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Motor Experience and Action Understanding:
A Developmental Systems Perspective
Bennett I. Bertenthal
June 10, 2018
Chapter to appear in:
Handbook of Integrative Psychological Development:
Essays in Honor of Kurt W. Fischer
Michael F. Mascolo & Thomas Bidell, Editors
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Motor Experience and Action Understanding:
A Developmental Systems Perspective
We see, or more likely learn to see, actions not as merely physical movements, but as
outcomes of intentional relations between agents and objects of their attention. These processes
are foundational to the development of social cognition and have been the focus of a large body
of studies in recent years addressing the behavioral, computational, and neural foundations of
action understanding (Decety & Sommerville, 2003; Hamilton & Grafton, 2006; Kilner, 2011;
Woodward, 2009). Still, the mechanisms responsible for this understanding continue to be a
source of considerable debate and controversy (e.g., Csibra, 2006; Jacob, 2013; Southgate, 2013;
Rizzolatti & Sinigaglia, 2010; Woodward & Gerson, 2014).
In recent years, considerable neurophysiological, neuropsychological, and behavioral
evidence has emerged to support the contention that action understanding and motor behavior are
closely linked (e.g., Gallese & Sinigaglia, 2011; Rizzolatti & Craighero, 2004), but there are still
many unanswered questions about how and why the motor system contributes to action
understanding. By action understanding, we mean the capacity to achieve an internal description
or representation of a perceived action and to use it to organize our understanding and prediction
of others’ behaviors. Adults are capable of understanding actions via multiple pathways (e.g.,
Kilner, 2011; Tessari & Rumiati, 2004), and thus it is difficult to assess the unique contributions
of the motor system. By contrast, human infants are just beginning to recognize and understand
actions at a time when their motor knowledge is more advanced than their cognitive or semantic
knowledge. As such, early development offers a unique opportunity for studying the relation
between motor experience and action understanding.
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By now there has been considerable attention directed toward this issue, but the
interpretation of the empirical evidence has been contentious in part because there is a tendency
to neglect the multifarious ways that experience contributes to action understanding (e.g.,
Hunnius & Bekkering, 2014. Dating back to the 1970s, Gottlieb (1976) developed a taxonomy
for considering the role of experience on perceptual development, which serves as a useful
starting point for considering the contributions of experience more generally. According to this
framework, perceptual experience could affect the development of a perceptual skill in one of
three ways: (1) If a structure or function is undeveloped at the time of the onset of experience,
experience may induce the structure or function; without experience, the structure or function
will not develop. (2) If a structure or function is only partially developed, experience may
maintain the structure or function at that level or facilitate its further development. (3) If the
structure or function is fully developed, experience would serve to maintain it. In the case of a
partially or fully developed structure or function, the lack of experience could eventuate in loss
of structure or function. The main reason this is relevant to the current controversy is that by
extending this same framework to motor experience, it can be seen that the contributions of this
experience to action understanding need not be all-or-none. Instead, it is extremely plausible that
motor experience can serve as a facilitator of action understanding, but that it is neither necessary
nor sufficient.
In order to evaluate this claim, the current review is guided by a developmental systems
perspective in which action understanding needs to be studied as a dynamical system. By
definition, such a system is high-dimensional, multi-level, multi-causal, and nonlinear. What has
been lacking in existing studies is a focus on modeling how behavior is dynamic, involves the
interaction of multiple factors, and unfolds over multiple time scales.
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The primary goal of this chapter is to demonstrate that many of the confusions and
contradictions in the literature are attributable to viewing specific processes related to action
understanding in isolation and not considering them as part of a larger system of development..
In the first section of this chapter, we address some common misunderstandings and conceptual
confusions when discussing action understanding. In the second section, we review evidence for
and against the proposition that action understanding is related to motor experience. The strong
form of this proposal asserts that motor experience is necessary for action understanding, but
there is also a more moderate proposal asserting a bidirectional relation between the two
constructs. In the final section, we discuss why it is essential to incorporate a developmental
systems perspective when considering these issues. Contrary to most current reviews of this
complex process, it is essential to consider the development of action understanding as related to
multiple factors that modulate the contributions of motor experience depending on age, task, and
context.
