body representation in children and adolescents...map the body parts of other children and...
TRANSCRIPT
Body Representation in Children and Adolescents
by
Sandra Marie Pacione
A thesis submitted in conformity with the requirements for the degree of Master of Science
Exercise Science University of Toronto
© Copyright by Sandra Marie Pacione 2015
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Body Representation in Children and Adolescents
Sandra Marie Pacione
Master of Science
Graduate Department of Exercise Science
University of Toronto
2015
Abstract
The purpose of the present study was to determine if children and adolescents are able to
map the body parts of other children and adolescents on to the representation of their own body
parts and if age influences this mapping. To this end, participants completed a body-part
compatibility task where responses were executed to coloured targets (relevant feature) presented
over the hand or foot (irrelevant feature) of separate male models of different ages (7, 11, and 15
years of age). It was found that body-part compatibility effects emerged for both the 10-12 and
13-16 year old age groups. No body-part compatibility effects were found for the 7-9 year old
age group. Most interestingly, the body-part compatibility effects for both the 10-12 and 13-16
year old age groups occurred when viewing models of their own peers. Overall, the results
indicate that the body-part matching process is sensitive to social factors.
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Acknowledgments
I would like to express my deepest gratitude to my supervisor, Professor Timothy Welsh,
whose unwavering support and understanding helped enrich my graduate education and fueled
my passion for research. To my committee members, Professor Luc Tremblay and Doctor Jessica
Brian, I am extremely grateful for your support and suggestions throughout the project. To my
lab mates, thank you for your encouragement and daily dose of laughter. To my friends and
family, thank you for helping me to succeed throughout the years. Most of all, I am fully
indebted to my parents, for their understanding, patience, and encouragement and for pushing me
farther than I thought I could go.
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Table of Contents
Acknowledgments ........................................................................................................................ iii
Table of Contents ......................................................................................................................... iv
List of Tables ................................................................................................................................ vi
List of Figures .............................................................................................................................. vii
Introduction .................................................................................................................................. ix
Chapter 1 Literature Review ....................................................................................................... 1
1.1 Introduction ......................................................................................................................... 1
1.2 Perception-Action Coupling ............................................................................................... 1
1.2.1 Summary ................................................................................................................. 4
1.3 Self-Other Mapping in Action and Shared Experiences ..................................................... 4
1.3.1 Self-Other Mapping and Action Observation in Children ...................................... 7
1.3.2 Summary ................................................................................................................. 8
1.4 Body Schema ...................................................................................................................... 9
1.4.1 Body Schema Development .................................................................................. 11
1.4.2 Summary ............................................................................................................... 12
1.5 Body-Part Compatibility ................................................................................................... 12
1.5.1 Summary ............................................................................................................... 15
1.6 Conclusion ........................................................................................................................ 16
1.7 The Current Project: Purpose and Specific Hypotheses ................................................... 17
Chapter 2 Research Article ........................................................................................................ 19
2.1 Introduction ....................................................................................................................... 19
2.2 Methods ............................................................................................................................. 22
2.2.1 Participants ............................................................................................................ 22
2.2.2 Apparatus, Task, and Procedure ........................................................................... 22
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2.3 Results ............................................................................................................................... 26
2.3.1 Spatial Compatibility ............................................................................................ 26
2.3.2 Body-Part Compatibility ....................................................................................... 28
2.3.3 Correlation of Upper and Lower Spatial RTs with Body-Part RTs ...................... 33
2.4 Discussion ......................................................................................................................... 35
Chapter 3 General Discussion .................................................................................................... 39
3.1 Findings and Implications ................................................................................................. 39
3.2 Limitations ........................................................................................................................ 41
3.3 Future Directions .............................................................................................................. 45
3.4 Delimitations ..................................................................................................................... 47
Chapter 4 Conclusion ................................................................................................................. 48
References .................................................................................................................................... 50
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List of Tables
Table
Number
Table Caption Page
Number
Table 2.1. Mean (and standard deviations) of the % of response errors as a
function of Presentation Side, Responding Effector, and Spatial
Height.
27
Table 2.2 Mean (and standard deviations) of the % of response errors as a
function of Presentation Side, Responding Effector, Model Type,
Target Location.
28
Table 2.3. Mean (and standard deviation) response times in milliseconds for
each of the 3 Groups as a function of Model Type and Target
Location. Marginal means are also provided.
29
Table 2.4. Planned comparison of response time differences across the three
age groups.
29
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List of Figures
Figure
Number
Figure Caption Page
Number
Figure 2.1. Examples of the 7, 11, and 15 year old models with coloured targets.
Only a single image was presented on each trial. The black boxes
surrounding each image were not presented in the experiment, but were
included here to demonstrate the different sizes and proportions of the
images.
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Figure 2.2. Examples of the coloured targets in lower and upper space. The black
boxes surrounding each image were not presented in the experiment,
but were included here to demonstrate the different locations of the
targets in the trials.
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Figure 2.3. Mean response time in milliseconds for the 7 to 9 year old group as a
function of model type and target location. Standard error of the mean
bars are depicted. Note that the response time scale is consistent across
Figures 2.3, 2.4, 2.5 at 200ms, although the range over which the data
are depicted are different.
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Figure 2.4. Mean response time in milliseconds for the 10 to 12 year old group as a
function of model type and target location. Standard error of the mean
bars are depicted. Asterisks indicate significant difference between
target locations, p <.05 *.
32
Figure 2.5. Mean response time in milliseconds for the 13 to 16 year old group as a
function of model type and target location. Standard error of the mean
bars are depicted. Asterisks indicate significant difference between
target locations, p <.05 *.
33
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Figure 2.6. Correlation of body-part difference scores from the body-part
compatibility task (y-axis) as a function of the spatial difference scores
from the spatial compatibility task (x-axis) for the 7 to 9 year old
group.
34
Figure 2.7. Correlation of body-part difference scores from the body-part
compatibility task (y-axis) as a function of the spatial difference scores
from the spatial compatibility task (x-axis) for the 10 to 12 year old
group.
34
Figure 2.8. Correlation of body-part difference scores from the body-part
compatibility task (y-axis) as a function of the spatial difference scores
from the spatial compatibility task (x-axis) for the 13 to 16 year old
group.
35
Figure 3.1 Difference scores of the incompatible by compatible conditions as a
function of model type for the 7 to 9 year old group. Conference
Intervals are depicted. Black dots indicate the three 7 year old
participants’ scores.
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Figure 3.2 Difference scores of the incompatible by compatible conditions as a
function of model type for the 10 to 12 year old group. Conference
Intervals are depicted.
43
Figure 3.3 Difference scores of the incompatible by compatible conditions as a
function of model type for the 13 to 16 year old group. Conference
Intervals are depicted.
43
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Introduction
In daily life, humans are constantly interacting with other people - be it helping an elderly
woman carry her groceries or talking with neighbours. According to Hobson and colleagues, to
identify with someone else is to relate to the actions of someone else from the other person’s
perspective. Through this identification process, it is possible to share experiences of the world
with another individual from the other’s perspective (Hobson & Hobson, 2007; Hobson & Lee,
1999; Hobson & Meyer, 2005). One of the processes that are thought to facilitate this complex
ability of identification and social interaction is one in which humans register the perceptions and
thoughts of others against the neural representations used to perceive the self. The main premise
of this theory is that an understanding of others occurs through the use of self-representations
(Lombardo et al., 2010). These cognitive representations of the self and the other are thought to
be fundamentally grounded in the physical context of the body (Niedenthal, Barsalou,
Winkielman, Krauth-Gruber & Ric, 2005). To perceive and act in its environment, the
individual’s body and its interactions with the sensory and social environment are represented in
the brain. Internal representations of the body are closely tied to the processing of action
understanding and social interactions, and hence social cognitive processes (Assainte, Barlaam,
Cignetti, & Vaugoyeau, 2014; Niedenthal et al., 2005).
The purpose of the present research is to investigate the integrity of mechanisms
underlying the ability to represent the bodies of other humans (i.e., self-other matching) in
typically developing (TD) children and adolescents. To investigate these processes, I will
evaluate the performance of TD individuals using a human body-part compatibility task (e.g.,
Bach, Peatfield, & Tipper, 2007; Welsh, McDougall, & Paulson et al., 2014; Pacione & Welsh.,
in press), which provides an index of the body-part matching process. Specifically, participants
will respond to coloured targets (relevant feature) presented over the hand or foot (irrelevant
feature) of separate male models of different ages (7, 11, and 15 years of age). The information
generated by the present study can be used to understand the neural underpinnings of how one’s
own body position influences one’s perception of others’ body representations.
My general predictions are that if the bodies in the images are mapped onto the human
body schema of the observer, then a body-part compatibility effect will be observed (as in Bach
et al., 2007; Welsh et al., 2014; Pacione & Welsh, in press). If the bodies in the images are not
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mapped onto the human body schema of the observer, then no body part compatibility effects
will be observed and there will be no differences between response times (RT) to stimuli
presented on the different body parts. With respect to the main research question, it is further
predicted that if the individuals of different ages are able to map the bodies of all the images onto
the human body schema, then generalized body-part compatibility effects will be observed across
all age groups. Alternatively, if the individuals are able to map the bodies of age-related images
onto the human body schema, then age-specific body-part compatibility effects will be observed
(as in Bach et al., 2007; Welsh et al., 2014; Pacione & Welsh, in press).
In the present document, I will begin by reviewing the theoretical underpinnings of both
perception-action coupling and self-other matching, followed by a discussion on the body
schema and finally, examine the role of body-part compatibility. This literature review will be
presented in Chapter 1. In Chapter 2, I will present my experimental findings associated with the
research question. In Chapter 3, I will discuss the implications of the research findings, followed
by a discussion of the current design of the experiment and applications for future research.
Finally, in Chapter 4 I will conclude with a summary of the purpose and main research findings
of the presented work and review some of theoretical underpinnings.
1
Chapter 1 Literature Review
1.1 Introduction
Humans have an inherent ability to understand other people. The ability to understand
others may be fundamentally situated in distributed neural networks that encompass shared self-
other body and action representations. This network is thought to enable individuals to represent
their own and others’ goal-directed actions via a single conceptual system (Decety &
Sommerville, 2003). This conceptual system would allow individuals to understand the actions,
emotions, and intentions of others. This innate relationship between the self and the other has
been recently underlined by theories of embodied cognition according to which bodily
experiences play a primary role in human cognition - cognitive processes are essentially
grounded in bodily states (Gallese & Sinigaglia, 2011). The notion of embodiment implies that
individuals draw on information from their own experiences and action capabilities to interpret
their environment and shape their own cognitive processes. Such experiences, however, are also
likely to be involved in the ability to perceive and to know the structure and movements of the
bodies of other individuals, and ultimately, to understand their actions and to interpret their
gestures for social communication.
In this review, I will begin with a discussion of perception-action coupling, followed by a
review of self-other matching in action and shared experiences. The review of this literature will
highlight why the action-perception coupling mechanism offers a functional bridge between
actions produced by the self and those produced by others, grounded on self-other equivalence. I
will also review recent neurophysiological evidence on the body schema and conclude with a
section on body-part compatibility. This latter literature will explore why the body-part
compatibility task appears to be an effective tool to assess self-other matching and potentially,
the involvement of the human body schema in social cognitive processes and will provide the
direct theoretical context for the present investigation.
1.2 Perception-Action Coupling
Not only are individuals able to select, plan and execute a variety of actions to achieve
their own personal goals, but individuals are also able to perceive and predict the intended and
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expected effects of such actions. The continuity between action and perception is thought to be
formed on the basis of an ideomotor (or common coding) network. In this common coding
network, the neural codes that are responsible for generating specific goal-directed action are
tightly coupled to the codes that represent the perceptual consequences of those actions
(Hommel, 2009; Prinz, 1997). It is thought that by repeatedly performing a movement and
experiencing the perceptual consequences of that action, a bidirectional association is formed
between the neural codes that represent the motor pattern that was generated and the sensory
consequences that action produced. The result of this bidirectional binding is that the activation
of one code can result in the activation of the other. That is, this bound action-effect coding
enables individuals to not only react to the environment by selecting the most appropriate effects
for a given situation, but also to anticipate the consequences of one’s own actions and the actions
of others. This series of coupled activation is thought to facilitate efficient and accurate response
selection (Elsner & Hommel, 2001).
