that R-E relationships play a role in the
efficiency of action selection and execution, Elsner and Hommel (2001) suggested a two-stage
model of voluntary action control, operating upon the framework of the ideomotor principle. As
its name suggests (and consistent with earlier thinking), this more formal model is comprised of
two stages. In the first stage, response-effect (R-E) contingencies are learned, and in the second
stage, response selection occurs based upon learned R-E bidirectional associations (Figure 1.1).
Elsner and Hommel (2001) proposed that when a randomly selected motor pattern (R) executed
by the actor results in a specific perceivable change in the environment, this motor program and
specific effect (E) are represented in the cognitive system. Due to the temporal overlap of the
cognitive codes for R and E, they are thought to become associated in such a way that activating
one code automatically activates the other. Thus, according to the two-stage model, after several
co-occurrences of R and E, this association has been established and actors are able to select this
motor program R in order to bring about a desired effect E. That is to say, the actor is able to
select a movement by mentally retrieving the known effects of the selected movement.
Likewise, perceiving effect E in the movement environment automatically primes the motor
program R. As the R-E relationship is thought to be bidirectional in nature, the selection of a
specific response activates the associated effect code, which can be used to predict the outcome
of that response.
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Figure 1.1: A two-stage model of voluntary action control (adapted from Elsner & Hommel, 2001).
Elsner and Hommel (2001) designed a series of experiments to empirically investigate
their two-stage model of voluntary action control. The experimenters adapted the task from
Hommel (1996) into a free-choice task with response selection/programming implications.
Acquisition trials were similar to that of Hommel (1996), except that there was a single
imperative stimulus (a white rectangle on a computer screen). Upon presentation of the
stimulus, participants were free to choose one of two keypresses. Each keypress (i.e., left or
right) triggered a unique auditory tone lasting 200 ms (i.e., high [800 Hz] or low tone [400 Hz];
symbolically - S R1 + E1 or S R2 + E2). Participants were free to choose and press either
key on each trial, and were asked to execute, as much as possible, a balanced ratio of left and
right responses over 200 acquisition trials. The test phase was similar to acquisition, except that
one of two effect tones was randomly played as the imperative stimulus. Participants were still
free to choose either response on any given trial, and were no longer required to mind a
balanced response ratio. Thus, in the test phase, participants produced either ‘acquisition-
consistent choices’ (e.g., E1 R1 + E1) or ‘acquisition-inconsistent choices’ (e.g., E1 R2 +
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E2). Recall that the critical dependent variable in Hommel (1996) was RT. Instead of evaluating
RT, Elsner and Hommel (2001) focused on response frequency in the test phase as the index of
preference for compatible or incompatible responses. This index of preference (or response
bias) was thought to reflect the activation of action codes via presentation of the effect. Overall,
the results indicated that participants preferred to execute responses which were consistent with
the learned R-E mapping during acquisition phases (e.g., Experiment 3A: 63.8% acquisition-
consistent, 36.2% acquisition-inconsistent; Experiment 3B: 60.1% acquisition-consistent, 39.9%
acquisition-inconsistent). This finding extended the known RT effect (e.g., Hommel, 1996) to
include implications in response selection. Together, these data are consistent with the notion
that R-E relationships are automatically activated upon the presentation of a learned action
effect, and that they have implications for response programming/selection.
Although the aforementioned research provided critical behavioural demonstrations of
the association between action and effect codes, it does not demonstrate this relationship when
effect codes are not perceptually available prior to response selection. In the critical condition of
Hommel (1996) and Elsner and Hommel (2001), one of two auditory effect tones E1/E2,
associated with one of two actions (R1/R2), would be presented prior or simultaneous to the ‘go’
signal. Kunde et al. (2002) argued that it was necessary to show R-E relationships during action
planning without effect codes being perceptually available (i.e., presenting (E1/E2) prior to the
execution of R1/R2). To this end, the researchers designed three experiments to examine the
action/effect relationship in a unique task, where effect codes were not perceptually available
prior to response selection. The task required participants to execute one of four key presses
(Figure 1.2), where pressing keys one and three immediately resulted in the playback of a low-
pitched tone (250 Hz, 600 ms duration), and pressing keys two and four were paired with a
high-pitched tone (650 Hz, 600 ms duration). The digits 1-4 and the colours red, yellow, blue,
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and green were both mapped to four keys in left-to-right order. In the first experiment, a
response cue (a number between 1-4, representing keypresses) was presented in the center of a
computer screen. Participants were instructed to prepare (but not execute) the keypress that
corresponded to the cue. The cue remained on the screen for 1500 ms, at which point a second
cue (one of four colours) was presented to participants that required an immediate response.
Immediately after the key press response had been completed, its corresponding auditory after-
effect would play. Critical trials occurred when the cue was invalid (that is, the prepared
response (e.g., the first cue was “3”) was not congruent with the produced response (e.g., the
second cue was red [key “1”], yellow [key “2”], or green ([key “4”]). On these invalid trials, the
second cue could indicate a response whose auditory effect either corresponded with (e.g., red)
or did not correspond with (e.g., yellow or green) the effect produced by the initially cued
response (e.g., “3”). The experimental prediction, termed the collateral facilitation hypothesis,
was that preparation of one motor program (corresponding to an auditory action effect) would
facilitate the execution of another response that shared the auditory action effect of the prepared
response. For example, if key 3 (mapped with a low-pitched tone) was initially cued, and the
second stimulus required a key 1 response (also mapped with a low-pitched tone), the authors
expected to see shorter RTs than if the second stimulus corresponded with a high-pitched effect
tone (the effect for keys “2” and “4”). This effect was confirmed in the second half of
Experiment 1 (after participants had learned the association between stimuli) in that RTs were
faster for corresponding invalid trials, than non-corresponding invalid trials.
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Figure 1.2: Response-effect mapping, and a visual description of valid and invalid trials in Experiment 1 of Kunde et al., (2002) (diagram adapted from original article).
In Experiment two, participants were presented with a stimulus S1, and were required to
prepare (but not execute) a corresponding response R1. Before they executed this action, another
stimulus S2 was presented, which was to be immediately responded to, followed by the
execution of the originally prepared action R1. The collateral facilitation hypothesis was also
demonstrated in this task, in that an action R2 was initiated with significantly shorter RTs when
the originally prepared action R1 corresponded with the same auditory effect as action R2.
Experiment 3 replicated these findings with a more complex, pen transport task.
Taken together, the behavioural research reviewed here supports ideomotor theory in
that it suggests an important role of action effects in the cognitive retrieval and selection of
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motor codes. Specifically, learned R-E associations (e.g., when a certain action R1 has been
learned to be associated with action effect E1) increase the efficiency (shorter RTs - Greenwald,
1970a, b; Hommel, 1996; Kunde et al., 2002) and probability (response frequency - Elsner &
Hommel, 2001) of initiating action R1, when its corresponding effect E1 is perceived prior to the
execution of action R1. These patterns of behavioural facilitation provide strong evidence in
support of the strong bi-directional association between action and effect codes predicted by
ideomotor theory.
1.3 Cortical Structures Involved in the R-E Associations
Evidence suggesting that action effects influence the selection and execution of
responses is growing. What is less clear, however, are the neural substrates of this relationship.
A large amount of work on this topic has been compiled on musical tasks. Skilled musicians are
an appropriate population to use when investigating R-E associations, as their practice is
comprised of pressing keys (or combinations of keys), each of which is associated with a unique
auditory effect tone. For example, Drost, Reiger, Brass, Gunter, and Prinz (2005) demonstrated
that expert pianists were slower (in terms of RT) to execute responses when pre-cue tones were
incongruent with the chord to be played. This data is consistent with the ideomotor notion that
perception of effects and executing actions are cognitively represented in a functionally similar
manner, and that the R-E association is bidirectional in nature.
Neurophysiological research with musical populations suggests that the frontoparietal
motor-related network may play a role in R-E associations. Evidence suggests that this common
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network is comprised of an area related to action, including premotor cortex, and dorsolateral
and inferior frontal cortex areas, as well as a strip related to perception, including the superior
temporal gyrus and supramarginal gyrus (Bangert & Altenmuller, 2003; Bangert et al., 2006;
Lotze, Scheler, Tan, Braun, & Birbaumer, 2003; Meister et al., 2004). These regions have also
been implicated in perception of visual effect codes, where presenting learned action effects
leads to premotor cortex activity when observing other actors (Calvo-Merino, Glaser, Grezes,
Passingham & Haggard, 2005; Tai, Scherfler, Brooks, Sawamoto, & Castiello, 2004).