What Processes are Involved in Action Understanding?
Some of the most prominent theories (e.g., Rizzolatti & Sinigaglia, 2010) suggest that
actions are understood by observers mapping the perception of other’s actions to their own
corresponding motor representations. This formulation of a shared representation for the
perception and planning of actions is a direct descendent of the ideomotor theory of James
(1890) and Greenwald (1970). According to this account, “every mental representation of a
movement awakens to some degree the actual movement which is its object” (James, 1890). The
implication is that there is some functional equivalence between executing an action and
perceiving, imagining, or preparing to perform the same action; each of these behaviors stimulate
the same motor representation – that is, the same neural circuitry we use to perform that action.
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(Jeannerod, 1994; Rizzolatti & Craighero, 2004). For example, when we observe a hand
grasping a glass, the same neural circuit that plans or executes this goal-directed action becomes
active in our own brain. The remarkable discovery of mirror neurons in monkeys provided the
first direct evidence that action observation and action execution shared a common neural
representation, and stimulated research exploring a homologous mirror mechanism in humans.1
Yet, enthusiasm for this finding sometimes overshadowed the details. First and foremost,
these findings were observed in macaque monkeys and mirror neurons were selective only for
goal-directed actions, such as grasping, holding, or manipulating objects, and not for observation
of a moving hand or object alone (Rizzolatti, Fogassi, & Gallese, 2001). In other words, mirror
neurons in monkeys code for the goals of an observed action, but do not necessarily code for the
means of these actions (Rizzolatti & Sinigaglia, 2010). Consistent with this finding is that
monkeys are capable of emulating observed behaviors but not explicitly imitating them via the
same means (Tomasello & Call, 1997; Custance, Whiten, & Bard, 1995). Thus, these neurons
provide monkeys with a mechanism for action understanding via the observation and emulation
of goal-directed actions, but they are apparently insufficient for enabling monkeys to imitate (see
Rizzolatti & Craighero, 2004, for a review).
Related, albeit, indirect evidence for a mirror system in humans was provided by
electrophysiological and neuroimaging studies revealing that observation of human actions
activates a complex network formed by occipital, temporal, and parietal visual areas, as well as
two motor regions (e.g., Decety, Chaminade, Grezes, & Meltzoff, 2002; Grafton, Arbib, Fadiga,
& Rizzolatti, 1996; Nishitani & Hari, 2000). Although the human mirror mechanism is often
1 Mirror neurons were first discovered in the early 1990s when a team of Italian researchers (Gallese,, Fadiga, Fogassi, & Rizzolatti, 1996; Rizzolatti, Fadiga, Gallese, & Fogassi, 1996) discovered individual neurons in the premotor cortex of macaque monkeys that fired both when they performed a goal-directed action, such as grasping a piece of food, and also when the monkeys observed a conspecific or a human perform the same action..
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considered similar to mirror neurons in that it is restricted to goal-directed actions, recent
research reveals much broader functionality. The mirror mechanism maps the sensory
representation of the action, emotion or sensation of another onto the perceiver’s own motor,
viscero-motor or somatosensory representation of that action, emotion or sensation (Gallese &
Sinigaglia, 2011). As such, it responds to both transitive and intransitive actions (Bertenthal,
Longo, & Kosobud, 2006), and in some situations generalizes to robotic actions (e.g., Gazzola,
Rizzolatti, Wicker, & Keysers, 2007). Unlike the monkey mirror system, the human homologue
enables imitation because it codes the specific movements that represent the means for achieving
goals (Chaminade, Meltzoff, & Decety, 2002; Iacoboni, Woods, Brass, Bekkering, Mazziotta, &
Rizzolatti, 1999).