Elsner and Hommel (2001) demonstrated action-effect integration through experience
across a series of studies. During the training phase of one task, they had participants perform a
choice reaction time task in which they made arbitrary left and right keyboard presses. A specific
effect tone followed each response, specifically, a high tone would follow a left key press and a
low tone followed a right key press. It was predicted that the constant pairing of a response with
an effect tone would lead to binding between that specific response and a specific tone.
Following the training, subjects were presented with a free-choice task where one of the two
effect tones was randomly presented prior to the moment at which the participant was to choose
to execute a left or right key press. The critical finding of the studies was that participants were
more likely to choose and execute the response that was compatible with effect tone that was
presented as the task-irrelevant pre-cue tone. That is, left key responses were made more often
after a high tone than when a low tone was presented, and right key responses were made more
often following a low tone than after a high tone. The authors concluded that this finding
indicated that participants formed an association between the motor pattern underlying the action
and the perceptual consequence of the action effect through experience during the training phase,
and that the presentation of the effect tone in the testing phase (e.g., a high tone) activated the
response code that would lead to that effect (e.g., left response). This pre-activation of the given
response then biased response selection processes leading to the more common execution of the
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response that was associated with the effect tone presented as the pre-cue. Overall, these findings
lend considerable support for a bidirectional relationship between actions and their perceptual
effects.
Relatedly, other researchers have proposed that individuals use a forward model to
predict their own actions as well as the actions of others (Wolpert, Ghahramani, & Jordan, 1995;
Wolpert, 1997, Blakemore & Decety, 2001). According to this approach, during self-produced
actions, a sensory prediction of the outcome of the action is produced along with the actual
motor command. The forward model makes a prediction of the sensory consequences of motor
commands, which are compared with the actual consequences of the movement. The results of
the comparison between the sensory prediction and the sensory consequences of the act can then
be utilized to reconfigure afferent inputs to bring about the desired action.
Although not yet directly linked to the forward model or ideomotor theory, the discovery
of ‘mirror neurons’ provided the first convincing physiological evidence for a direct link
between action perception and action execution. It was reported by di Pellegrino and colleagues
(1992) that action-coding neurons or ‘mirror neurons’ reside in the prefrontal cortex of monkeys.
Surprisingly, these neurons discharged significantly more both when the monkey performed a
goal-directed action and when it observed another individual performing the same action.
Similarly, in humans, several brain regions including the premotor cortex, the posterior or
parietal cortex and the cerebellum, are activated both during action generation and while
observing and simulating others’ actions (Decety, et al., 1994; Decety et al., 1997; Ruby &
Decety, 2001; Fadiga, Fogassi, Pavesi, & Rizzolatti, 1995; Hari, Forss, Avikainen, Kirveskari,
Salenius, & Rizzolatti, 1998; Buccino et al., 2001). Thus, simply watching the goal-directed
movements of the body parts of another individual activates the same functionally specific
regions of the premotor cortex as performing those movements; a phenomenon sometimes
known as “motor resonance”.
In human subjects, a number of functional imaging studies have demonstrated the
involvement of motor representations during the perception of actions performed by others
(Hamzei, Rijntjes, Dettmers, Glauche, Weiller, & Buchel, 2003; Calvo-Merino, Glaser, Grezes,
Passingham, & Haggard, 2005). Notably, Buccino and colleagues (2001) showed that the
activation pattern in the premotor cortex elicited by the observation of actions performed by
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another individual follows somatotopic organization in conjunction with the observed action.
Specifically, they reported that watching mouth, foot, and hand actions elicits different activation
sites in the premotor and parietal cortices, which are normally involved in the actual execution of
the observed actions. These results strongly support the existence of an action execution-
observation matching system. This system would support the processes that allow individuals to
recognize actions performed by others by mapping the observed action on the individual’s own
motor representation. According to this hypothesis, action observation automatically activates in
the observer the same neural substrates involved in the actual execution of the observed action.
The activation of the same neural substrates during action observation would allow the observer,
through an execution-observation matching mechanism, to understand the perceived actions of
the other (Buccino et al., 2004; Decety & Grezes, 2006). This matching mechanism may provide
the basis for social interactions and constitute a necessary precursor for the capacity to imitate
and language acquisition (Rizzolatti & Arbib, 1998; Rizzolatti, Fadiga, Fogassi, & Gallese,
2002).
1.2.1 Summary
Action observation is thought to arise from action-perception coupling mechanisms that
are mediated by internal representations of the action themselves. In this common coding
network, the neural codes that are responsible for generating specific goal-directed action are
tightly coupled to the codes that represent the perceptual consequences of those actions
(Hommel, 2009; Prinz, 1997). This tight coupling and bidirectional activation enables
individuals not only to react to the environment, but also to anticipate the consequences of
others’ actions. Moreover, these representations not only guide behaviour, but may also be used
to interpret the behaviour of others. This action-perception coupling mechanism offers a
functional bridge between actions produced by the self and those produced by others, grounded
on self-other equivalence (Decety & Sommerville, 2003).
1.3 Self-Other Mapping in Action and Shared Experiences
Self-other mapping is a process by which individuals register the perceptions and
thoughts of others against the representations used to perceive the self. This process asserts that
the self and other are intricately tied together. Gallese (2001) emphasizes that to understand the
intended goals of an observed action, a link must be established between the observer and the
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observed actor. In doing so, the self is used as an anchor point for modelling others’ actions and
intentions (Lombardo et al., 2010). Specifically, individuals use information from their bodies
and action capabilities to understand the actions of others (Decety & Sommerville, 2003).
Consistent with ideomotor approaches, the sensory consequences of an individual’s
action can be used to understand and predict the actions of others (Jeannerod, 2001; Sebanz &
Knoblich, 2009; see also Wolpert, Ghahramani, & Jordan, 1995; Wolpert, 1997). According to
this model, during self-produced actions, a motor command and an efference copy (i.e., sensory
prediction) of the outcome are produced in parallel to predict the sensory consequences of the
motor act. The sensory prediction and actual sensory consequences are compared to better
inform future actions. Blakemore and Decety (2001) suggest that the forward model stores
representations of sensory predications associated with multiple actions. This store of predictions
of the consequences of self-generated actions could therefore be used to estimate the actions (and
therefore intentions) made by another individual. Thus, through an implicit process of action
simulation, the actions of another individual could be mapped onto the stored sensory predictions
of the individual’s own actions (Gallese, 2001; Blakemore & Decety, 2001; Jackson & Decety,
2004). This interpretation is also compatible with simulation theories, which assume that when
an individual observes the actions of others, one covertly simulates the same action (Jackson et
al., 2004). Observing the actions of another can therefore act as a mirror to gain more knowledge
about the self (Gallese, 2003).
The observation of action can initiate a simulated response in the observer (Blakemore &
Decety, 2001). Similarly, during situations involving more than one actor, action simulation can
also be used to coordinate actions with others. This process becomes clear when one considers
that joint action often requires that two or more individuals adapt their actions in time and space
to achieve a common goal (Sebanz & Knoblich, 2009; Sebanz, Knoblich & Prinz, 2003).
Critically, it is proposed that a shared task representation is created whereby co-actors attend to
the same objects and events, creating a ‘perceptual common ground’ (Sebanz, Bekkering &
Knoblich, 2006). For performance, it has been suggested that joint action coordination toward a
shared goal is to a large extent achieved by internal simulation of actions and effects that allows
co-actors to predict their own and their partner’s actions using their own motor system (Wolpert
et al., 2003). When coordinating actions with the other person, motor simulations of one’s own
and a partner’s actions need to be integrated to achieve a shared goal. This integration is
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achieved whereby the individual incorporates the others’ action capabilities into their own action
planning. Joint action provides a unique context by which the action capabilities of the self are
used not only to understand the actions of others, but are central to coordinating actions with
others.
At the neural level, it is interesting to note that our ability to represent our own thoughts
and actions and those of others are closely tied together and may share similar origins in the
brain (Decety et al., 2003; Jackson et al., 2004). Recent research indicates that the premotor,
insula and the right inferior parietal cortex may be crucial in correlating notions of the self with
the other. Activation of the right inferior parietal lobe correlates with sense of ownership in
action execution (Farrer, Franck, Georgieff, Firth, Decety, & Jeannerod, 2003). Similarly,
activation in the right inferior parietal lobe is also found in reciprocal imitation and during
mental simulation of another’s actions (Ruby & Decety, 2001). Additionally, when subjects are
asked to adopt another person’s perspective to evaluate their beliefs, the right inferior parietal
lobe is also strongly involved (Ruby & Decety, 2003). These findings highlight a partial overlap
between self-processing and the processing of others in the brain, lending support for a shared
neural representation (Jeannerod, 2003).
This shared neural representation goes beyond the domain of action to incorporate affect
and emotions, allowing individuals to empathize with others (Gallese, 2001, 2003). According to
Jeannerod (2003), empathy expresses the possibility that individuals are able to understand other
people’s behaviour because they attempt to replicate and simulate their mental activity. Such a
view has received empirical support from a variety of behavioural and neuroimaging studies that
highlight similar neural systems are involved both in the recognition and in the expression of
specific emotions. Dimberg and colleagues (2000) demonstrated that viewing facial expressions
triggers expressions on one’s own face, even in the absence of conscious recognition of the
stimulus. An fMRI study confirmed these results by showing that when participants are required
to observe or to imitate facial expressions of various emotions, increased neural activity is
detected in the regions that are implicated in the expression of these emotions, including the
superior temporal sulcus, the anterior insula, the amygdala and the premotor cortex (Carr,
Iacoboni, Dubeau, Mazziotta, & Lenzi, 2003). Similarly, the experience of pain by the self and
its observation in others also provides support for a shared neural representation of empathy. In
an fMRI study, Morrison and colleagues (2004) compared the activation pattern during the
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experience of pain and its observation in others. The results revealed common activated areas in
the anterior cingulate cortex and the anterior insula. Altogether, these findings emphasize a
system that prompts the self to resonate with the emotional state of the other through simulation.
Observing the other spontaneously activates the parallel motor representation and its associated
autonomic and somatic responses in the self.
1.3.1 Self-Other Mapping and Action Observation in Children
Observing the other and modelling one’s appearance and actions to more closely
resemble those of the one’s peers appears to be particularly relevant for pre-adolescent and
adolescent populations. Specifically, peer interactions at schools and community settings are
formally structured to facilitate same age interactions. Large amounts of time are spent with
peers of one’s own age, thus shaping shared experiences. These shared experiences are often
created through social play. Experiences gained within own-age groups foster similar behavioral
norms and interaction styles, and over time, these interactions may promote the development of
similar attitudes, motives, interests, and aspirations (Leaper, 1994; Maccoby, 1998). As such,
own-age peer groups represent a potentially powerful context for socialization (Serbin, Moller,
Gulko, Powlishta, & Colburne, 1994).
Social psychological research has demonstrated that children show preferences for
members of their own groups across many domains, including gender, race, and even nationality
(Bigler & Liben, 2006). Furthermore, there is social pressure to act in accord with one’s group.
Thus, children who do not conform to the social norms of the in-group are judged more harshly
than children who do, and this is especially true for older children and adolescents as compared
to younger children (Abrams, Rutland, Cameron, & Marques, 2003). In particular, peer
interactions may have both a positive and negative influence on child and adolescent
development. In particular, research has focused on the role of peers as socializers of
adolescents’ negative behaviours, such as drug use, smoking and delinquency (Brechwald &
Prinstein, 2011). Thus, children who share similar interests and commonalities may be viewed as
like-minded individuals and are perceived more positively. On the other hand, those children
who do not share commonalities with their own-age peers may be viewed as individuals who are
not ‘like me’ and excluded from the in-group. Subsequently, children may be biased in favour of
in-group members and will strive for consistency between themselves and their own-age peers
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(Martin, Fabes, & Hanish, 2014). For instance, children want to be more like their own-age
group members which leads them to choose to interact with same-aged peers.