Non-expert musicians have also been examined via fMRI while they acquire R-E
associations between pressing keys and receiving auditory feedback through experience. Lahav,
Saltzman, and Schlaug (2007) had non-musicians learn a piano piece during an acquisition
phase, followed by a test phase where participants were required to passively monitor a variety
of tone sequences. Some of the tone sequences were novel, but the critical trials were those in
which part of the piece they had learned in the acquisition phase was replayed. Consistent with
the notion that the R-E associations involve the motor system, fMRI results demonstrated
activation in the frontoparietal motor-related network when participants listened to sequences
consistent with those that they learned in the acquisition phase. Specifically, activation was
found in Broca’s area, the premotor region, the intraparietal sulcus, and the inferior parietal
region.
Taken together, this research suggests that R-E associations involve the motor system
and related perceptual and cognitive areas. What has yet to be demonstrated, however, is more
direct evidence that perception of a learned action effect automatically primes the motor code
associated with that action in the motor system (and specifically in primary motor cortex [M1]).
To address this issue, the current research project will use transcranial magnetic stimulation
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(TMS) to probe the excitability of the nervous system at the effector level, subsequent to the
presentation of a learned action effect.
1.4 Transcranial Magnetic Stimulation
TMS is a safe, non-painful, and non-invasive method of stimulating the cerebral cortex.
When TMS is applied over an area of motor cortex which corresponds to a specific area of the
motor homunculus, muscular contractions can be elicited (a technique first demonstrated by
Barker, Jalinous, & Freeston, 1985). By analyzing the characteristics of selectively elicited
muscular contractions, one can gain insight into the excitability of the corticospinal tract.
A modern TMS unit consists of a magnetic stimulator and an electrical capacitor. Its
operation and function is based upon Faraday’s Law, and the related principle of
electromagnetic induction. The electrical capacitor stores and delivers a large amount of
electrical current to the magnetic stimulator (consisting of a coil of wire that is connected to the
electrical capacitor - Maeda & Pascual-Leone, 2003; Rothwell, 1997). The brief electrical
current induces an equally brief magnetic field in the volume surrounding the coil. This transient
magnetic field can induce an electrical current in any nearby electro-conductive medium. If the
induced magnetic field is close enough to the brain, the field induces an electrical current in the
extracellular fluid of the brain which, if it is of sufficient magnitude, can generate action
potentials in nearby neurons. When M1 is stimulated, the change in electrical potential can
activate the cortical interneurons which synapse to the descending pyramidal neurons. When
enough of the neurons are activated, the descending action potentials can activate the alpha-
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motorneurons and cause a brief muscle contraction. In typical TMS research where M1 is
stimulated, surface electromyographic (EMG) electrodes are placed on the skin to monitor
electrical activity in the effector muscles of interest and record the induced muscle contraction
(Wasserman, 1997). The induced contraction is termed the motor evoked potential (MEP).
When the amount of stimulation is kept constant, the amplitude of the MEPs is an indicator of
corticospinal excitability (Maeda & Pascual-Leone, 2003). The amplitude of the MEP is
typically calculated as the difference in voltage between the largest negative and positive peaks.
Larger amplitude MEPs for a given level of stimulation are thought to reflect an increase in
corticospinal excitability, while relatively smaller amplitude MEPs for a given level of
stimulation are thought to reflect decreased excitability or inhibition.
Although TMS has many potential diagnostic and therapeutic uses, the current research
project used TMS as an investigative tool. Specifically, TMS was used as an indicator of
corticospinal excitability while participants perform an experimental task. As a methodological
example, Fadiga, Fogassi, Pavesi, and Rizzolatti (1995) used TMS to elicit MEPs in this manner
to determine if the observation of another person’s response activates the motor system in a
response/muscle specific manner. This study was based on research with monkeys suggesting
that a subset of neurons in motor area F5 becomes active similarly when the monkey executes
goal-directed movements and when it observes similar movements (di Pellegrino, Fadiga,
Fogassi, Gallese & Rizzolatti, 1992). To determine whether a similar phenomenon occurs in
humans while avoiding the invasive procedures of primate studies, Fadiga et al. monitored
TMS-induced MEPs in the hand muscles of human participants while the participants: 1)
observed an experimenter grasping 3-D objects; 2) simply looked at the same 3-D objects; 3)
observed an experimenter tracing geometrical figures in the air; or, 4) detected the dimming of a
light. Fadiga et al. found that MEP amplitudes were highest in the condition where participants
16
observed an experimenter grasping 3-D objects. The authors suggested that this increase in
MEP amplitude indicated that the excitability of the motor system increases when humans
observe a goal-directed action performed by another individual. The method used by Fadiga et
al. of recording and analyzing TMS-induced MEPs as an index of motor system excitability
while participants perform an experimental task was adapted for use in the current research
project.
1.5 Cerebral Laterality in Response Planning
The areas that contribute to motor planning and control are spread throughout each
hemisphere, and the two cerebral hemispheres seem to contribute different aspects to the motor
plan. For the typical right-handed individual, the data suggest that the left hemisphere plays a
critical role in planning the timing and amplitude of muscle contractions, and the right
hemisphere plays a dominant role in organizing the spatial components of the action (see Elliott
& Roy, 1996; Sainburg, 2010 for reviews). Due to its dominant role in planning muscle
contractions, it is generally accepted that response planning typically involves the left
hemisphere regardless of which limb is involved. This conclusion is based on a series of
neurophysiological (e.g., Frey, 2008; Haaland et al., 2000; Janssen et al., 2011; Johnson-Frey et
al., 2004; Kim et al., 1993) and behavioural studies (see Elliott & Roy, 1996; Sainburg, 2010 for
reviews). For example, Johnson-Frey et al. (2004) reported findings from fMRI studies of right-
handed adults examining the cortical structures involved in planning (defined by the authors as
identifying, retrieving, and preparing actions with commonly used tools), verses executing tool
actions using either the dominant or non-dominant hand. Regardless of the limb in question,
17
planning to use a tool activated a left hemisphere network, composed of: the posterior superior
temporal sulcus, proximal middle and superior temporal gyri, inferior frontal and ventral
premotor cortices, anterior and posterior supramarginal gyri, angular gyrus, and prefrontal
cortex.
Further, results from studies of intermanual transfer of learning (in which participants
learn a sequence of movements with one hand and then perform it with the other hand) indicate
that there is greater transfer of learning when the participant learns the task with their left hand
and then performs it with the right hand, then vice versa (e.g., Taylor & Heilman, 1980). This
greater left-to-right than right-to-left transfer is thought to occur because the left-hemisphere is
involved in the planning of actions for the left hand and, hence, “learns” the motor task even
though the right hand is at rest during acquisition. On the contrary, the right hemisphere is not
involved during the planning and execution of right-handed movements and, hence, the right-
hemisphere/left-hand system does not benefit as much from the training of the right hand.
Overall, the data suggest that the left hemisphere plays an important role in the planning and
learning of movements for both hands. As will be made clearer below, this apparent laterality in
function influenced the location of stimulation in the current research project.
1.6 Experimental Aims and Rationale
The main purpose of the current research project was to use TMS to investigate whether
the perception of a learned after-effect automatically results in the retrieval of its associated
motor code. The underlying hypothesis was that if the after-effect automatically retrieves the
18
motor code, the representation of that motor code in M1 should increase in excitability. Thus,
the automatic retrieval of the motor codes should be reflected by the presence of higher TMS-
induced MEP amplitudes following the presentation of the tone associated with that response
than when a tone associated with a different response is presented.