Actions are multi-determined
In spite of the extensive evidence for a mirroring mechanism in humans, the sufficiency
or necessity of this mechanism for explaining action understanding is far from definitive (e.g.,
Hasson & Frith, 2016; Kilner, 2011). One reason for this uncertainty is that evaluating the
contributions of motor representations in adults is always problematic because their
understanding is informed by multiple higher-level cognitive processes that could obviate the
need for direct matching and motor simulation. Developmental research offers valuable
converging evidence for addressing this important issue. If action understanding is dependent on
motor-based representations, then the likelihood of young children demonstrating this skill
should be closely tied to their own motor development (Longo & Bertenthal, 2006).
This seemingly straightforward hypothesis has been the source of a large number of
developmental studies, and the results are generally supportive. It is nevertheless difficult to
fully evaluate this developmental prediction, because actions are often limited to goal-directed
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reaching, and action understanding is rarely defined in such studies. As we will discuss in this
chapter, actions extend well beyond reaching and include intransitive actions, such as pointing
and gesturing, as well as vocalizations and facial expressions. Actions are represented by the
motor brain at multiple levels from muscle synergies to movement trajectories to the goals or
effects of the movements. The activation of a motor representation enables an appreciation of
the means (i.e., how the body parts are arranged to move) by which the action is executed as well
as an appreciation of the goal or the effects of the action. During the performance of an action,
the motor representation guides its execution, whereas during the observation of an action, the
motor representation results in a mental simulation of the movement and its goal.
Actions can thus be understood at many different levels: intentions or the overall reason
for executing the action; short-term goals necessary to realize the intention, such as grasping an
object; motor programs describing the spatial-temporal patterning of muscles enabling the
action; and kinematics describing the movement of the action in space and time (Kilner, 2011).
In order for an observer to understand the intention of an action, it is necessary to analyze the
movement at either the intention or goal level while having direct access to only the visual
representation of the kinematic information. These levels are thus not independent and are
hierarchically organized such that the kinematics is dependent on the motor level, the motor level
is dependent on the goal, and the goal is dependent on the intention.
It is important to note that actions are described in increasingly abstract terms as we
move up the hierarchy. For example, the motor representations of intentions and goals are
described at more abstract levels which are useful for achieving greater flexibility in performing
a task because they can be accomplished with different actions. This implies, however, that there
is no one-to-one mapping between actions and goals (cf. Kilner, 2011). As such, one of the
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critical challenges confronting the observer is that the same actions can be executed to achieve
different goals and intentions. Initial accounts of action understanding based on a direct
matching or mirror mechanism proposed that simply mapping the observed action to the motor
representation was sufficient for understanding the goal or intention because of a simulation
mechanism. If we know what our goal or intention is when we execute an action, then we should
know the intentions of another when we observe the same action because this percept activates
the corresponding motor representation in our own motor brain. If, however, there exists a one-
to-many mapping between observed actions and intentions, then there is a problem with this
account. Interestingly, this may be less of a problem for infants whose actions are more
stereotypic and are triggered more by context than by recall. Indeed, this is consistent with the
research literature that we later review in this chapter.
Inter-dependence of action and attention
There are a number of inter-related processes contributing to action understanding, and
these processes unfold over real and developmental time. Yet, many of these processes are
missed in standard laboratory experiments because the stimuli are often reduced to a situation
lacking sufficient complexity, such as a disembodied arm reaching for a single object (e.g.,
Woodward, 1998). Frequently, these simplified stimuli are necessary to conduct experimentally
rigorous and well-controlled experiments using real-time measures, such as eye tracking or
electroencephalographic recordings (EEG), but they eliminate critical processes that are
generally necessary for perceiving and understanding actions in more natural social situations.
For example, these paradigms obviate the need for attentional selection because the stimuli are
all preselected. Yet, selective attention is often the key to what we can learn because it provides
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the ability to maintain a behavioral or cognitive set amidst distracting or competing stimuli
(Bertenthal & Boyer, 2015).