The limited amount of research that has been done on action observation and execution in
children reveals findings that are consistent with this own-age group affiliation effect. In
particular, Marshall and colleagues (2010) investigated motor contagion in children. Motor
contagion is an interference effect that occurs during movement execution when simultaneously
observing someone else’s incompatible action. The authors found stronger contagion effects
when children observed dynamic images of their own peer. Specifically, they instructed children
to move a stylus on a graphics tablet vertically or horizontally in the presence of a background
video. The background video was of a model moving her arm in a direction that was either
congruent or incongruent with the axis of the child’s stylus movements. The presence of the
incongruent background movements was associated with significant interference effects on
children’s stylus movements; there was more motion in the incongruent direction. Of particular
importance, this interference effect was stronger when the background movements were
performed by a same-aged peer rather than by an adult. Thus, these findings suggest that there
may be an age specific bias in motor resonance and, perhaps, body mapping with children and
adolescents.
1.3.2 Summary
The ability to engage with others is critically grounded in a shared neural representation
between the self and other. It is this shared self-other representation that allows individuals to
understand the behaviours, thoughts, and emotions of others. It is made possible through a
simulation mechanism that matches action observation and execution onto the same neural
substrate (Gallese, 2001). Self-other equivalence is particularly relevant for pre-adolescent and
adolescent populations. Specifically, children learn the ‘culture’ of their own-age group and they
subsequently seek to be viewed as like-minded individuals and be perceived more positively by
their own age peers. Ultimately, an individual’s capacity to share experiences with others is
fundamentally grounded in the body. Gallese (2003) suggests that what makes the behaviour of
other agents intelligible is the fact that their body is experienced as something analogous to one’s
own experienced body. This correspondence is achieved by identifying the body parts of others
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and matching those to the representation of one’s own body parts in the brain – a process I turn
to next.
1.4 Body Schema
Perhaps some of the more compelling evidence for the existence of a cognitive
representation of body position comes from the earliest interactions between infants and their
adult models. It appears that even before experiencing contact with the environment, humans are
equipped with a rudimentary knowledge about the dynamic organization not only of one’s own
body, but also of its relations to other bodies. Even minutes after birth, infants show a strong
innate tendency to mimic sounds and oro-facial motor acts performed by the adult models in
front of them (Meltzoff & Moore, 1977). This finding indicates that infants can visually identify
the movement of a specific part of the adult body and produce a similar movement in the
corresponding part of their own anatomy (Berlucchi & Aglioti, 2010). This early form of
imitation is an example of the established link between the self and other.
Neuropsychological evidence for an individual’s ability to code body parts was initially
derived from studies that reveal that humans possess a body schema or a mental construct
devoted to the dynamic spatial organization amongst parts of the body of the self and its relations
to that of other bodies (Semenza & Goodglass, 1985; Semenza, 1988; Ogden, 1985; Sirigu,
Grafman, Bressler, & Sunderland, 1991). It is thought that a body representation (or schema) is
used for the unconscious encoding of body position for both the self and others because it is
evoked during the perception of a human body. For example, Reed and Farah (1995) had
participants perform a series of same-different visual matching tasks for body position memory.
Specifically, participants had to determine if the cued position of a human model had changed or
not. At the same time, participants engaged in a secondary movement task of moving either their
arm or leg. Both movement conditions showed facilitated performance when the same body part
was cued and then moved and impaired performance when a different body part was cued and
then moved. Most interestingly, they subsequently compared participants’ performance on the
body position memory task with an object position memory condition. In this object memory
condition, participants were cued to attend to changes in either the top (white) or the bottom
(yellow) part of a blocked figure. The critical finding of the study was that a facilitated
performance was found for the body position task, but not for the object position condition.
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These results indicate that the body schema is used to encode body position for both the self and
others. This cognitive representation of body position is separate from representations used to
remember the positions of objects.
In accordance with the earlier behavioral findings, neurophysiological evidence now
confirms that a number of cortical regions may be involved in the processing of bodies.
However, the perception of bodies, like that of faces, evokes a consistent and selective pattern of
neural activity within the extrastriate visual cortex (extrastriate body area- EBA). Using fMRI,
Downing and colleagues (2001) found a region in the lateral occipitotemporal cortex which
yielded a significantly stronger response when subjects viewed images of human bodies and
body parts. This region was less active when viewing animals, and least active during the
perception of inanimate objects such as tools, suggesting a dominance for the processing of
bodies – in particular human bodies (see Peelen & Downing, 2007 for a review). The
neuroimaging evidence for a specialization of the EBA for human body recognition is strongly
supported by complementary evidence that functional interference with neural activity in the
EBA impairs visual processing of human bodies. Temporary inactivation of the EBA with
repetitive transcranial magnetic stimulation (rTMS) selectively impairs discrimination of bodies
but not faces or objects on delayed matching-to-sample visual tasks (Urgesi, Berlucchi &
Aglioti, 2004; Pitcher, Charles, Devlin, Walsh & Duchaine, 2009).
The discovery of the EBA has brought about much clarity in understanding how
individuals perceive the dynamic spatial organization amongst body parts for both the self and
others. However, more research is needed to fully capture an understanding of the body in the
brain. Specifically, questions have been raised as to whether the EBA may respond differentially
to signals from one’s own body and signals from other bodies. Experimental evidence related to
this question is conflicting. Recent fMRI studies by Hodzic and colleagues (2009) show no
differential activation to the presentation of unfamiliar or familiar bodies, including one’s own
body. Other studies have suggested that the EBA is activated more by allocentric than egocentric
views of body parts (Chan, Peelen, & Downing, 2004; Sax, Jamal, & Powell, 2006). Clearly,
although the EBA seems to be preferentially activated during the viewing of human bodies,
aspects of the EBA in the human cortex are still in need of further exploration.
11
1.4.1 Body Schema Development
The body schema is plastic and can be shaped by influences of experience (Berlucchi &
Aglioti, 1997). Specifically, the body schema is thought to develop progressively throughout
childhood and adolescence (Assaiante, Barlaam, Cignetti, & Vaugoyeau, 2014) and improves
through its interactions with the environment and other people. Some developmental studies
have reported that the postural body schema matures later in childhood, from 8 to 10 years old
(Eliasson, Forssberg, Ikuta, Appel, Westling, & Johansson et al. 1995; Schmitz, Martin,
Assaiante, 2002; Assaiante, Mallau, Viel, Jover, & Schmitz, 2005; Cignetti, Chabeauti,
Sveistrup, Vougoyeau, & Assaiante, 2013; see Assaiante et al., 2014 for a review). It appears
that the postural body schema is not fully mature at the age of 8 years of age (Schmitz et al.,
2002). Indeed, a study involving anticipatory postural perturbations involving a bimanual load-
lifting task reported that children as old as 8 years of age had difficulty mastering the
coordination between the arm executing the unloading and the stabilization of the postural
forearm position to allow for an effective grasping of the object (Schmitz et al., 2002). Further,
in a sit-to-stand and back-to-sit task with changes in support surface inclination, children aged 7
to 10 years of age partially adapted their motor strategies in accordance with the tilt surface. The
children’s strategies were not as effective as those of the adults when trying to improve vertical
truck orientation (Cignetti et al., 2013). Thus, despite a partial adaptation, it appears that the
updating of the postural body schema is a process that matures progressively throughout
childhood.
However, it appears that adolescent representations are still far from equaling those of
adults. Specifically, adolescents have been shown to transiently neglect proprioceptive feedback
and over-use visual information to regain postural control as compared to adults when
experiencing slow oscillations (Cignetti, Chabeauti, Vougoyeau, & Assaiante, 2013). Thus, the
body schema continues to mature with development as the body kinetics and brain associations
transition from childhood to adolescence and consolidate in adulthood (Assaiante, et al., 2014).
In particular, changes in cortical development have been associated with the elimination of
unused synapses and a simultaneous myelination of relevant fiber tracts during this period and
stabilizing in early adulthood (Gogtay et al., 2004; Barnea-Goraly et al., 2005). Thus,
fluctuations in cortical development and body kinematics in both childhood and adolescence may
parallel changes occurring in body schema maturation during development.
12
1.4.2 Summary
The identification of body-related cortical areas, such as the EBA, have brought
considerable clarity in linking theoretical conceptual representations of the self and other with
other evidence grounded in the bodily experience. The correspondence between the self and
others may be achieved by identifying the body parts of others and matching those to the
representation of one’s own body parts in the brain. This matching process might allow one to
create a shared neural representation between the self and other. Note, however, that the body
representation of children and adolescents may not be fully developed as both cortical and body
kinematic fluctuations stabilize in adulthood. Although the preceding section reviewed evidence
in favour of general body processing areas, the following section will consist of a review of
behavioural studies that support this self-other body mapping process.
1.5 Body-Part Compatibility
A number of recent studies have assessed the behavioural implications associated with
adult interpersonal body representation. For example, Thomas, Press, and Haggard (2006)
studied adult subjects’ response to a tactile (vibration) stimulus on their own bodies after viewing
a corresponding visual cue on an adult model’s body. Tactile detection was facilitated when the
visual cue was presented on the homologous body part of the observer. Similarly, Bach and
colleagues (2007) found that response times (RT) for finger and foot responses were shorter
when targets were presented over homologous body sites as opposed to another body part of a
model. Specifically, the researchers had participants view static and dynamic images of a model
that had red or blue coloured targets superimposed on the hand, foot, or head. The participants
were instructed to respond with a finger press to a blue target and a foot pedal press to red target
regardless of where it was presented. They found that when there was compatibility between the
target placement on the model’s body and the responding effector of the participant (e.g., blue
target on the hand or red target on the foot), shorter RTs were recorded than when the target was
in another location. That is, finger and foot responses were shorter when the blue or red targets
were presented over the hand and feet, respectively, then when the targets were presented on
another body part of the model. Consistent with Reed and Farah (1995), the authors of these
studies suggested that these body-part compatibility effects emerged because viewing and
attending to homologous body sites of another person can automatically increase the activation
13
and sensitivity of perceptual and motor areas representing that body part in the body schema.
This body-part specific activation subsequently primes and facilitates responses involving the
same body sites of the viewer, and/or perhaps causing interference when the individual needs to
respond with a different limb.
Interestingly, self-other matching can occur between humans and nonhuman mammalian
animals (Pacione & Welsh, in press; Welsh, McDougall, & Paulson, 2014). Following an
adaption of Bach et al. (2007) study, these studies used the body-part compatibility task to assess
the mapping of the fore- and hindlimbs of nonhuman animal bodies on to the homologous limbs
of the human body schema. The results revealed body-part compatibility effects when mammals
(i.e., bears, monkeys, meerkats) were observed in a bipedal posture, but not these same mammals
are in a quadrupedal posture. However, when crossing taxonomical “classes” to include reptilian
and aves images, no limb compatibility effects were observed when the animals (i.e., lizard,
penguin, owl) were in a bipedal posture. Thus, there may be sensitivity in the body schema to the
characteristics (and perhaps class/group) of the body in the observed image.
A fundamental concern that has emerged in the literature is whether these body-part
compatibility effects are modulated by (or are completely due to) pre-existing stimulus-response
spatial compatibility effects (Umilta & Nicoletti, 1990). In typical S-R compatibility tasks,
responses to stimuli are faster if the stimulus is on the spatial orientation (e.g., side of space) as
the responding effector (Simon, 1969). In tasks involving body-part compatibility involving foot
and hand responses, spatial compatibility effects can extend to whole body frames whereby a
hand response is facilitated for “high” target locations and foot responses are facilitated for
targets at “low” spatial locations (Nicoletti & Umilta, 1984, 1985). Thus, because the targets on
the hands and feet of the model are high and low in the display, the spatial and body-part
compatibility effects are confounded.