This project consisted of two experiments. In Experiment 1, participants completed a
task similar to the free-choice button task in Elsner and Hommel (2001). The purpose of this
experiment was to validate the task used in the main experiment by replicating the findings of
Elsner and Hommel (2001). Recall that Elsner and Hommel (2001) reported that, subsequent to
an acquisition phase designed to associate specific R-E (i.e., button-tone) mappings, participants
had a preference to interact with compatible over incompatible buttons following the
presentation of one of the tones. The authors argued that this response selection preference
occurred because the presentation of a specific tone activated the motor code associated with
that tone, biasing the participant to select and execute that response. Experiment 1 was
conducted to ensure that a similar protocol could generate the same pattern of effects before it
was adapted for use in the TMS study.
Experiment 2 (the critical new experiment) involved an adaptation of the free-choice
button press task in Experiment 1 to include a single TMS pulse on each test trial. TMS-induced
MEPs of an effector muscle served as an indicator of corticospinal excitability following the
presentation of effect codes. Based on ideomotor theory’s prediction that common coding
underlies motor planning, and the resulting perception of an after-effect evokes a representation
of its associated action in the motor system (e.g., Elsner & Hommel, 2001; Hommel, 1996;
Kunde et al., 2002), it was predicted that the cognitive retrieval of an effect-evoked response
code should not only be apparent behaviourally (reflected in response selection biases), but also
19
neurophysiologically (reflected in MEP amplitudes). Thus, the main experimental hypothesis
was that MEP amplitudes should be higher than baseline when the effect tone presented prior to
TMS was compatible with the learned R-E relationship for the stimulated muscle, compared to
when the presented effect tone is associated with the contraction of a different muscle. Similar
to the biases in response selection, these differences in MEP amplitude should only be present
after the participant has completed an acquisition phase in which he/she has learned to associate
a response with a specific effect (i.e., the tone should not affect amplitudes in the pre-acquisition
test, but should affect MEP amplitudes in the post-acquisition test). However, if common
coding has a more limited role in motor behaviour, or if after-effect perception does not evoke
response codes, then the presentation of effects should not influence the activity of the motor
system. Also, given that TMS will be directly applied to the hand area of M1 in this experiment,
absence of an MEP effect may also suggest that the R-E relationship is not exclusively localized
to M1, but may be represented in other areas in the brain.
20
2 Chapter Two: Experiment 1
As mentioned above, an initial experiment was conducted without TMS to ensure that
the task used in the main experiment was capable of replicating the results of Elsner and
Hommel (2001). Recall that the dependent variable of interest in the free-choice tasks of Elsner
and Hommel (2001) was response frequency - contrary to previous studies which focused on
RT. To this end, participants completed a free-choice button press task before and after an
acquisition phase designed to establish a link between each response and its associated auditory
action effect. In pre- and post-test tasks, participants were presented with one of two previously
learned action effects prior to the imperative stimulus. The experimental prediction was that
participants in the post-test task would prefer to interact with the button whose learned after-
effect was compatible with the pre-cue auditory stimulus.
2.1 Methods
2.1.1 Participants
Nine volunteers (5 male) from the University of Toronto participated in the experiment.
Testing sessions lasted approximately 30 minutes, and subjects were compensated $5 CAD for
their time. All participants were right handed, and between the ages of 18 and 28 years (M=23;
SD=2.4). Prior to their involvement, participants were provided with a written explanation of
the experiment, and were asked to provide written consent to the procedures. All procedures
21
were approved by the Ethics Review Board at the University of Toronto and complied with the
ethical standards of the 1964 Declaration of Helsinki regarding the treatment of human
participants in research.
2.1.2 Procedure
All experimental stimuli and data recording were controlled by a custom E-Prime
program run on a Dell PC. Participants responded to visual stimuli on a computer monitor (Dell:
REV A00) and provided their responses on a custom built button board situated in front of them
(Figure 2.1). During all experimental trials, participants were seated comfortably in a chair in
front of a computer monitor with their palms facing down, resting on a button board, and their
left and right index fingers positioned 2 cm lateral of their respective buttons. Participants
completed three separate blocks; a pre- and a post-test, which were separated by an acquisition
block.
Figure 2.1: Experimental button board.
22
In the pre-test block, trials began with a white fixation cross appearing in the center of a
computer monitor over a black background for 1000 ms (Figure 2.2). At the end of the fixation
phase, the white cross disappeared and after a brief delay (100 ms) one of three pre-cue tones
were presented for 600 ms (consistent with Kunde et al. 2002); a low tone (200 Hz), a high tone
(800 Hz), or white noise. Low and high tones indicated that participants were required to
execute an action on that trial, whereas white noise indicated a ‘no-go trial’. Following the
presentation of the auditory stimulus, a white square appeared in the middle of the screen
(consistent with Elsner and Hommel, 2001). Participants were instructed to press one of the
buttons by lifting and abducting their either their left or right index finger 2 cm to execute a
button press as quickly as possible. Consistent with Elsner and Hommel (2001), participants
were free to choose either a left or right hand keypress on any given trial, and were told that
auditory tones were irrelevant to the task. Participants were instructed to respond as quickly and
as spontaneously as possible and were advised that exclusively pressing one key was not
acceptable. On all trials, button contact resulted in the disappearance of the white square, and
the screen turned black, indicating the end of the trial. There was a 1000 ms inter-trial interval.
Each of the three pre-cue tones were played on 14 trials, resulting in a total of 42 pre-test trials.
23
Figure 2.2: Schematic of pre and post-test procedures
The acquisition task followed the same general procedure as the pre-test task, with a few
differences. First, there was no pre-cue tone. The trial sequence simply progressed from a
fixation cross (1000 ms), to a black screen (1000 ms), to the imperative stimulus (a white
24
square). Second, pressing either button resulted in the immediate playback of one of two
auditory stimuli (600 ms duration) via two computer speakers (simultaneous playback through
both speakers). Pressing the left button resulted in a high-pitched tone (800 Hz), whereas the
right button resulted in a low-pitched tone (200 Hz). Participants completed 200 trials, and
although they were free to choose either button on any given trial, they were instructed to
maintain a goal of pressing each button an equal number of times. This procedure is similar to
Elsner and Hommel (2001) and has been shown to produce R-E associations.
The post-test task was identical to the pre-test task, except for one difference.
Immediately upon button contact, the corresponding auditory tones that were learned in the
acquisition block were played (lasting 600 ms). The effect tones were played upon button press
during the post-test to ensure that any R-E associations established during acquisition were
maintained. Thus, compatible trials were said to be trials where the participant pressed the
button which corresponded to the initial ‘go/no-go’ tone (e.g., high pre-cue tone, followed by a
left button press, causing a high tone to play), whereas incompatible trials occurred when the
participant chose the opposite response (e.g., high pre-cue tone, followed by a right button press,
causing a low tone). Notably, response-contingent auditory tones remained dependent upon the
keypress, as in acquisition. Each pre-cue tone was played on 14 trials, resulting in a total of 42
pre-test trials.
2.1.3 Dependent Measures
Two main dependent measures were collected and analyzed; reaction time (RT) and
response frequency (RESP). RT was defined as the time between visual stimulus onset (white
25
square) and button press. RESP was defined as the percentage of trials on which a participant
interacted with compatible or incompatible buttons.
2.2 Data Analysis and Results
Temporal, but not location, data for trials with RT values larger than two standard
deviations from each participant’s mean (outliers) or shorter than 100 ms (anticipations) were
removed from the data. Trials were also deleted when participants moved in the ‘no-go’
condition, or failed to respond at all. These criteria resulted in removal of 1-14% of trials per
participant and 5% of total experimental trials. RT and RESP data were submitted to separate 2
(Task: pre-test, post-test) by 2 (Compatibility: compatible, incompatible) repeated measures
ANOVAs. Mauchly’s test was performed to ensure sphericity of the data, but there were no
violations of the assumption of sphericity. The nature of any significant results involving three
or more means was determined using a Tukey’s HSD post-hoc test. Alpha was set to p<.05 for
all tests.
26
2.2.1 Reaction Time
Regarding RT, the analysis revealed a significant main effect of Compatibility, F(1,
8)=13.33, p<.01. Post-hoc testing revealed that participants had shorter RTs when interacting
with compatible targets (M=348 ms; SD=79.3) than to incompatible targets (M=378 ms;
SD=76.8). Although there was no main effect of Task, F(1, 8)=1.11, p>0.1, the interaction
between Task and Compatibility approached significance, F(1, 8)=4.88, p=.058 (see Figure 2.3).