To address this issue, Wiggett and colleagues (2011) directly investigated whether the
associations learned between executing body actions and observing body actions constitute a
unique kind of association, or whether they were more generalized to spatial codes. Using an
incongruent effector training task, they compared body action priming effects with spatial action
priming effects. Specifically, they presented participants with images of a hand and a foot that
lifted, or two circles that changed in size. The participants were instructed to focus on a letter
14
that was presented in the centre of the screen and ignoring the other stimuli by lifting either their
hand when they saw the letter “H” or their foot when they saw the letter “F”, respectively. The
study had priming conditions in which the letters and the task-irrelevant stimuli were compatible
(e.g., the letter F presented with a foot lift), or incompatible (e.g., a letter F presented with a hand
lift). To be comparable with the body conditions, where a hand is normally positioned above the
foot, the shape conditions were organized such that a hand movement was denoted with a change
in the top circle, while a foot movement was denoted with a change in the bottom circle.
Spatially compatible (e.g., the letter F presented with a change in the bottom circle), or
incompatible (e.g., a letter F presented with a top circle change) conditions were also presented.
Following the priming phase, participants were divided into training groups (i.e., body
compatible, body incompatible, shape compatible, or shape incompatible). In the compatible
groups, the participants’ actions were consistent with the subsequent visual feedback from the
stimuli and in the incompatible groups, participants’ actions were inconsistent with the
subsequent visual feedback from the stimuli. The authors found that action-perception
associations that are related to the body do not appear to generalize to spatial priming effects,
even with specific training. Specifically, the priming effect associated with viewing body parts
was smaller for those who received the incompatible training with body stimuli. In contrast, the
priming effect elicited by spatial compatibility was not modulated by training. That is, there was
no difference between the compatible and the incompatible groups who received training on the
shape stimuli. Additionally, learning effects did not transfer to other domains. For example,
shape incompatible spatial training had no effect on subsequent body compatibility priming
effects. The authors thus concluded that associations between executing and observing body
actions constitute a special kind of learned association.
Additionally, Catmur and Heyes (2011) attempted to determine if spatial and body-part
compatibility effects were independent by assessing the time courses of spatial and body-part
compatibility effects. They had participants complete a choice reaction time task, in which they
responded to coloured targets that were placed either on the index or little finger of a hand
model. Participants were instructed to make an abduction movement of either the index or the
little finger according to the specific colour illuminated. The coloured target was followed by a
task-irrelevant abduction movement of either the index or the little finger movement of the hand
model. The study had testing conditions in which spatial and body frames of reference were
15
aligned and situations where these were in opposite. Using a quintile analysis in which they
binned the RTs in the shortest to longest fifths, the authors were able to assess the magnitudes of
the spatial and body compatibility effects at different points during the course of a trial. The
authors reported that spatial compatibility effects were present in the early stages of a trial and
body compatibility arose later in the trial. These results indicate that spatial and body
compatibility effects display different time courses across a set of trials and, hence, are likely due
to independent mechanisms.
Finally, Wiggett and colleagues (2013) compared spatial and body compatibility effects
across the whole body, using hand and foot responses. They presented task-irrelevant hand and
foot priming stimuli and had participants make hand and foot responses to letters that were
presented in the centre of the screen. Additionally, the authors manipulated the location of the
hand and foot on the screen, placing the hand above the foot on half the trials and reversing the
placement in the other half. Consistent with Catmur and Heyes (2011), the results revealed
different time courses for spatial and body priming effects, with spatial compatible effects
appearing earlier in a trial. Interestingly, the effects of hand/foot location on screen are primarily
found for foot, but not hand responses. Foot responses appear to be more efficient when the body
part location matches the anatomy of the participant compared to when it does not. Taken
together, the results of these studies suggest that both spatial and body compatibility effects exist,
operating simultaneously over separate time courses. The neural systems mediating the spatial
and body compatibility effects are likely different, with body part identity in regions of the EBA
(e.g., Downing et al., 2001; Peelen & Downing, 2007) and egocentric spatial location involving
different cortical regions. The task of resolving response conflict to enable selective action is
likely common to both situations and it is these interactions between the two frames of reference
that will take place in common neural (motor) structures.
1.5.1 Summary
Body-part compatibility tasks appear to be an effective tool to assess self-other matching
and potentially, the involvement of the human body schema in social cognitive processes. Based
on the current data, it has been suggested that seeing another person’s body part leads to an
activation of the representation of that body-part in the body schema of the viewer. This body-
part specific activation subsequently primes and facilitates responses involving the same body
16
sites of the viewer. The correspondence that is achieved between identifying the body parts of
others and matching those to the representation of our own body parts in the brain, allows one to
create a shared neural representation between the self and other. Thus, it is thought that the
processes that lead to the body-part compatibility effect are those that support the human ability
to empathize with, mimic, and understand the actions of other humans. In tasks involving body-
part compatibility, spatial compatibility effects can extend to whole body frames, however,
spatial and body- part compatibility effects appear to operate simultaneously using relatively
independent mechanisms. Overall, the research focus of these studies has centered on the
processes underlying the ability of the adult human to represent the bodies and actions of other
adult humans. Thus, the body-part compatibility task may be well suited to explore the
ambiguities surrounding body representation in children and adolescents.
1.6 Conclusion
Social functions, such as planning one’s own behaviour in a group, anticipating one’s
own and others’ behaviours, and empathizing with others appears to rely on people’s ability to
match the bodies and actions of the others to the representations used to perceive and act the self.
Action-perception mechanisms are thought to facilitate such complex interactions because the
neural codes that are responsible for generating actions are tightly coupled to the codes that
represent the perceptual consequences of those actions (Hommel, 2009; Prinz, 1997). These
representations not only guide one’s own behaviour, but are also used to interpret the behaviour
of others. This action-perception coupling mechanism offers a functional bridge between actions
produced by the self and those produced by others.
Additionally, this ability to understand others is fundamentally enriched by a distributed
neural network that encompasses shared self-other representations (Gallese, 2001). These shared
representations are created when one registers the perceptions and thoughts of others against the
neural representations used to perceive the self. This process asserts that the self and other are
intricately tied together (Lombardo et al., 2010). By means of action simulation, the actions of
another individual could be mapped onto the stored sensory predictions of one’s own actions
(Blakemore & Decety, 2001). Self-other equivalence is particularly relevant for pre-adolescent
and adolescent populations who strive to conform to own-age group norms.
17
This intricate relationship between the self and the other has been recently underlined by
theorists of embodied cognition according to which bodily and action experiences play a primary
role in human cognition - cognitive processes are essentially grounded in bodily states (Gallese
& Sinigaglia, 2011). What makes the behaviour of other agents intelligible is the fact that their
body is experienced as something analogous to one’s own experienced body. This
correspondence is achieved by identifying the body parts of others and matching those to the
representation of one’s own body parts in the brain (Blakemore & Decety, 2001; Jackson &
Decety, 2004; Berlucchi & Aglioti, 2010).
An effective tool to assess self-other matching at the level of the body is the body-part
compatibility task (Bach et al., 2007; Welsh et al., 2014; Pacione et al., in press). Observing a
body or body part is thought to lead to body-part specific activation in the body schema, which
subsequently primes and facilitates responses involving the same body sites of the viewer (Bach
et al., 2007; Reed & Farah, 1995). The correspondence that is achieved between identifying the
body parts of others and matching those to the representation of one’s own body parts in the
brain, allows one to create a shared neural representation between the self and other. Thus, the
body-part compatibility task may be well suited to explore the ambiguities surrounding body
representation in a number of different populations, including children and adolescents.
1.7 The Current Project: Purpose and Specific Hypotheses
The purpose of the present study is to investigate the integrity of mechanisms underlying
the ability to represent the bodies of other humans (i.e., self-other matching) in typically
developing (TD) children and adolescents. To investigate these processes, I will evaluate the
performance of TD individuals using a human body-part compatibility task which provides an
index of the body-part matching process (e.g., Bach et al., 2007; Welsh et al., 2014; Pacione et
al., in press). This information can be used to understand the cognitive underpinnings of how
one’s own body influences one’s perception of others’ body representations.
To this end, participants of different ages will complete a body-part compatibility task in
which targets will be presented over static images of a 7, 11, and 15 year old male model.
Coloured targets will be superimposed over the hand or foot of the models. Participants will be
instructed to execute a left or right key press to red or blue coloured targets, respectively.
18
If the bodies in the images are mapped onto the human body schema of the observer, then
a body-part compatibility effect will be observed and RTs will be shorter when the stimulus is
presented on the compatible body parts (e.g., red stimulus on the hand) than on incompatible
body parts (e.g., red stimulus on the foot) (as in Bach et al., 2007; Welsh et al., 2014; Pacione et
al., in press). If the bodies in the images are not mapped onto the human body schema of the
observer (or if the body schema is not sufficiently developed in the observer), then no body part
compatibility effects will be observed and there will be no differences between RTs to stimuli
presented on the different body parts. With respect to the main research question, it is further
predicted that if children and adolescents of all ages engage in self-other mapping with people of
all ages, then they will be able to map the bodies of all the images onto the human body schema
and body-part compatibility effects will be observed in all cases. Alternatively, if the children
and adolescents resonate most with the bodies of the images that share similar characteristics and
age (i.e., their peer group), then age specific body-part compatibility effects will be observed. In
this latter scenario, body-part compatibility effects will only be observed with the 7 year old
model type for children in the 7 to 9 year old age group. For children in the 10 to 12 year old age
group, body-part compatibility effects will only be observed with the 11 year old model type.
Finally, body-part compatibility effects will only be observed with the 15 year old model type for
adolescents in the 13 to 16 year old group.
19
Chapter 2 Research Article
2.1 Introduction
In daily life, humans are constantly interacting with other people - be it helping a child
grab a glass off a high shelf or talking with neighbours. Adults are able to identify with the
bodies and actions of others in order to engage in a shared experience of the world. This is
particularly true when an adult is asked to pass a jug of water to a child. The adult must consider
if the child can manage the weight of the object, thus identifying with the child’s body. One of
the processes that is thought to facilitate this complex ability of understanding others is one in
which humans register the perceptions and thoughts of others against the neural representations
used to perceive the self. Evidence for self-other mapping comes from different sets of studies
revealing a facilitatory effect in responses to observing body parts in static (e.g., Bach, Peatfield,
& Tipper, 2007; Thomas, Press, & Haggard, 2006) and dynamic (e.g., Brass, Bekkering, &
Prinz, 2001; Catmur, & Heyes, 2011; Wiggett, Downing, & Tipper, 2013; Wiggett, Hudson,
Tipper, & Downing, 2011) displays. For example, Bach et al. (2007) studied the response times
of adults to coloured targets that were superimposed over an adult model’s body. They found that
response times (RT) for finger and foot responses were shorter when targets were presented over
the hand and feet, respectively, of an adult model than when the targets were presented over
another body part of the model (see also Jovanov et al., 2015; Thomas et al., 2006). The authors
suggested that these body-part compatibility effects emerged because viewing and attending to a
target on homologous body sites can automatically increase the activation and sensitivity of
perceptual and motor areas representing that body part in the observer’s body schema. This
body-part specific activation subsequently primes and facilitates responses involving the same
body sites of the viewer, or interferes with responding when the response involves a different
limb.