Figure 2.3: Mean reaction times separated by time and compatibility. Error bars indicate standard error of the mean.
27
2.2.2 Response Frequency
The RESP analysis did not reveal significant main effects of Time, F(1, 8)=1.00, p>0.1,
or Compatibility, F(1, 8)=3.23, p>0.1. More theoretically relevant to the experimental
hypothesis, however, the analysis revealed a significant interaction between Task and
Compatibility, F(1, 8)=6.91, p<.05 (Figure 2.4). Post-hoc analysis of this interaction revealed
that there was no difference between compatible (M=49%; SD=1) and incompatible (M=51%;
SD=1) trials in the pre-test, however participants preferred to respond to compatible targets
(M=63%; SD=19.4) over incompatible targets (M=37%; SD=19.4) in the post-test.
Interestingly, the magnitude of the differences found here were similar to those reported by
Elsner and Hommel (2001).
Figure 2.4: Mean response frequency separated by time and compatibility. Error bars indicate standard error of the mean.
*Denotes significance at the p<.05 level
28
2.3 Discussion
Experiment 1 was designed to evaluate the validity of the present experimental design
with respect to that of the original free-choice R-E design in Elsner and Hommel (2001). The
main finding was that, in the post-test task, participants preferred to interact with buttons which
were consistent with R-E mappings learned during the preceding acquisition block. This finding
is consistent with the literature in that 200 acquisition trials are typically sufficient for actors to
establish an R-E association between button presses and their contingent auditory tones, which
is reflected in response selection biases.
29
3 Experiment 2
Because Experiment 1 demonstrated participants’ preference for compatible targets after
200 acquisition trials, a second study was designed to investigate the potential
neurophysiological bases of this action-effect relationship. Experiment 2 employed a similar
paradigm to Experiment 1 with the addition of a single TMS pulse on each pre-and post-test trial.
According to ideomotor theory’s prediction that common coding underlies motor planning and
that the perception of an after-effect evokes a representation of its associated action in the motor
system (e.g., Hommel, 1996; Elsner & Hommel, 2001; Kunde et al., 2002), it was anticipated
that the cognitive retrieval of an effect evoked response code should not only be apparent
behaviourally (as evidenced in response selection biases), but also neurophysiologically.
Specifically, it was expected that MEP amplitudes would indicate increased excitability when the
effect tone was compatible with the learned R-E relationship for the stimulated hand than when it
was incompatible with the learned R-E relationship for the stimulated hand.
To this end, single pulse TMS was provided to the area of the right M1 that represents the
first dorsal interosseous (FDI) muscle of the left hand. TMS was provided after the presentation
of effect tones. As in Experiment 1, participants learned to associate the generation of high tones
with depression of the left button and low tones with depression of the right button. To press the
button, participants had to lift and then abduct the index finger which required activation of the
FDI. Hence, it was predicted that activation of left and right FDI would be part of the motor code
that would be associated with high and low tones, respectively. MEPs in the left FDI were
evoked during the time window after the presentation of the tone, but before the presentation of
the visual imperative stimulus. During this time, participants should be selecting and planning
30
their upcoming response, but should still be at rest. If perception of the effect activates the motor
codes of the action that brings about that effect in the M1, then the high tone should activate
(increase the excitability) of the M1 representation of left FDI in the right hemisphere. The
presentation of the low tone should not influence the activation of the M1 representation of left
FDI because it is associated with a right hand response (which is represented in the left
hemisphere). If presentation of the high tone activates the cortical representation of left FDI in
M1, then MEPs recorded from the left FDI should be of greater amplitude when the high tone is
presented prior to the TMS pulse than when the low tone is presented prior to the TMS pulse (a
within-left-hand difference between MEPs on compatible and incompatible trials). Critically,
this difference should only be present in the post-test task (i.e., only after the acquisition phase in
which the R-E association has been developed). Alternatively, if the effect tone does not activate
the representation of the action in M1 (perhaps because the associations are represented upstream
from M1), then there will be no differences in MEP amplitudes following the presentation of low
and high tones.
Note that the right-hemisphere/left-hand system was chosen for stimulation because of
concerns over the confounding role the left hemisphere plays in programming actions for both
hands. That is, even though the left hemisphere should become most active following the
presentation of the low tone, it could be that the left hemisphere becomes active following both
low and high tones because of its role in planning movements for both limbs in right-handed
people. For this reason, it was thought that a more sensitive index of cortical activation
following presentation of the effect tone would be to test the right hemisphere, which would be
more isolated from the influences of both of the effect tones and/or the general planning process.
31
As an additional testing of the ideomotor coding and the timecourse of response
activation, TMS was provided at 3 time points prior to the imperative stimulus. The three time
points were: 0 ms, 150 ms, and 300 ms after the offset of the 600 ms effect tone (the 300 ms
condition was also simultaneous to the imperative visual stimulus). It was expected that
stimulation at 0 ms may be too early for activation of motor codes to be present, but that there
could be increases in excitability (and larger MEPs) at the 150 ms and 300 ms stimulation times.
3.1 Methods
3.1.1 Participants
Eleven different volunteers (5 male) from the University of Toronto, that did not take part
in Experiment 1, participated in Experiment 2. Testing sessions lasted approximately one hour
and 30 minutes. Participants were compensated $15 CAD for their time. All participants were
right handed, and between the ages of 21 to 28 years (M=24; SD=2.7). Prior to their
involvement, participants were provided with a written explanation of the experiment, and were
asked to provide written consent to the procedures. All procedures were approved by the Ethics
Review Office at the University of Toronto and complied with the ethical standards of the 1964
Declaration of Helsinki regarding the treatment of human participants in research. To ensure that
the use of TMS was not contraindicated, participants completed a medical history questionnaire
(Appendix A) and a mental health questionnaire (Appendix B) prior to their involvement in the
study. Among other things, these questionnaires investigated whether he or she (1) wore a
pacemaker, spinal/bladder stimulator, or acoustic device; (2) had any neurosurgical procedures
32
with large craniotomies; (3) had any other intracranial metallic components; (4) had a history of
seizure; or (5) was taking any medication that may affect the excitability of their nervous system
(i.e., antispastics, anxiolytics, hypnotics, antiepileptics, etc.) (Rossini, Barker, Berardelli,
Caramia, Caruso, Cracco, et al., 1994).
3.1.2 Equipment
The TMS system was a single pulse monophasic stimulator (Magstim 200) with a figure-
8 coil with an internal diameter of 70 mm. An image-guided TMS system (Rogue Research,
Montreal, QC; Brainsight 2) was used to locate cortical landmarks and ensure that TMS pulses
were delivered to the same location on each trial. EMG data from the left FDI of the index finger
was recorded from surface electrodes (Rogue Research, Montreal, QC). All experimental stimuli
and response data were controlled and recorded by a custom E-Prime program on a Dell PC.
EMG was recorded by the Brainsight system (3000 Hz) for a 200 ms period that began 50 ms
prior to the TMS pulse and ended 150 ms after the TMS pulse. These data were stored for offline
analysis using Brainsight system software. Participants perceived stimuli on a computer monitor
(Dell; REV A00) and provided their responses on a keyboard situated at a comfortable arms
reach in front of them, so that they could rest their elbows on the armrests of the chair (Rogue
Research, Montreal, QC; Generation 3 TMS chair).
3.1.3 Procedure
33
During all experimental trials, participants were seated comfortably in a chair in front of
a computer monitor with their palms facing down, resting on a keyboard. Although not
necessarily theoretically relevant, it is worth noting that Experiment 2 was completed using
button presses on a keyboard, rather than a custom button board (as was used in Experiment 1).
Participants’ left and right index fingers were positioned on their respective home positions; the
letter ‘z’ (left hand; target was the letter ‘c’) and the number ‘3’ (right hand, number pad; target
was the number ‘1’). Participants completed four separate blocks; an initial mapping phase, a
pre-test block, an acquisition block, and a post-test block.
During the mapping phase, the experimenters used the TMS and Brainsight 2 systems to
identify the participants’ scalp position over the right motor cortex at which the largest MEP
amplitude was evoked in the FDI of the left hand index finger following a TMS pulse. To locate
the hand motor area, a standard procedure was carried out for all participants (Conforto,
Graggen, Kohl, Rosler & Kaelin-Lang, 2004; Mills & Nithi, 1997). Throughout this procedure,
participants were seated comfortably in a chair, with their arms and hands as relaxed as possible,
resting on the armrest of the chair. The electrodes were placed on the left FDI, and a ground was
positioned on the distal aspect of the ulna. After the electrodes were fixed to the skin, the
participant’s head was registered to the default brain map of the Brainsight system using the
anatomical landmarks of the nasion, the tip of the nose, and the edge of each ear.
In the first step of the mapping, the vertex of the scalp was determined by marking (with
non-permanent marker) the intersection of the naison-inion line and the interaural line (Figure
3.1). Next, a mark was made 5 cm to the left of the vertex along the interaural line, representing
the approximate location of the right motor cortex.
34
Figure 3.1: Schematic representation of the vertex of the scalp and the approximate location of motor cortex (A) (adapted from Conforto et al., 2002).
The coil was oriented 45 degrees to the body midline, and tangential to the scalp in order
to facilitate posterior to anterior flow of the electric current along the primary motor strip. The
experimenter initially placed the TMS coil over point A (Figure 3.1), and continued to move the
coil over the scalp in 1 cm steps until an observable MEP was elicited in the left FDI. As
necessary, stimulus intensity was increased in 5% intervals until an MEP was observed. The
resting motor threshold (rMT) was defined as the minimum stimulus intensity which evoked five
of ten MEPs of at least 50 µV (peak-to-peak) from the left FDI (Rossini et al., 1994). Once the
rMT was identified, the experimenter dropped a virtual target on the scalp of the virtual brain
map using the Brainsight 2 software. This virtual target acted as the reference point to which the
experimenter oriented the TMS coil for the duration of the experiment. Experimental stimulus
35
intensity was 120% of rMT, resulting in an average of intensity of 55% (± 7.9 SD) of the
maximal capacity of the TMS unit across participants.
The acquisition task was identical to Experiment 1, except that responses were made on a
keyboard rather than a button board. The pre- and post-test tasks were identical to the procedure
in Experiment 1, with two changes. First, each trial was initiated by an experimenter mouse
click, replacing the consistent one second intertrial interval in Experiment 1. This change was
implemented so that the experimenter could ensure that the participant was prepared for the
upcoming trial, which would include TMS. This experimenter-initiated trial procedure also
allowed the participant to take a break at any time if they needed a break from TMS (though no
participants took this break within a block). Second, each trial included a single TMS pulse at the
specified testing stimulus intensity determined in the mapping procedure for each participant. On
each trial, this pulse occurred at 0 ms, 150 ms, or 300 ms after the offset of the presentation of
the pre-cue tone. To ensure consistent temporal order of events (i.e., time between pre-cue tone
and onset of visual stimulus), auditory stimuli in the 0 ms condition were followed by a 300 ms
wait period, and in the 150 ms condition a 150 ms wait period before the appearance of the
visual stimuli (white square). Thus, there were three TMS presentation times (0, 150, 300 ms),
and three pre-cue tones (high tone, low tone, white noise), resulting in 9 conditions. Similar to
Experiment 1, the only difference between pre- and post-test procedures was that in the post-test,
each keypress was coupled with its associated auditory after-effect to maintain any R-E
association established during acquisition (Figure 3.2). Participants completed 14 trials in each
condition; a total of 126 total pre- and post-test trials.
36
Figure 3.2: Schematic of Experiment 2 pre- and post-trials.
37
3.1.4 Dependent Measures
Three dependent measures were collected and analyzed; normalized peak-to-peak MEP
amplitudes (MEP), reaction time (RT) response frequency (RESP) to compatible and
incompatible targets. Consistent with Experiment 1, RT was defined as the time between visual
stimulus onset (white square) and button press, and RESP was defined as the percentage of
responses participants executed following compatible and incompatible tones. MEP amplitudes
were recorded as the absolute µV difference between the highest positive and lowest negative
voltage recorded. MEP values were normalized for each participant and condition by dividing
mean values in each condition by the average peak-to-peak MEP amplitude in the control (white
noise, neutral tone) condition because this was a “no-go” rest trial and, hence, there should be no
change in corticospinal activation on these trials. This procedure was completed separately for
pre- and post-test values for each participant. As an example, if a participant had a raw peak-to-
peak MEP amplitude of 1150 µV in the pre-test compatible, left hand (response), 0 ms StimTime
condition, and had an average peak-to-peak amplitude in the control (white noise) condition of
900 µV, their normalized MEP value would be 1.28. Normalized MEP values above 1 (one)
indicate increased corticospinal excitability compared to baseline, whereas values below one
suggest decreased excitability or inhibition relative to baseline. Using the white noise/no-go
trials as the baseline helped to control for such factors as the effect of a tone alone, time from
tone, and time to the visual stimulus on corticospinal excitability.
38
3.2 Data Analysis and Results
Temporal, but not location, data for trials with RT values larger than two standard
deviations from each participant’s mean (outliers) or shorter than 100 ms (anticipations) were
removed from the data. Trials were also deleted when participants moved in the ‘no-go’
condition, or failed to respond at all. These criteria resulted in removal of 2-15% of trials per
participant and 10% of total experimental trials. It should be noted that one participant did not
make any post-test incompatible responses with their right hand at the 0 ms StimTime. For this
reason, this participant did not have RT or MEP values for this condition. Absent RT and MEP
values for this participant were substituted with the mean value for that specific condition from
the other participants. This substitution allowed the participant to be included in all analyses.
Regarding RESP, this issue did not require adjustment; the participant simply chose to execute
0% of their responses in this condition. To ensure that this procedure did not bias the results of
the experiment, all analyses were competed both with and without the added values from the
participant in question. The overall pattern of results was not meaningfully altered by
substituting RT and MEP values.
RT, RESP, and MEP data were submitted to separate 2 (Task: pre-test, post-Test) by 2
(Compatibility: compatible, incompatible) by 2 (Active Hand: left, right) by 3 (StimTime: 0 ms,
150 ms, 300 ms) repeated measures ANOVAs. Note that the factor Active Hand refers to the
hand that actually completed the response upon presentation of the visual imperative stimulus.
Mauchly’s test was performed to ensure sphericity of the data; regarding RT, a main effect of
StimTime violated the assumption of sphericity, and as such, a Greenhouse-Guisser correction is
39
reported for that one effect. The nature of any significant results involving 3 or more means
were determined using a Tukey’s HSD post-hoc test. Alpha was set to p<.05 for all tests.
3.2.1 Reaction Time
Regarding RT, the analysis revealed a significant main effect of Active Hand, F, (1,
10)=22.52, p<.001. Post-hoc analysis revealed that participants were faster when responding
with the right (non-stimulated) hand (M=433 ms; SD=117.5), than the left (M=482 ms;
SD=120.2).
40
There was also a main effect of StimTime, F (1.1, 11)=15.36, p<.01 (see Figure 3.3).
Post-hoc comparisons revealed that participants responded faster in the 0 ms condition (M=413
ms; SD=112.4) than both the 150 ms (M=473 ms; SD=109.5) and 300 ms conditions (M=502
ms; SD=122.2). There were no significant differences between RTs in the 150 ms and 300 ms
conditions.
Figure 3.3: Mean reaction time separated by StimTime. Error bars indicate standard error of the mean.
*Denotes significance at the p<.05 level
41
Additionally, there was a significant interaction between Compatibility and Active Hand,
F(1, 10)=9.66, p<.05 (Figure 3.4). Post-hoc analysis revealed that RTs were shorter when
participants executed compatible responses with the right hand than compatible responses with
the left (stimulated) hand. There were no differences between incompatible responses with the
left hand and incompatible responses with the right hand.
Figure 3.4: Mean reaction time separated by Active Hand and Compatibility. Error bars indicate standard error of the mean.
*Denotes significance at the p<.05 level
42
Lastly, there was a significant interaction between Time and StimTime, F(2, 20)=4.15,
p<.05. Of particular interest within this interaction was whether RTs for a given StimTime
differed across Time. Pre- versus post-test RTs were not significantly different from one another
in either the 150 or 300 ms StimTimes. However, participants had shorter RTs at the 0 ms
StimTime in the post-test (M=370 ms; SD=102.6) than in the pre-test (M=456 ms; SD=16.1)
(Figure 3.5).