Overall, the findings of studies exploring this body-part compatibility effect are
consistent with research that has centered on the cognitive and neural processes underlying the
ability of the adult human to represent the bodies and actions of other adult humans (e.g., Ogden,
1985; Peelen & Downing, 2007; Reed & Farah, 1995; Sirigu, Grafman, Bressler, & Sunderland,
1991). Evidence for this ability to code body parts was initially derived from neuropsychological
20
studies that revealed that humans possess a body schema or a mental construct devoted to the
dynamic spatial organization amongst parts of the body of the self and its relations to that of
other bodies (Semenza & Goodglass, 1985; Semenza, 1988; Ogden, 1985; Sirigu, Grafman,
Bressler, & Sunderland, 1991). It is thought that a body representation (or schema) is used for
the unconscious encoding of body position for both the self and others and this cognitive
representation is separate from representations used to remember the positions of objects (Reed
& Farah, 1994). In accordance with the earlier behavioral findings, neurophysiological studies
suggest that a consistent and selective pattern of neural activity within the extrastriate visual
cortex (extrastriate body area [EBA]) is evoked during the perception of bodies (Downing et al.,
2001). The EBA exhibited a significantly stronger response when subjects viewed images of
human bodies and body parts. It became less active when viewing animals, and least active
during the perception of inanimate objects such as tools, suggesting a dominance for the
processing of bodies – in particular human bodies (see Peelen & Downing, 2007 for a review).
Thus, this research indicates that the body schema can encode body parts of both the self and
other. It is thought that this body schema is what supports self-other matching, at least with
respect to body parts.
It is important to note here that the research reported above has focused on these
processes in adults. The processes leading to the child and adolescent’s ability to understand the
bodies of other children and adolescents has, to our knowledge, received no direct experimental
attention. The present study was conducted to provide some initial insights into the complex
child-to-child social cognitive process of body-part matching.
Although no research, to our knowledge, has explored body schema use in self-other
matching in this manner, there has been some research related to the development of the body
schema for understanding the self. Investigations of the developing body schema of the self in
childhood and adolescence have centered on transiently disturbing sensory information, in
particular proprioceptive and visual messages, during sit-to-stand, tendon vibration, and illusory
motion tasks (Eliasson, Forssberg, Ikuta, Appel, Westling, & Johansson et al. 1995; Schmitz,
Martin, Assaiante, 2002; Assaiante, Mallau, Viel, Jover, & Schmitz, 2005; Cignetti, Chabeauti,
Sveistrup, Vougoyeau, & Assaiante, 2013; see Assaiante et al., 2014 for a review). These studies
have highlighted the plasticity of the developing postural body schema, focusing specifically on
how the individual perceives the self through transient postural disturbances. Overall, these
21
studies have centered on examining the development of the postural body schema from an
intrapersonal frame of reference. Specifically, the body schema is thought to develop
progressively throughout childhood and adolescence, with some developmental studies reporting
that the body schema matures later, from 8 to 10 years old (Eliasson, Forssberg, Ikuta, Appel,
Westling, & Johansson et al. 1995; Cignetti, Chabeauti, Sveistrup, Vougoyeau, & Assaiante,
2013). Thus, as the body kinetics and brain associations transition from childhood to
adolescence and consolidate in adulthood, the body schema is thought to continue to mature with
development (Assaiante, et al., 2014). However, despite a body of work on the individual
development of the postural body schema, little work has examined the interpersonal interactions
between children, specifically, the development of associations created between children’s own
bodies and the bodies of other children.
Although the emergence of body-part compatibility effects occurring during adult-to-
adult interactions suggests that self-other body-part matching occurs in adults, researchers have
yet to examine these effects in child and adolescent populations. This gap in the literature has
emerged despite the fact that childhood and adolescence would seem to be a time of particular
relevance for studying the development of intra- and inter-body representations. The transition
from middle childhood to late childhood and adolescence involves a great deal of peer
socialization. Children may have a preference for members of their own age groups who share
similar behaviours, interests, and activities (Abrams, Rutland, Cameron, & Marques, 2003).
Older children and adolescents are more self-conscious of their self-presentation and may strive
for consistency with their own age peers in order to conform to in-group norms and avoid own-
age group segregation (Abrams, Rutland, Cameron, & Ferrell, 2007; Martin, Fabes, & Hanish,
2014). Similarly, indirect investigations exploring the effect of viewing peer versus adult model
stimuli have yielded parallel results. Specifically, Marshall and colleagues (2010) found stronger
motor contingent effects when children observed dynamic images of their own peer than an adult
model (see also Liuzza, Setti, & Borghi, 2012).
The purpose of the present study is to investigate the integrity of mechanisms underlying
the ability to represent the bodies of other humans (i.e., self-other matching) in typically
developing (TD) children and adolescents. To this end, participants will complete a body-part
compatibility task while viewing static images of a 7, 11, and 15 year old male model.
Participants will execute left or right key presses to red or blue targets, respectively, which will
22
be presented on the hand or foot of the model. If the bodies in the images are mapped onto the
human body schema of the observer, then a body-part compatibility effect will be observed and
RTs will be shorter when the stimulus is presented on the compatible body parts (e.g., red
stimulus on the hand) than on incompatible body parts (e.g., red stimulus on the foot) (as in Bach
et al., 2007; Welsh et al., 2014; Pacione &Welsh, in press). If the bodies in the images are not
mapped onto the human body schema of the observer, then no body part compatibility effects
will be observed and there will be no differences between RTs to stimuli presented on the
different body parts. Additionally, it is further predicted that if the individuals are able to map the
body-parts of all the images onto their own body schema, then body-part compatibility effects
will be observed in all cases. Alternatively, if the individuals resonate most with the bodies of the
images that share similar characteristics and age (i.e. their peer group), then age specific body-
part compatibility effects will be observed.
2.2 Methods
2.2.1 Participants
Forty-one typically developing children (32 males, 9 females; mean age = 11.3 years old;
range = 7-16; SD = 2.86) volunteered to take part in the study with their parents/guardians
providing informed consent prior to beginning data collection. For their participation, all children
were financially compensated ($10). An additional two children were recruited, but their data
were excluded due to an inability to complete the task. All participants completed abbreviated
versions of the Edinburgh handedness inventory to assess hand dominance and the Ishihara
colour plates 38 set to ensure that none of the children were colour blind. Two of the children
were left-hand dominant, two were ambidextrous, and the remaining 37 were right-hand
dominant. All participants were naïve to the purpose of the study.
The protocol was completed in a single session that lasted 30-45 minutes. The procedures
were consistent with the codes of the Declaration of Helsinki and were approved by the
University of Toronto Research Ethics Board.
2.2.2 Apparatus, Task, and Procedure
A group of participants (n= 31) performed the task in a laboratory where they sat in a
chair at a desk approximately 70 cm away from a computer screen. All stimuli were presented
23
on a 16” LCD screen. A second group of participants (n= 10) performed the task at home, where
the experimenter projected the program from a laptop to a 16” LCD computer monitor. The same
experimenter oversaw the testing in both sites. Stimuli consisted of real-life profile colour
pictures of three male models - a ~7 year old child, a ~11 year old child, and a ~15 year old
adolescent in a standing posture (see Figure 2.1). The models all wore similar clothes (jeans and
a plain black t-shirt). These 3 images were flipped horizontally such that each of the images was
presented in a rightward and leftward profile orientation (i.e., a total of 6 images were used). The
images of each model were carefully selected amongst a series to match the other images on
perspective, hand and feet position, and head and eye orientation as closely as possible. The
images presented displayed all limbs and the whole face from a frontal view, with the face and
eye gaze directed at the participant.
Each body was digitally extracted from the original environment and positioned on a
neutral white background. The figures were separated from their environment to prevent
irrelevant information in the background from distracting the participants and to highlight the
target stimuli. Each image varied in height to reflect the differences in age. The 7 year old model
was the shortest (17 cm [h] x 7 cm [w]), followed by the 11 year old model (18.5 cm [h] x 8 cm
[w]) and the 15 year old model was the tallest (20.5 cm [h] x 9.5 cm [w]).
A single target was presented on each picture. The target was a blue or red circle (1 cm
diameter) that was superimposed over one of the most distal structures (hand or foot) of the
models. Blue and red circles were presented equally often on the different limbs. Because the
relative proportions of the different bodies differed slightly, the specific location of each target
for each model condition differed slightly. For the 7 year old model, targets appearing on the
hand were 11 cm from the bottom of the screen. Targets appearing on the foot appeared 4.5 cm
from the bottom of the screen. For the 11 year old model, the targets appearing on the hand
appeared 10.5 cm from the bottom of the screen and the targets appearing on the foot appeared
3.5 cm from the bottom of the screen. For the 15 year old model, the targets appearing on the
hand appeared 11.5 cm from the bottom of the screen and the targets appearing on the foot
appeared 3 cm from the bottom of the screen. The images were also equally presented in a
rightward or leftward profile orientation, such that the targets appeared equally as often on the
right and left limbs.
24
Figure 2.1. Examples of the 7, 11, and 15 year old models with coloured targets. Only a single
image was presented on each trial. The black boxes surrounding each image were not presented
in the experiment, but were included here to demonstrate the different sizes and proportions of
the images.
Further, two images were created by digitally removing the model body from the
coloured targets (see Figure 2.2). An upper and lower coloured target image was presented,
which roughly represented the locations of the hand and foot target positions on the model
bodies, respectively. Targets appearing in the upper space were 11 cm from the bottom of the
screen. Targets appearing in the lower space appeared 3.5 cm from the bottom of the screen.
These two images were flipped horizontally such that each of the images was presented in a
rightward and leftward spatial orientation (i.e., a total of 4 images were used). Blue and red
circles were presented equally often at the upper and lower spatial locations.
25
Figure 2.2. Examples of the coloured targets in lower and upper space. The black boxes
surrounding each image were not presented in the experiment, but were included here to
demonstrate the different locations of the targets in the trials.
The task consisted of a two-choice hand response task. Participants placed their left
index finger over the “z” key and their right index finger over the “3” key on the number pad of a
standard English language keyboard. Participants were told to press the “z” and “3” keys with
their index fingers as soon as possible when a red or blue circle, respectively, was recognized in
the picture. Instruction screens that outlined the task were presented prior to each block in a
black font on a white background. A custom program written using E-Prime (2.0) software
controlled the presentation of the experimental stimuli and recorded the timing and identification
of the responses.
There were two main tasks in the study – a spatial compatibility and a body-part
compatibility task. The spatial compatibility task was conducted to ensure that the participant
could follow instructions and complete the basic task. The data from this task were also
analyzed to test for any pre-existing upper or lower spatial compatibility effects. The spatial
compatibility task consisted of a block of 24 trials of the choice response task with the images of
the upper and lower coloured targets. There were no bodies in the spatial images (see Figure
2.2). The 24 trials in this spatial compatibility block consisted of three instances of each image
(the factorial combination of target [red, blue], spatial field [upper, lower], and orientation [left
or right]) presented in random order.
26
Following the spatial compatibility task, a familiarization session of six randomized trials
with images that included the models was presented before completing the body-part
compatibility task. The body-part task consisted of five blocks of 24 trials of the choice response
task with the model images. The 24 trials in each block consisted of a single instance of each
image (the factorial combination of target [red, blue], model [7 year old, 11 year old, 15 year
old], limb [hand, foot], and orientation [facing left or right]) presented in a random order within
each block.
At the beginning of each trial, the word “READY” was presented 8 cm from the bottom
of the white screen with black font; a location that was roughly equidistant between the potential
location of a hand or foot target. The experimenter advanced the “READY” cue for each trial
when she was confident the participant was focused on the task and ready to complete a trial.
Following the “READY”, a black fixation cross was positioned at the same location to direct and
maintain attention to the lower portion of the screen during the foreperiod. Target images were
presented randomly 1000-3000 ms after the presentation of the fixation cross to discourage
anticipation. The picture was positioned such that the targets were equidistant from the
“READY” and fixation cross and the feet of the models were 3-4 cm from the bottom of the
screen.
2.3 Results
The children were divided into three groups for analysis (7 to 9: n = 13; 10 to 12: n = 14;
13 to 16: n = 14). Two main sets of analyses, one on the spatial compatibility and one on the
main body-part compatibility data, were conducted to address specific theoretically-relevant
questions.