Figure 3.5: Mean reaction time separated by Task and StimTime. Error bars indicate error of the mean.
*Denotes significance at the p<.05 level
43
Consistent with Elsner and Hommel (2001) and Experiment 1 of the current
investigation, the interaction between Time and Compatibility did not approach significance,
F(1, 10)=1.2, p=0.3 (Figure 3.6). That is, there was no RT advantage when participants executed
compatible responses, compared to incompatible responses. Potential explanations for this
finding are discussed in more detail in Section 4.1.
Figure 3.6: Mean reaction time separated by Task and Compatibility. Error bars indicate standard error of the mean.
44
3.2.2 Response Frequency
The RESP analysis revealed a main effect of Active Hand, F(1, 10)=5.61, p<.05,
indicating that participants preferred to perform the task with their left hand (M=54.9%; SD=1)
rather than their right hand (M=45.9%; SD=1). This slight bias might have emerged due to the
extra excitation provided via the TMS. Critically, there was a significant interaction between
Time and Compatibility, F(1, 10)=6.27, p<.05 (Figure 3.7). Post-hoc analysis revealed that in the
post-test condition, participants preferred to interact with compatible trials (M=59%; SD=21.4)
over incompatible trials (41%; SD=21.4). No differences were present in the pre-test condition.
This finding is consistent with the experimental prediction, and replicates results from both
Elsner and Hommel (2001) and Experiment 1 of the current project.
Figure 3.7: Mean response frequency separated by Time and Compatibility. Error bars indicate standard error of the mean.
*Denotes significance at the p<.05 level
45
3.2.3 Normalized MEPs
An analysis of MEP data revealed a significant main effect of Active Hand, F(1, 10)=
48.37, p<.001. MEP values were significantly higher when responses were made with the left
hand (M=1.47; SD=0.68) than the right hand (M=1.05; SD=0.57).
Additionally, there was a main effect of StimTime, F(2, 20)= 4.41, p<.05. Post-hoc
analysis revealed that MEP values were higher in the 0 ms condition (M=1.4; SD=0.66) than in
the 150 ms (M=1.19; SD=0.64) and 300 ms (M=1.18; SD=0.65) conditions, which were not
different from one another (Figure 3.8).
Figure 3.8: Mean MEP separated by StimTime. Error bars indicate standard error of the mean.
*Denotes significance at the p<.05 level
46
Lastly, there was a significant interaction between Time, Hand, and Compatibility F(1,
10)=5.15, p<.05. Post-hoc analysis of this interaction revealed only one marginally theoretically-
relevant significant difference: MEP values were higher in post-test compatible responses made
with the left hand (M=1.56; SD=0.57), compared to the post-test compatible condition in the
right hand (M=0.93; SD=0.48) (Figure 3.9). It is important to note, however, that there were no
significant pre/post differences between compatible and incompatible responses when the left
hand subsequently responded (i.e., no within-left-hand differences).
Figure 3.9: Mean MEP values separated by Time, Active Hand, and Compatibility. Error bars indicate standard error of the mean.
*Denotes significance at the p<.05 level
47
The critical four-way interaction of Time, Hand, Compatibility, and StimTime did not
approach significance F(2, 20)=0.27, p=0.77. This result suggests that the pre/post differences in
the amplitudes of the MEPs on compatible trials did not increase as a function of time from the
presentation of the effect tone.
48
4 Discussion
The present study was designed to investigate the neural basis of R-E relationships in a
task in which participants built an association between an action and its response-contingent
auditory consequence. In Experiment 1, the results of Elsner and Hommel (2001) were
replicated. Specifically, in a free-choice task following a 200 trial R-E acquisition phase,
participants preferred to interact with buttons that were compatible with a learned R-E
contingency rather than one that was incompatible with the learned R-E contingency (reflected in
response frequency results). In Experiment 2, the pre- and post-tests included a single TMS pulse
at one of three different timepoints after the presentation of a learned after-effect. As expected,
the behavioural results of Experiment 1 (preference for compatible buttons in the post-test) were
replicated. Of critical theoretical importance, it was hypothesized that perception of an effect-
evoked response code should be apparent not only behaviourally, but also neurophysiologically -
as evidenced by higher MEP values when the effect tone was compatible with the learned R-E
relationship for the stimulated hand, compared to a control condition. This hypothesis was based
upon the ideomotor notion that the perception of an after-effect learned to be associated with a
particular action automatically evokes a representation of that associated action in the motor
system (e.g., Elsner & Hommel, 2001; Hommel, 1996; Prinz, 1997; Kunde, et al., 2002). MEP
data did not confirm this hypothesis. Specifically, MEP amplitudes were not affected in a
meaningful way by the presentation of a learned after-effect in that there was no apparent within-
hand difference in corticospinal excitability in compatible trials after a 200 trial R-E acquisition
phase. Overall, the behavioural results of the current research project support ideomotor theory
49
and will be discussed first. Second, the neurophysiological results, which did not compliment the
behavioural results, will be considered. MEP results will be discussed regarding potential
complications related to the stimulated cortical hemisphere in Experiment 2, followed by a
consideration of the cortical structures thought to be involved in the R-E relationship. Lastly,
alterations to the current experimental task will be considered.
4.1 Behavioural Results
Neither Experiment 1 or 2 demonstrated a compatibility advantage for RT subsequent to
the acquisition phase. Although some action-effect studies report differences in RT (e.g.,
Hommel, 1996; Kunde et al., 2002), the nature of the current task may not necessarily have set
the conditions needed to garner RT differences. Specifically, due to the free-choice nature of the
task, participants may have chosen to initiate their response more freely in time, thus negating
any RT bias that may have existed. The generally long RT for a simple task supports the notion
that participants may not have completed the task with a sense of urgency. The lack of
theoretically relevant RT results is consistent with the findings of the free-choice experiments of
Elsner and Hommel (2001).
More theoretically relevant to the current experiment, the initial hypotheses pertaining to
R-E relationships were supported by RESP data in both Experiments 1 and 2. When given the
choice, participants preferred to interact with buttons that were compatible with the R-E
contingencies learned in the acquisition task. These results replicated the findings of Elsner and
Hommel (2001) and are consistent with the notion that learned relationships between self-
50
produced movements, and movement-contingent events lead to an automatic and bidirectional
integration of the motor code responsible for producing movement. The integration of these
codes are maintained in a common cognitive code which stores the event-related information. In
the case of the present studies, the presentation of an effect tone activated the associated response
code, and this activated response code subsequently biased response selection in favour of the
“compatible” over the “incompatible” response.
4.2 Neurophysiological Results
It was anticipated that there would be increases in normalized MEP values in the post-test
task when the pre-cue tone presented was compatible with the learned R-E contingency for the
left hand, and when participants executed the compatible response. This effect was predicted to
increase in time from the onset of the tone. Such was not the case; in fact, the critical interaction
(Task x Hand x Compatibility x StimTime) did not approach significance. It was observed,
however, that normalized MEP values recorded in the left hand were higher in the post-test
condition for compatible responses subsequently made with the left hand, than compatible
responses subsequently made with the right hand (see Figure 3.9). Upon initial assessment, this
result appears promising; it was expected that the difference between mean MEP values would
be highest in the post-test on trials where the pre-cue tone corresponded with the left (stimulated)
hand, compared to the right hand. Upon investigation of the data, however, these results are
likely due to higher overall mean MEP values for left hand response trials, compared to right
hand trials. Specifically, rather than the aforementioned difference being consistent with the
experimental hypothesis, these two points (the highest of four means for left hand responses,
51
compared to the lowest of four means for right hand responses) were likely different due to
lateral differences in excitability, based upon which hand responded. Simply put, the to-be-
executed response was selected prior to the TMS pulse and any subsequent difference is likely an
artifact. This claim is corroborated by the fact that a main effect of Active Hand was found;
across all conditions, trials where participants responded with their left hand yielded higher MEP
values than those where they responded with the right hand. Further, there were no significant
differences between pre/post values within the left hand. Overall, these data suggest that,
although the presentation of the effect tones influenced the selection of the responses the
participants executed, the effect tones did not significantly influence corticospinal excitability.
Although the MEP data do not support the hypothesis that the ideomotor coding would affect M1
excitability, they are not necessarily contradictory to ideomotor theory, broadly speaking,
because it is possible that the common codes underlying the response selection biases exist
upstream from M1.
4.2.1 Cortical Structures Involved in the R-E Relationship.
It may have been the case that stimulating the hand area of M1 did not result in a
neurophysiological expression of the R-E relationship because the stimulated area was
downstream of the critical cortical areas responsible this association. Although M1 is known to
have a major role in the planning of actions and is the main source of the corticospinal neurons
that deliver the action signals to spinal efferent neurons, there is contradicting evidence
suggesting that the R-E relationship may exist elsewhere in the brain.
52
For example, Elsner et al. (2002) conducted a positron emission tomography (PET) study
to cortically evaluate ideomotor principles. In this study, participants underwent a typical R-E
task - they first learned that self-initiated keypresses were paired with specific tones (i.e., high or
low tones). After 200 trials of learning, participants were put in a PET scanner, and were
required to passively listen to sequences of action-effect tones and neutral tones, and were not
required to execute a response. Consistent with previous research suggesting that the motor
system plays a role in R-E relationships, the researchers found that the caudal supplementary
motor area increased in activation as the frequency of action-effect tones increased. However,
these researchers also found that the right hippocampus also increased its activity in a similar
manner to the caudal supplementary motor area. Thus, the researchers suggested that not only
does the perception of an after-effect automatically retrieve the associated motor code, but they
also suggested that the increase in hippocampal activation likely indicates that there is a memory
retrieval of the learned associations. That the hippocampus and supplementary motor area may
have a role in the R-E relationship may also explain the lack of a critical interaction in the
current project. The design of Experiment 2 necessitated that the majority of R-E relationships
take place (or at least are expressed) in M1, because the TMS pulse was localized to M1 in order
to generate a muscular contraction at the level of the effector. The results of Elsner et al. (2002)
suggest that M1 might not be activated following the presentation of action effect; at least not
when the person is not required to execute the response.
Similarly, Melcher, Weidema, Eenshuistra, Hommel, and Gruber (2008) replicated and
extended the results of Elsner et al. (2002) using fMRI. Participants actively learned R-E
associations between keypresses and auditory tones, and then passively perceived learned action
effects inside an fMRI scanner. Consistent with the behavioural effects in typical R-E research,
this experiment demonstrated that passive perception of learned action effects results in
53
activation of a number of motor-related brain regions (SMA, premotor cortex, somatosensory
cortex, and cerebellum). Notably, this effect was only observed when left hand action effects
were passively observed, whereas right hand action effects did not demonstrate this trend.
Although this lateralized trend suggests a novel asymmetry in R-E associations that might have
been consistent with our predictions, the authors could only speculate as to what may have
produced this result.
Lastly, Mutschler et al. (2007) provided evidence for R-E associations in cortical
locations that are alternative to the motor system. The researchers used fMRI, and had
participants passively listen to piano melodies which had been actively learned (participant
learned to play the piece), or passively learned (participant listened to the piece) for 30 minutes.
The results indicated that there was a significant increase in activation for the active learning
group in the sensorimotor hand area of the insular cortex, compared to the passive learning
group. These results suggest that the perception of learned action-effect associations may be
stored in the insular sensorimotor cortex.
Taken together, there is a considerable amount of evidence suggesting that R-E
associations may exist within an extensive fronto-partietal network of motor-related areas see
also (see Section 1.3), R-E associations might not involve M1 directly. If this is the case,
stimulating M1 would not necessarily index response code activation, even if R-E associations
exist cortically. Note, however, that in all the previous studies reviewed here the task involved
passive listening. Passive listening might have been used as the experimental task to potentially
control for the confounding effects and extra cortical activity associated with the planning and
selection of a movement. The absence of M1 activity in those studies would be consistent with a
passive listening condition in which no movement was required. The present research was based
54
on the assumption that requiring execution of the task might increase the potential for M1
because the motor system would be engaged to a higher degree. This assumption might have
been faulty and M1 might not be involved in R-E associations, even when a response is needed.
In addition, it is possible that 200 trials of acquisition, or only a single day of acquisition, were
not sufficient to result in significant changes in the coding of M1 (e.g., Ungerleider, Doyon, &
Karni, 1996; Karni et al. 1998). The bias observed in response selection suggests that some
neural plasticity occurred somewhere in the system, but it is possible that M1 was not affected.
Thus, there might not have been a change in MEP amplitude following the presentation of the
different tones because M1 may not be involved in the coding of R-E associations.
4.2.2 Considerations Related to Stimulated Hemisphere.
Another possible reason for the absence of an influence of effect tone on MEPs may have
to do with the stimulated hemisphere/hand system. As discussed earlier in the document (see
Section 1.5), a conscious decision was made to stimulate the right-hemisphere/left-hand system
to potentially isolate the effects of the tone to a single hemisphere and not confound the influence
the left hemisphere plays in planning movements of both limbs. It has been repeatedly reported
that cortical structures in the left hemisphere play a role in movement planning, regardless of
which limb is involved (e.g., Frey, 2008; Haaland, et al., 2000; Kim et al., 1993; Janssen et al.,
2011; Johnson-Frey et al., 2004). Thus, regardless of whether participants chose to respond with
the left or right limb, it was possible that the left hemisphere would be involved in the planning
of that action. Because of the role of the left hemisphere in action planning for both limbs, the
present study adopted a more conservative approach, and chose to stimulate right M1. It was
55
believed that if the left hemisphere was stimulated, MEP results may have changed similarly for
both right and left hand responses because it is involved in planning response for both hands. It
may have been the case that this approach was too conservative. That is, it is possible that the
right hemisphere played too little a role in action planning, and this limited role may have been
responsible for the absence of critical differences in MEP values. In other words, because the
role of the right hemisphere in movement planning is more limited than the left hemisphere (e.g.,
Johnson-Frey et al., 2008), its level of activation may not have been sufficient to bring about
observable differences in the MEP data. It is difficult to know if this was a contributing factor to
the lack of modulation in MEP amplitude, but future work should repeat this study with
stimulation of the left hemisphere.
4.2.3 Task-Related Considerations
It is also possible that the lack of neurophysiological support for the R-E relationship
stems from task design limitations, which may result in participants pre-planning their responses
to a certain extent even prior to the onset of the tone. Recall that test trials in Experiment 2
involved a fixation cross, followed by a delay, followed by a 600 ms pre-cue tone, and a 300 ms
time span including a TMS pulse and a delay (delay time was variable depending upon
StimTime). It may have been the case that due to the timing of task events/stimuli, participants
had already planned which of the two movements they would execute on the upcoming trial by
the time that the TMS pulse was delivered. The pre-planning of the responses may be reflected
in the main effect for Active Hand observed for MEP amplitudes.
56
Additionally, participants may not have completed the task with the sense of urgency
which was expected, but rather they may have selected an action and retrieved the motor plan
subsequent to the delivery of the TMS pulse. The latter suggestion is consistent with the lack of
an RT bias for compatible trials in the post-test condition; it appeared as though participants
were executing their responses more freely in time, without a sense of urgency. If this were the
case, neurophysiological differences would also not have been expected. The task design was
based upon the assumption that participants would be responding to stimuli as quickly and as
accurately as possible. If they executed their responses more freely in time, the timing of TMS
pulses may not have been a true indicator of excitability during the cognitive retrieval of motor
plans bound to the presented effect tone.
Lastly, there may be issues with the timing of stimulation and the length of the effect
tones. In Experiment 2, the earliest StimTime condition was immediate upon offset of the effect
tone. Thus, all three StimTime conditions stimulated M1 after the offset of the effect tone (600
ms after the onset of the tone). A necessary adaptation to the task would be to stimulate M1
simultaneous to or during the effect tone to get a better sense of the timecourse of M1 activation
following the tone. This may provide further insight regarding the corticospinal excitability of
the motor system while the effect tone is perceptually available.