2.3.1 Spatial Compatibility
RT data for the spatial compatibility trials on which the participant executed the wrong
response (e.g., a right hand response, instead of a left hand response, for a red target) were
eliminated (4.6% of all trials) (see Table 2.1). After the wrong response trials were removed,
RTs were collapsed across side of space within the upper and lower spatial trial types to create a
mean RT value for upper and lower fixation for each participant. Mean RTs for the spatial
compatibility task were submitted to a 3 (Group: 7 to 9, 10 to 12, 13 to 16) by 2 (Spatial Height:
27
Upper, Lower) mixed ANOVA with repeated measures on the last factor. Alpha was set at 0.05
for all tests. All significant effects are reported.
No significant main effect of Spatial Height was found, F (1, 38) = 0.578, MSE =
2,640.53, p = 0.452, ηp2 = 0.015. A significant effect of Group was found, F(2, 38) = 18.26, MSE
= 25,342.12, p<0.001, ηp2 = 0.49. Planned comparisons were conducted by collapsing the RTs of
all the trial types for each participant. The analysis revealed that the mean RTs for the 13 to 16
year old group (M = 483 ms, SD = 79) were significantly shorter than that of both the 10 to 12
year old group (M = 637 ms, SD = 121), t(26) = 3.99, p<0.001, and the 7 to 9 year old group (M
= 743 ms, SD = 133), t(25) = 6.24, p<0.001. The mean RTs for the 10 to 12 year old group were
also significantly shorter than the 7 to 9 year old group, t(25) = 2.17, p = 0.04.
Of greater theoretical relevance, there was no significant Group by Spatial Height
interaction, F(2, 38) = 0.628, MSE = 2,640.53, p = 0.539, ηp2 = 0.032. Overall, the results reveal
no pre-existing upper or lower spatial field effects amongst the upper and lower coloured stimuli.
Thus, any body-part compatibility effects that may emerge with the body-part compatibility task
are not likely to be modulated by pre-existing upper or lower spatial effects.
Table 2.1. Mean (and standard deviations) of the % of response errors as a function of
Presentation Side, Responding Effector, and Spatial Height.
Presentation Side
Spatial
Height
Effector Upper Lower
Left Side
Left Hand 2.44 (8.79) 3.25 (10.01)
Right Hand 5.69 (12.70) 9.76 (15.35)
Right Side
Left Hand 4.06 (11.04) 6.50 (13.37)
Right Hand 1.62 (7.26) 3.25 (10.01)
28
2.3.2 Body-Part Compatibility
RT data for the test trials on which the participant executed the wrong response were
eliminated (3.1% of all trials). After the RTs for the wrong response trials were removed, the
data were collapsed across right/leftward orientation and a mean and standard deviation for each
participant, for each limb condition (hand, foot) were derived. Trials where no response was
recorded and those that were greater than 3 standard deviations above the mean for a condition
for each individual were considered outliers and were deleted (1% of all trials). Overall, 4.1% of
all trials were deleted as anticipation error (defined as RTs shorter than 100 ms), inattention
errors, wrong responses, no responses, or outliers. Table 2.2 displays the execution errors
(incorrect responses) across each limb condition.
Table 2.2 Mean (and standard deviations) of the % of response errors as a function of
Presentation Side, Responding Effector, Model Type, Target Location.
Mean RTs for the test stimuli were submitted to a 3 (Group: 7 to 9, 10 to 12, 13 to 16) by
3 (Model: 15 year old, 11 year old, 7 year old) by 2 (Target Location: Hand, Foot) mixed
ANOVA with repeated measures for the last two factors. Planned comparisons were conducted
during the post-hoc analyses. Alpha was set at 0.05 for all tests. All significant effects are
reported.
Presentation
Side
Model Type
7 Year Old 11 Year Old
15 Year Old
Effector Hand Foot Hand
Foot
Hand
Foot
Left Side
Left Hand
0.49
(3.12)
0.49
(3.12)
0.49
(3.12)
1.46
(6.91)
2.44
(6.62)
1.46
(5.27)
Right Hand
3.90
(9.19)
3.90
(9.19)
6.34
(11.34)
5.36
(8.98)
4.89
(11.64)
5.85
(9.21)
Right Side
Left Hand
3.90
(8.02)
4.89
(9.78)
6.34
(11.34)
4.39
(8.38)
4.39
(10.5)
4.39
(8.38)
Right Hand
0.49
(3.12)
1.46
(5.27)
2.44
(6.62)
2.93
(8.44)
0.97
(4.36)
0.49
(3.12)
29
The analysis of RTs revealed a trending main effect of Target Location, F (1, 38) = 3.27,
MSE = 1,753.24, p = 0.07, ηp2 = 0.079. Overall, RTs were shorter to targets presented on the
hand (M = 686 ms, SD = 171) than for targets on the foot (M = 695 ms, SD = 179). A significant
effect of Group was also found, F(2, 38) = 23.42, MSE =84,796.62, p<0.001, ηp2 = 0.552.
Planned comparisons were conducted by collapsing the RTs of all the trial types for each
participant. Table 2.3 and 2.4 outline the associated group descriptive statistics and the planned
comparisons across the three groups.
Group 7 yr. Model
Hand Foot
11 yr. Model
Hand Foot
15 yr. Model
Hand Foot
Group
Mean
7 to 9 847 (95)
838 (118)
815 (99)
846 (138)
830 (116)
855 (134)
839 (108)
10 to 12 713 (144)
702 (139)
706 (144)
740 (148)
716 (159)
712 (152)
715 (144)
13 to 16 525 (100)
523 (96)
535 (110)
530 (107)
514 (85)
543 (112)
528 (99)
Condition
Means
691 (175)
684 (174)
682 (165)
702 (185)
683 (179)
700 (183)
Table 2.3. Mean (and standard deviation) response times in milliseconds for each of the three
Groups as a function of Model Type and Target Location. Marginal means are also provided.
Pair t df Sign. (2-tailed)
7 to 9 vs. 10 to 12 2.51 25 .019*
10 to 12 vs. 13 to 16 3.99 26 <.001*
7 to 9 vs. 13 to 16 7.77 25 <.001*
Asterisks indicate significant difference between groups, p <.05 *.
Table 2.4. Planned comparison of response time differences across the three age groups.
30
Of greater theoretical relevance, there was a significant Model by Target interaction, F(2,
76) = 3.35, MSE = 1,376.21, p = 0.04, ηp2 = 0.081. Planned comparisons for the 2-way
interaction revealed no significant body-part compatibility effects when viewing the 7 year old
model type, t(40) = 0.88, p = 0.380. Significant body-part compatibility effects were found when
viewing both the 11 year old, t(40) = 2.07, p = 0.04, and 15 year old, t(40) = 2.10, p = 0.04,
model types.
Although the 3-way Group by Model by Target interaction was not significant, F(4, 76) =
1.88, MSE = 1,376.21, p = 0.12, ηp2 = 0.90, separate ANOVAs were conducted for each age
group to determine if any age-specific body-part compatibility effects emerged when viewing the
various model types (i.e., consistent with a priori prediction). The mean RT values for each
group were submitted to a 3 (Model: 15 year old, 11 year old, 7 year old) by 2 (Target Location:
Hand, Foot) repeated measures ANOVA. The results of this analysis are reported in the
following sections.
Note that the patterns of execution errors were generally consistent with the pattern of
RTs (lower errors or higher accuracy in conditions with shorter RTs) suggesting that the patterns
of RTs were not due to a speed-accuracy trade-off. Due to concerns over there being an
insufficient number of errors across the participants and the conditions to conduct a meaningful
and reliable analysis on the number of errors, an ANOVA on errors was not conducted.
2.3.2.1 7 to 9 year old Group
The ANOVA revealed that the Model by Target interaction that was significant in the
main analysis, was not significant in this age-group analysis, F(2, 24) = 1.41, MSE = 2,122.75, p
= 0.26, ηp2 = 0.105. Further, planned comparisons were conducted by averaging the RTs of all
the hand and foot trial types separately, per model type for each participant. The analysis
revealed no significant body-part compatibility effects occurring when viewing any of the three
model types- 7 year old model t(12) = 0.47, p = 0.64, d = 0.14, 11 year old model t(12) = 1.32, p
= 0.21, d = 0.41, 15 year old model t(12) = 1.64, p = 0.12, d = 0.48 (Figure 2.3). This pattern of
findings suggests that the activation or mapping of body-parts to the human body schema may be
underdeveloped. Thus, the absence of differences in RTs across the different model types
suggests that the body schema and other mechanisms associated with body representation may
not be fully developed at this stage of childhood.
31
Figure 2.3. Mean response time in milliseconds for the 7 to 9 year old group as a function of
model type and target location. Standard error of the mean bars are depicted. Note that the
response time scale is consistent across Figures 2.3, 2.4, 2.5 at 200 ms, although the ranges over
which the data are depicted are different.
2.3.2.2 10 to 12 year old Group
The ANOVA revealed a significant Model by Target interaction, F(2, 26) = 3.56, MSE =
1,168.12, p = 0.04, ηp2 = 0.215. Planned comparisons were conducted by averaging the RTs of
all the hand and foot trial types separately, per model type for each participant. Specifically, a
significant body-part compatibility effect occurred when viewing the 11 year old model type,
t(13) = 2.47, p = 0.03, d = 0.66 (Figure 2.4). No significant effects were found for either the 7
year old model type, t(13) = 0.72, p = 0.48, d = 0.19 or the 15 year old model type, t(13) = 0.26,
p = 0.80, d = 0.07. This pattern of findings suggests that the activation or mapping of body-parts
to the human body schema may be age-specific, with a facilitated response when responding to
images of one’s own peer, at least during this developmental stage.
32
Figure 2.4. Mean response time in milliseconds for the 10 to 12 year old group as a function of
model type and target location. Standard error of the mean bars are depicted. Asterisks indicate
significant difference between target locations, p <.05 *.
13 to 16 year old Group
The ANOVA for the oldest group revealed a trending, but non-significant, Model by
Target interaction, F(2, 26) = 2.83, MSE = 895.17, p = 0.07, ηp2 = 0.179. Planned comparisons
were conducted by averaging the RTs of all the hand and foot trial types separately, per model
type for each participant. Specifically, a significant body-part compatibility effect occurred only
when viewing the 15 year old model type, t(13) = 2.38, p = 0.03, d = 0.78 (Figure 2.5). No
significant effects were found for either the 7 year old model type, t(13) = 0.24, p = 0.82, d =
0.06 or the 11 year old model type, t(13) = 0.65, p = 0.53, d = 0.17. Overall, these results are
consistent with an age specific body-part hypothesis, with a facilitated response when responding
to images of one’s own peer.
33
Figure 2.5. Mean response time in milliseconds for the 13 to 16 year old group as a function of
model type and target location. Standard error of the mean bars are depicted. Asterisks indicate
significant difference between target locations, p <.05 *.
2.3.3 Correlation of Upper and Lower Spatial RTs with Body-Part RTs
Overall, the data from the test phase suggest that a body-part compatibility effect emerges
for the 10-12 and 13-16 year old groups when they are observing their peers. Although the initial
analysis of upper and lower target locations in the spatial compatibility task (reported in section
2.3.1) indicated that there was no difference between targets in these locations when the image of
the model was not present, it is still possible that spatial coding mechanisms contributed to the
patterns of body-part compatibility effects. To further analyze the effect of upper and lower
spatial compatibility on body-part compatibility, difference scores were calculated between mean
RTs for body-part (hand/foot) stimuli and mean RTs for spatial (upper/lower) height. These
difference scores were then submitted to a Pearson correlation analysis to determine if there was
a relationship between the magnitudes of the difference scores across individuals. The logic
behind this test was that if a spatial coding mechanism (and not body-part matching) was
responsible for the patterns of RTs observed in the main body-part analysis, then the magnitudes
of each individuals’ difference scores should be similar across the spatial and body-part stimuli.
It was found that the difference scores for body-part stimuli are not significantly correlated with
the difference scores of the spatial RTs for all three groups - 7 to 9 year old: r = 0.09, p = 0.77
(Figure 2.6); 10 to 12 year old group: r = -0.34, p = 0.23 (Figure 2.7); 13 to 16 year old: r = 0.10,
34
p = 0.71 (Figure 2.8). These results suggest that the body-part compatibility effects that emerged
with the body-part stimuli are likely not related to any pre-existing spatial capability effects.
Figure 2.6. Correlation of body-part difference scores from the body-part compatibility task (y-
axis) as a function of the spatial difference scores from the spatial compatibility task (x-axis) for
the 7 to 9 year old group.
Figure 2.7. Correlation of body-part difference scores from the body-part compatibility task (y-
axis) as a function of the spatial difference scores from the spatial compatibility task (x-axis) for
the 10 to 12 year old group.
35
Figure 2.8. Correlation of body-part difference scores from the body-part compatibility task (y-
axis) as a function of the spatial difference scores from the spatial compatibility task (x-axis) for
the 13 to 16 year old group.
2.4 Discussion
The purpose of the present study was to investigate the integrity of mechanisms
underlying the ability to represent the bodies of other humans (i.e., self-other matching) in
typically developing (TD) children and adolescents. Specifically, the current study sought to
examine the interpersonal interactions between children and adolescents. The findings revealed
that the limbs of children and adolescents are mapped onto the homologous representation in the
human body schema of the observing child and adolescent, but only for specific age groups and
certain stimuli. Specifically, body-part compatibility effects were found for both the 10 to 12 and
13 to 16 year old age groups. On the other hand, an absence of body-part compatibility effects
was found for the 7 to 9 year old age group when viewing any of the three model types.
Additionally, the body-part compatibility effects that emerged were not modulated by pre-
existing upper and lower spatial compatibility effects. Most interestingly, the body-part
compatibility effects that emerged for both the 10 to 12 and 13 to 16 year old age groups
occurred only when viewing models of their own peers. In sum, the results are consistent with an
age specific body-part hypothesis in that older children and young adolescents only engaged in
self-other body-part mapping with the image of an age-related peer. Finally, the absence of
differences in RTs across the different model types for the 7 to 9 year old age group suggests that
the body schema and/or other mechanisms associated with body representation and body
36
mapping may not be fully developed at this point in childhood. The following discussion will
review these results in the context of an age specificity associated with the body schema.
The results and conclusions of an age specificity associated with the body schema are
broadly consistent with the own-age bias observed in facial processing in early childhood. For
example, Anastasi and Rhodes (2005) reported that children aged 5 to 8 years old had higher
levels of facial recognition scores when viewing other child versus adult faces. These results
were confirmed by Melinder and colleagues (2010) who also found an increased amplitude of the
N170 component of the visual event related potential when children viewed child versus adult
faces (see also Hills & Lewis, 2011). Thus, the present data indicate that the own-age bias seen
in facial processing may also extend to the body schema when mapping homologous body parts
of one’s peer.
Additionally, age specific effects have been found in studies that have indirectly
compared the influence of peer versus adult models. When investigating motor resonance in
children, Liuzza and colleagues (2012) found that children responded faster when a hand prime
was of a child’s as opposed to an adult’s. In another study, Marshall and colleagues (2010)
investigated motor contagion in children. They found that the presence of background
movements made by the same-age model was associated with an increase in motor contagion
relative to the condition in which an adult was the background model. These findings lend
support for a same-age bias in body mapping with children and adolescents. Specifically, body
mapping may be facilitated when there is greater age congruency between the observers own
body and that of the observed.
Perceptions of similarity and congruency are particularly relevant for adolescents and
children in late childhood. Adolescence and pre-adolescence are time periods of great peer
socialization which has a great deal of theoretical importance for understanding the development
of intra- and inter-body representations. Specifically, the organization of schools and community
settings create own-age group segregation with children and adolescents spending large amounts
of time with same age peers (Martin, Fabes, & Hanish, 2014). Further, children and adolescents
begin to develop a preference for members of their own age groups who share similar interests,
behaviours, and activities. Finally, children and adolescents begin to strive for consistency
between the self and other as social pressure to act in accordance with one’s group and to
37
conform to the social norms of the in-group takes more of a precedence in later childhood and
adolescence (Abrams, Rutland, Cameron, & Ferrell, 2007). Thus, a heightened awareness of
one’s own body in relation to a same aged peer’s body (as observed in the present study) may be
a manifestation of these contexts and experiences. This particular importance in maintaining peer
group norms for adolescents and pre-adolescents may be due to fears of own-age group
exclusion and peer rejection (Abrams, Rutland, Cameron, & Marques, 2003).
In regards to the lack of compatibility effects found in the 7 to 9 year old age group, this
result may be due in part to an underdevelopment associated with the body schema and other
mechanisms associated with body representation. In particular, the body schema is thought to
develop progressively throughout childhood and adolescence, with some developmental studies
reporting that the body schema matures later, from 8 to 10 years old (Eliasson et al., 1995;
Cignetti et al., 2013). Thus, the large amount of variability seen in this group may reflect the
differences in the rate of progression of body representation development across different
children. Alternatively, the absence of age specific compatibility effects seen with the 7 to 9 year
old model may originate from the physically smaller size of the model’s body. Specifically, the
distance between the targets placed on the hands and feet of the model may have not been
enough spatial distance between the two targets and subsequently participants did not view them
as separate entities. Thus, it is possible that with more spatial distance between the targets, body-
part compatibility effects may have emerged. Finally, it is also possible that compatibility
effects did not emerge because the participants failed to fully understand the task, or because
they took sufficient time to resolve any particular conflicts or interference effects prior to
responding. The fact that this group had the longest RTs of all groups is consistent with either of
these possibilities. Future research may well distinguish between these alternatives.
In sum, the findings of the present study support the notion that the limbs of children and
adolescents can be mapped onto the homologous body-part representations in the human body
schema of the observing child and adolescent. Specifically, body-part compatibility effects were
found for both the 10 to 12 and 13 to 16 year old age groups. On the other hand, an absence of
body-part compatibility effects was found for the 7 to 9 year old age group when viewing any of
the three model types. It is suggested that the absence of differences in RTs across the different
model types for the 7 to 9 year old age group may be due in part to an underdevelopment
associated with the body schema and other mechanisms associated with the body representation.
38
Most interestingly, the body-part compatibility effects that emerged for both the 10 to 12 and 13
to 16 year old age groups occurred when viewing models of their own peers. In sum, the results
are consistent with an age specific body-part hypothesis, with a facilitated response when
responding to images of one’s own peer. Future work could address whether adults are more
sensitive to mapping the body-parts of other adults than of those belonging to children or
adolescents.
39
Chapter 3 General Discussion
3.1 Findings and Implications
The purpose of the present research was to investigate the integrity of mechanisms
underlying the ability to represent the bodies of other humans (i.e., self-other matching) in
typically developing (TD) children and adolescents. Specifically, it was investigated if children
and adolescents map the body parts of other children and adolescents onto their own body
schema and how the observer’s and model’s age might influence this mapping. The results
revealed that the limbs of children and adolescents are mapped onto the homologous
representation in the human body schema of the observing child and adolescent but only under
certain conditions. Specifically, body-part compatibility effects were found for both the 10 to 12
and 13 to 16 year old age groups. On the other hand, no body-part compatibility effects were
found for the 7 to 9 year old age group when viewing any of the three model types. Most
interestingly, the body-part compatibility effects that emerged for both the 10 to 12 and 13 to 16
year old age groups occurred only when viewing models of their own peers.
In sum, the results are consistent with an age-specific body-part hypothesis, with a
facilitated response when responding to images of one’s own peer. These results are broadly
consistent with the own-age bias observed in facial processing in early childhood. Specifically,
higher levels of facial recognition scores were reported when children viewed other children’s
faces (Anastasi & Rhodes, 2005; Melinder et al., 2010; Hills & Lewis, 2011). Similarly, indirect
investigations exploring the effect of viewing peer versus adult model stimuli have yielded
parallel results. In particular, separate studies on motor resonance and motor contagion reported
stronger effects when children observed dynamic images of their own peer (Marshall et al., 2010;
Liuzza et al., 2012). Taken together, the current results of the present study lend support for the
idea that body mapping, like that of facial recognition, may be facilitated when there is greater
age congruency between the observers own body and that of the observed. It is possible that
these age-specific effects arise because peer interactions at schools and community settings are
formally structured to facilitate same age interactions. Thus, the age-specific effect might have
further arisen because people of these age groups are more often exposed to and see people of a
similar age than of other age-groups. This exposure to similar aged individuals might prime or
40
otherwise enhance the efficiency with which these bodies and faces are processed relative to
others. In the end, this facilitated identification with one’s peer may be a reflection of shared
neural representations between the self and other, where the body of one’s peer is experienced as
something analogous to one’s own experienced body. Thus, this correspondence is achieved by
identifying the body parts of others and matching those to the representation of our own body
parts in the brain (Blakemore & Decety, 2001; Jackson & Decety, 2004; Berlucchi & Aglioti,
2010).
Additionally, the reason the age-specific effect only emerged for the 10 to 12 and 13 to
16 year old groups is because greater identification with one’s peer is of particular importance
for adolescents and pre-adolescents who strive for similarity and congruency with in-group
norms (Abrams, Rutland, Cameron, & Ferrell, 2007). Specifically, adolescents and pre-
adolescents will strive for consistency with their own age groups to avoid peer segregation and
exclusion. Thus, these older children may be more sensitive and self-conscious of their public
self-presentation (Martin et al., 2014). Our results are in line with such conclusions, in particular,
age-specific body-part compatibility effects were found with the oldest age groups (10 to 12
years of age and 13 to 16 years of age), which represent pre-adolescent and adolescent children,
respectively. Thus, when viewing images of their own peers, pre-adolescents and adolescents
may be more aware of the bodies of their peers than younger individuals resulting in facilitated
RTs or greater interference when the response involves a different limb for these age groups.
Overall, our results suggest that body-part mapping may be own-age specific, particularly with
pre-adolescents and adolescents. Thus, the transition from middle childhood to late childhood
and adolescence can be a pivotal time in the development of intra- and inter-body
representations.
Finally, it should be noted here that it is not suggested that the absence of differences in
RTs across the different model types for the 7 to 9 year old age group indicates that the body
schema is dysfunctional or not intact in this age group. The point raised here is that is it possible
that the intricate processes of self-other mapping may not be fully developed in this age group. It
is clear that humans are equipped with a rudimentary knowledge about the dynamic organization
not only of one’s own body, but also of its relations to other bodies at a very early age. Even
minutes after birth, infants show a strong innate tendency to mimic sounds and oro-facial motor
acts performed by the adult models in front of them (Meltzoff & Moore, 1977). This data
41
indicates that the substrates of a self-other matching system are functioning early in infancy. The
absence of a body-part compatibility effect for the 7 to 9 year olds in the present study, however,
may indicate that children in early to middle childhood may not be as self-conscious of their own
and peers bodies because the desire to maintain peer group norms is less salient as those
experienced by pre-adolescent and adolescent children. Thus, it may be the combination of a
developing self-other mapping system and a muted self-perception that contributed to the lack of
body-part mapping in the 7 to 9 year old group.
3.2 Limitations
Limitations of the present study may include a limited amount of trial presentations for
both the spatial and body-part compatibility tasks. Specifically, for the spatial compatibility task,
3 instances of each of the 8 image combinations were presented. Due to the limited amount of
sample data, an outlier procedure was not conducted. Thus, any deviations in attention could
have biased the mean RTs for a particular trial type. Further, any response errors would
significantly reduce the data sample, thus placing significantly more weight on the remaining
viable trials. The range of standard deviations for the spatial compatibility task was between 38-
263 ms. Similarly, with the presentation of the body-part compatibility trials, 5 instances of each
of the 24 image combinations were presented. Thus, eliminating wrong response errors and data
through an outlier procedure limited the amount of interpretable data. The range of standard
deviations for the body-part compatibility task was between 20-170 ms. Thus, the range of
standard deviations for the body-part compatibility task was smaller than that of the spatial
compatibility task. Although this limited number of trial numbers was chosen to keep the time of
testing to a reasonable level and maintain data collection integrity by avoiding fatigue and
boredom, future work could include additional trial numbers.