57
5 Conclusions
The purpose of the research reported in this thesis was to test if the perception of a
learned after-effect automatically resulted in the retrieval of its associated motor code. This
purpose was investigated over two experiments. In Experiment 1, participants completed an
acquisition phase where they learned R-E mapping between two keypresses and their response-
contingent auditory effect tones. In a free-choice testing phase after acquisition, where one of
two effect tones was presented prior to the imperative stimulus, participants demonstrated a
preference to interact with the button that was compatible with the effect tone that had played
following the response during the learned R-E mappings in the acquisition phase. In Experiment
2, participants completed a similar acquisition task, but the pre- and post-test tasks were adapted
to include a single TMS pulse at one of three timepoints on each trial. The amplitude of the
MEPs evoked via TMS was used as an index of corticospinal excitability following the
perception of a learned after-effect. Behaviourally, the results from Experiment 2 were consistent
with Experiment 1; participants preferred to interact with the button that was compatible with the
pre-cue effect tones after an acquisition phase. The neurophysiological results did not reflect this
response bias. The critical interaction did not reach significance, and differences which did
emerge were likely due to underlying biases caused by differential activation when the
stimulated versus non-stimulated hand responded.
Three potential (not mutually exclusive) explanations may account for the absence of
MEP differences in Experiment 2. First, the experimental design involved stimulating the right
hemisphere. This conservative approach was taken because the left hemisphere is thought to be
involved in response planning for both limbs, and it was thought that stimulating the right
58
hemisphere would avoid potential confounds associated with this role of the left hemisphere.
This approach, however, may have been too conservative, as the right hemisphere may not play a
substantial enough role in response planning to see differences in excitability. Second, TMS was
applied to M1. Growing evidence suggests that R-E associations may take place outside of the
motor system – or at least upstream from M1. If this were the case, stimulating M1 would not
necessarily reflect increased excitability as reflected in MEP data. Lastly, trial sequences need to
be adapted. Specifically, the timecourse of test trials may have enabled participants to pre-plan
their responses, which would result in less excitability at the stimulation times, and TMS
stimulation must be adapted so that participants are stimulated simultaneous to the playback of
the auditory effect tone. Overall, the present research suggests that presentation of the effect
tones influence the selection of the responses the participants executed, but the effect tones did
not significantly influence corticospinal excitability. Further research is necessary to determine
whether this is due to the stimulated hemisphere, non-stimulated cortical structures playing a role
in R-E associations, or timing of task events.
59
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Appendices
APPENDIX A: MEDICAL HISTORY QUESTIONNAIRE
FOR VOLUNTEERS PARTICIPATING IN STUDIES INVOLVING TRANSCRANIAL MAGNETIC STIMULATION
SURNAME:............................ GIVEN NAMES:.................................
DATE OF BIRTH:............................ SEX:......................
ADDRESS:..............................................................................................
HOME PHONE:....................... WORK PHONE:.......................
1. When was the last time you had a physical examination?
2. If you are allergic to any medications, foods or other substances, please name them.
3. If you have been told that you have any chronic or serious illnesses, please name them.
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4. Have you been hospitalized in the past three years? Please give details.
5. During the past twelve months:
Has a physician prescribed any form of medication for you? Y/N
Have you experienced any faintness, light-headedness, blackouts? Y/N
Have you occasionally had trouble sleeping? Y/N
Have you had any severe headaches? Y/N
Have you experienced unusual heartbeats such as skipped beats or
palpitations? Y/N
Have you experienced periods in which your heartbeat felt as though it
were racing for no apparent reason? Y/N
6. At present:
Do you experience shortness of breath or loss of breath while
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walking? Y/N
Do you experience sudden tingling numbness or loss of feeling in
your arms, hands, legs, feet or face? Y/N
Do you get pains or cramps in your legs? Y/N
Do you experience pain or discomfort in your chest? Y/N
Do you experience any pressure of heaviness in your chest? Y/N
Do you have diabetes? Y/N
If yes, how is it controlled (please circle one)? dietary means... insulin injector...
oral medication... uncontrolled...
7. Have you ever been told that your blood pressure was abnormal? Y/N
8. How often would you characterize your stress level as being high (please circle one)?
never…occasionally... frequently... constantly...
9. Have you ever undergone electro-convulsive-therapy (ECT)? Y/N
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10. If you are female, are you or is there a chance you might be pregnant? Y/N
11. Have you ever experienced seizures or fainting spells? Y/N
12. Have you ever been told that you have any of the following illnesses?
(please circle all that apply)
myocardial infarction... arteriosclerosis... heart disease... heart block...
coronary thrombosis... rheumatic heart... heart attack... aneurism...
coronary occlusion... angina... heart failure... heart murmur...
13. Has any member of your immediate family been treated for or suspected
of having any of the following conditions? Please identify their relationship
to you (e.g., father, mother, etc.)
(a) Epilepsy-
(b) Stroke-
(c) Diabetes-
(d) Heart disease-
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(e) High blood pressure-
(f) Memory loss-
(g) Dementia-
14. Please list all operations or surgical procedures of any kind performed
in the last 15 years.
1.
2.
3.
4.
5.
6.
15. Have you ever been injured by any metallic foreign body
(e.g., nail, bullet, shrapnel, etc.)? Y/N
16. Have you ever engaged in metal grinding? Y/N
If yes, could metal fragments be present near your eyes? Y/N
17. Is there any history of head trauma with loss of consciousness? Y/N
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18. Please indicate if you have any of the following:
Cardiac pacemaker Y/N
Aneurysm clips Y/N
Implanted cardiac defibrillator Y/N
Any type of biostimulator Y/N
Any type of internal electrodes (e.g., cochlear implant) Y/N
Insulin pump Y/N
Any type of electronic, mechanical or magnetic implant Y/N
Hearing aid Y/N
Any type of intravascular coil filter or stent (e.g., IVC filter) Y/N
Artificial heart valve prosthesis Y/N
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Orbital/eye prosthesis Y/N
Any type of surgical clip or staple Y/N
Intraventricular shunt Y/N
Artificial limb or joint Y/N
Dentures Y/N
Any implanted orthopaedic item (eg. pins, rods, screws, nails,
clips, plates, wire) Y/N
Any other implanted item Y/N
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I certify that the above information is correct to the best of my knowledge. I have read and understand the entire contents of this form and I have had the opportunity to ask questions regarding the information on this form.
Volunteer's name
______________________________________
Volunteer's signature
______________________________________ Date: _____________________
Witness's name
______________________________________
Witness's signature
______________________________________ Date: _____________________
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Appendix B: Participant and Testing Session Information
Date: __________________ Participant Number:____________ Age: ____________
Gender (circle one): Female / Male
Vision (circle one): Normal / Corrected-to-normal
Do you wear corrective lenses of any kind?
If so, please wear them when you participate in the study.
Assessment of Mental Health
1) With a “yes” or “no” answer, please tell me if you have any pre-existing mental illnesses or disorders of the central nervous system. If your answer is “yes”, please do not provide any details.
2) With a “yes” or “no” answer, please tell me if you have had a concussion or other closed-head injury within the last 3 months. If your answer is “yes”, please do not provide any details.
Note: Potential participants must answer “no” to both of these questions in order to be allowed to
enter into the study. When they arrive for the testing session, they will also be required to
complete a more thorough Health Questionnaire.
Determination of Hand Dominance
Please answer these questions using the following scale:
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Always the left hand - Mostly the left hand - Either hand – Mostly the right hand – Always the
right hand
1) Which hand do you use to write with when you are writing with a pen? 2) Which hand do you use to throw a ball? 3) Which hand do you use to eat soup with a spoon? 4) Which hand do you use to brush your teeth? 5) Which hand do you use to hold a hammer when hammering a nail into a wall?
Stimulation and Recording Details
EMG Channel 1: Muscle_____________ Estimate MEP P2P amplitude at rMT: ______µV
EMG Channel 2: Muscle_____________ Estimate MEP P2P amplitude at rMT: ______µV
Resting motor threshold: ___________% Number of MEPs >100 µV P2P: _________/10
Testing level (115% rMT): _________%
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APPENDIX C: EXPERIMENT 1 MEAN VALUES
Mean RT values (in ms) ± standard deviation
Mean RESP values (%) ± standard deviation
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APPENDIX D EXPERIMENT 2 MEAN VALUES
Mean RT values (in ms) ± standard deviation
Mean RESP values (%) ± standard deviation
Mean normalized MEP values ± standard deviation