Another limitation was that only one image per age condition was presented. Thus, it is
possible that no body mapping could occur because of an idiosyncratic feature in the specific
image that was chosen. This may be particularly true for the image of the 7 year old model in
which no body mapping was seen with any of the groups. Future work could include more than
one image per age condition.
Moreover, the age of the model used to represent the 7 to 9 year old age group is on the
lower end of the age range and may not accurately represent the mean of that age group. A one-
42
sample t-test was conducted to determine whether the age of the 7 year old model was
significantly different from the mean of the 7-9 year old age group. The analysis revealed that
the age of the model was significantly different from the mean of the age group, t(12) = 5.11, p<
0.001. Similar analyses performed with the other groups revealed that the age of the model for
which each group demonstrated a compatibility effect was not different from the age of the
groups: 11 year old model for the10 to 12 year old group, t(13) = -0.69, p= 0.50 (Figure 3.2); 15
year old model for the 13 to 16 year old group, t(13) = -1.07, p= 0.30 (Figure 3.3). Although it is
possible that the difference in age between the model and the participants is a factor that led to
the breakdown in self-other matching, inspection of the distribution scores of the three 7 year old
participants’ in that group revealed that these individuals are part of the overall distribution.
Thus, it appears unlikely that a discrepancy between the ages of the7 year old model and the
participants in the 7 to 9 year old group was the leading factor that led to the absence of a body-
part compatibility effect in the 7-9 year old age group (see Figure 3.1).
Figure 3.1. Difference scores of the incompatible by compatible conditions as a function of
model type for the 7 to 9 year old group. Conference Intervals are depicted. Black dots indicate
the three 7 year old participants’ scores.
43
Figure 3.2. Difference scores of the incompatible by compatible conditions as a function of
model type for the 10 to 12 year old group. Conference Intervals are depicted.
Figure 3.3. Difference scores of the incompatible by compatible conditions as a function of
model type for the 10 to 12 year old group. Conference Intervals are depicted.
Additionally, the inclusion of an adult model and adult participants could have provided
additional insights and a clearer picture of interpersonal body representation. In particular, by
having adult participants respond to both the images of the children and of an adult model, one
could investigate whether age specific body-part mapping also occurs with adult interactions.
More importantly, one could explore whether age specific effects are specific of pre-adolescent
44
and adolescent groups or whether this age specific effect also applies to adult and older adult
groups and thus occurring with most age groups.
Another potential limitation of the present study is its cross-sectional design because this
type of design is one of the weakest developmental designs. Cross-sectional studies provide a
'snapshot' of the outcome and the characteristics associated with it, at a specific point in time.
This ‘snapshot’ is limited because it provides information about individuals at a specific point in
time and differing results may emerge if a different time-frame is chosen. Specifically, cross-
sectional designs may be susceptible to cohort effects which make it particularly difficult to
separate effects of developmental changes from cohort effects when examining age effects across
a wide range of ages. This limitation makes interpreting results particularly difficult as cross-
sectional designs are not able to track changes in social processes over time and individual
changes in development. Following the same group of participants over multiple time points in
their lives, as in a longitudinal design, would elevate such effects and allow for the assessment of
developmental trends over time.
On a final methodological note, the newer two-choice hand response task for testing
body-part matching was employed for the present study, substituting the previous technique of
recording foot and thumb responses (e.g., Bach et al., 2007; Welsh et al., 2014; Jovanov et al.,
2015; Pacione & Welsh, in press). Although the patterns of results in earlier work (e.g., Bach et
al., 2007; Welsh et al., 2014; Jovanov et al., 2015; Pacione & Welsh, in press) suggest that the
previous technique of using a foot and thumb responses is sensitive to body part matching
processes, co-occurring vertical spatial compatibility may always present a challenge and
potential confound to interpreting body-part compatibility effects. Using a choice hand response
eliminated the possibility of vertical influence because the responding hands of the participants
are situated at the same elevation in real space, excluding any differences in elevation that were
seen with responses with the foot pedal and thumb plunger. With a choice hand response task,
spatial left-right compatibility effects are likely to be observed, but these left-right spatial
compatibility effects are not relevant because these spatial compatibility effects are orthogonal to
the body-part coordinates. That is, the spatial coordinates between the critical body-part target
conditions (hand/foot) are vertical, whereas the co-occurring spatial dimension is horizontal and
should be more independent of any body-part coding. One potential limitation of this new
choice-hand approach is that the explorations of body-part matching are essentially restricted to
45
the upper-limb. Although studies employing the upper-limb matching procedure are sufficient
for a number of experimental and theoretical contexts, such as animal-human upper limb
matching (Pacione & Welsh, in press) and perhaps tool-embodiment (Jovanov et al., 2015), this
constraint might limit investigations of a wider range of phenomena and matching of multiple
body parts within a single design.
3.3 Future Directions
The body-part compatibility task is an effective tool to assess self-other matching and,
potentially, the involvement of the human body schema in social cognitive processes. It is
thought that the processes that lead to the body-part compatibility effect are those that support
the human ability to empathize with, mimic, and understand the actions of other humans because
it involves the matching of the body parts of others to the representation of the body of the self.
Thus, the body-part compatibility task can be used to assess deficits in self-other matching in
clinical populations, in particular Autism Spectrum Disorder (ASD).
ASD is clinically defined as a triad of impairments in social interaction, communication,
and behavioural flexibility (American Psychiatric Association, 1994). Some of the interpersonal
impairments include difficulties developing a conceptual representation that encompasses the
mental states of others (Theory of Mind) and engaging in shared attention and emotional
engagement with other individuals (Rogers & Pennington, 1991; Williams, Whiten, Suddendorf,
& Perrett, 2001; Smith & Bryson, 1994; Williams, 2008). Autism can be further characterized at
the motor level, with accounts of repetitive and stereotyped behaviour (Williams et al., 2001).
Specifically, persons with autism consistently exhibit problems with mental flexibility and
planning. For example, persons with autism perform like their peers when a task involves
concrete planning, however, more abstract planning behaviours pose a particular challenge
(Glazebrook, Elliott, & Szatmari, 2008). Thus, analyzing deficits associated with action
understanding may correlate with prominent social impairments seen in individuals with autism.
In exploring such potentials, a future study can be employed to investigate the integrity of
mechanisms underlying the ability to represent the bodies of other humans (i.e., self-other
matching) in individuals with ASD by comparing the performance of TD and those with ASD
individuals using the human body-part compatibility task. This information can be used to
understand the neural underpinnings of how one’s own body position influences one’s perception
46
of others’ body representations. The knowledge can be used to identify areas of dysfunction in
ASD.
It is thought that an impaired formation/organization of self-other representations’ may
be at the centre of many of the impairments associated with autism (Williams et al., 2001;
Stewart et al., 2013; Smith & Bryson, 1994; Rogers & Pennington, 1991). Based on the cognitive
profile associated with ASD, and in particular challenges in imitation and theory of mind, it has
been suggested that these impairments seen in individuals with ASD may be related to an
inability to relate perceived limb movements of another individual to executed limb movements
by one’s self, highlighting a self-other mapping or action observation/mirror neuron system
impairment as one of the main possible causes of the deficit (Stewart et al., 2013). Rogers and
Pennington’s (1991) Intersubjectvity Theory suggests that it is this impaired self-other matching
process in individuals with ASD that results in a cascade of impaired capacities including
imitation, emotion-sharing, joint attention, theory of mind, and pretend play.
In designing this future study, the TD participants from the current study and an ASD
group would be matched based on sex, chronological age and non-verbal IQ. The task and design
of the experiment would be based on the current study, where the ASD children would be
responding to the same 3 human male figures – an adolescent aged 15, a child aged 11, and a
child aged 7 - as those presented to the TD participants in the present study. If the children in the
ASD group are able to represent the bodies of others, then that would suggest that limb mapping
is intact and an additional element associated with imitation and action observation may be
impaired. Thus, it may be that the interaction of neural networks associated with limb mapping
and action understanding are compromised. In addition, it could be postulated that motion
detection is a more complex task, reflecting an array of neuronal inputs and therefore additional
areas of possible deficiency. If, however, compromised body-part compatibility effects are seen
in the ASD group, than that would suggest that body mapping is impaired. Such a finding would
suggest that individuals with autism are not able to map the body parts of other individuals onto
their own body schema. This impairment would be reflected in imitation and action observation
deficiencies because, presumably, one needs to understand and match the body parts of others to
the representations of homologous body parts of the self to enable efficient imitation. Therefore,
the imitation impairments seen in individuals with ASD confirm an inability to relate perceived
47
limb movements of another individual to executed limb movements by one’s self, reinforcing a
self-other mapping impairment as a possible cause of the deficit.
3.4 Delimitations
A key factor in making the present work achievable was governing the duration of the
present study in order to maintain the attentional focus of the participants, in particular, the
participants in the youngest age group. Specifically, trial numbers for both the pre-test and test
phases were reduced to facilitate the most accurate responses. The trial blocks were designed to
be completed within a feasible about of time (2-5 minutes), hoping to keep the attentional focus
of the participants on the task. Additionally, the experimenter advanced the “READY” cue for
each trial when she was confident the participant was focused on the task and ready to complete
a trial. Rest and refocusing breaks were strongly encouraged between blocks, ensuring the
participants were refocused when returning to the study.
Additionally, the original design of the study included a 4th
model type representing a
young adult. With the addition of this extra model type, it had increased the amount of blocks
and trials presented which made the study duration exceedingly long and unworkable.
Proceeding with only 3 model types provided the most appropriate alternative. Overall, the study
duration was limited to a maximum 45 minute single session, to ensure that the participants, in
particular the youngest participants, could maintain their focus and attention on the relevant task.
48
Chapter 4 Conclusion
The purpose of the present study was to investigate the integrity of mechanisms
underlying the ability to represent the bodies of other humans (i.e., self-other matching) in
typically developing (TD) children and adolescents. The findings revealed that when viewing
images of children and adolescents with targets placed on homologous body sites of the
observing participant, increased sensitivity of the homologous representation in the human body
schema of the observing child and adolescent will occur. In particular, body-part compatibility
effects were found for both the 10 to 12 and 13 to 16 year old age groups. Most interestingly, the
body-part compatibility effects that emerged for both the 10 to 12 and 13 to 16 year old age
groups occurred when viewing models of their own peers. On the other hand, no body-part
compatibility effects were found for the 7 to 9 year old age group when viewing any of the three
model types.
The results of the present work support the idea that children and adolescence are able to
register the bodies of other children and adolescents, creating a shared neural representation
between the self and other. This shared representation is thought to enable individuals to
represent their own and others’ goal-directed actions via a single conceptual system (Decety &
Sommerville, 2003). This conceptual system would allow individuals to understand the actions,
emotions, and intentions of others. Further, facilitated identification with one’s peer may be a
reflection of shared neural representations between the self and other, where the body of one’s
peer is experienced as something analogous to one’s own experienced body. Thus, individuals
are drawing on information from the structure and movements of their own body to interpret
their environment and shape their cognitive processes. Ultimately, such experiences are likely to
be involved in the ability to understand the actions of others and engagement in social
interaction.
In concluding, the present work provides some initial insights into peer-to-peer
interactions. Specifically, strong resonance with the bodies of one’s peers may be an important
platform on which multiple aspects of social and cognitive development may be built. Indeed,
embodiment is at the heart of action understanding and social interaction. Thus, the potential
implications of these findings may highlight peer interactions as an invaluable source of learning
49
for children and adolescents in school environments. Peers may not provide the same kind of
structure and support during social interactions that are provided by adults, however, the
relevance of peers for early social cognitive development may be understated. Further, these
findings may highlight implications for understanding ASD and other cognitive disorders.
Specifically, impairments associated with self-other matching with one’s peer may be central to
many of the deficits seen in individuals with ASD, including imitation, action observation and
emotional sharing. The knowledge gained can be used to create specialized programs that focus
on building interpersonal skills, with a special emphasis on peer interactions.
50
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