Selective attention is available from birth in the form of exogenous orienting or stimulus-
driven attention. This form of attention is considered to be reflexive and automatic (Corbetta &
Shulman, 2002) and depends on the salience or survival value of the stimulus. For example,
neonates attend preferentially to attractive faces, and are most sensitive to the presence of eyes in
a face (Batki, Baron-Cohen, Wheelright, Connellan, & Ahluwalia, 2001). They are also more
likely to track a schematic face-like stimulus than one in which the features are scrambled
(Johnson & Morton, 1991). This form of attention is highly adaptive, because it helps to ensure
that infants’ perceptual experiences are focused on meaningful stimuli that are important for
survival. Endogenous orienting or goal-directed attention is the intentional allocation of
attentional resources to a predetermined location or target. This type of orienting occurs when
attention is directed according to an observer’s goals or desires, allowing the focus of attention to
be manipulated by the demands of the task or situation (Corbetta & Shulman, 2002).
Endogenous orienting depends on higher-level processes that develop with age and experience,
and significantly influence what the child decides to look at. One of the first examples of
endogenous orienting occurs around four months of age when infants begin to predictively track
(i.e., purposefully shift their attention to) objects that are briefly occluded (von Hofsten,
Kuchukhova, & Rosander, 2007).
Thus, action understanding depends on the development of both stimulus-driven as well
as goal-directed attention, because both will increase the likelihood of the child gaining
perceptual experience with actions. In the former case, the experience will be dictated by the
frequency and saliency of the actions, while in the latter case the experience will be dictated by
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the knowledge and goals of the child. In both cases, perceptual experience is considered a
driving force in learning about actions, and there should be a reciprocal relation between the
development of action understanding and the development of selective attention.
Thus far, we have not addressed whether these observed actions are self-generated or
produced by others. All spatially coordinated actions will require attention on the part of the
agent if the action is to be successful. If, for example, an infant is to reach for and grasp an
object, then it is necessary for the infant to attend to the target of the reach and coordinate its
motor response with the proprioceptive and kinesthetic sensations of reaching to the target
(Bertenthal & von Hofsten, 1998). In other words, self-generated reaching is a multi-modal
behavior that is organized by attention to the target. When infants observe reaching by another
agent, they will first need to decide whether or not to focus their attention on the goal-directed
action and only then can they map their perception to an internal representation. If they already
are capable of the same action, then they will possess a motor representation of the reach. If they
are incapable of the same action, they may still possess an internal representation depending on
their perceptual experience and cognitive development. The bottom line here is that attention to
self-generated actions is necessary for the development of a motor representation in the same
way that attention to observed actions is necessary for the development of a perceptual or
conceptual representation. Curiously, attention and motor representations are sometimes placed
in opposition to each other as explanations for action understanding (e.g., Sommerville,
Hildebrand, & Crane, 2008). It is more likely, however, that these two processes are
complementary as opposed to being oppositional. As a consequence, measuring infants’ action
understanding will often not be sufficient to adjudicate between a motor representation or a
visual/conceptual representation mediating the response.
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Attention can be further differentiated in terms of its time course. Most simple object-
directed actions unfold over a period of time lasting between a few hundred milliseconds and a
few seconds. This suggests that predicting the goal of an action occurs within two to three
seconds or less, but observers will covertly orient to the target of an action even before they
begin to respond (i.e., overtly orient). In standard laboratory tasks, orienting attention to a target
prior to the beginning of a gaze shift or reach will facilitate detecting the target (Gredebäck &
Daum, 2015). This sort of orienting is often covert and does not require the overt movement of
the eyes or head. It thus occurs very quickly, usually within 100 to 300 ms (Bertenthal, Boyer, &
Harding, 2014; Driver, Davis, Ricciardelli, Kidd, Maxwell, & Baron-Cohen, 1999; Friesen &
Kingstone, 1998), and is followed by the selection and execution of a response. Covert attention
is often studied in the lab with a spatial cueing paradigm (Posner, 1980).
Hood and colleagues (Hood, Willem, & Driver, 1998) adapted this paradigm to study
infants’ covert attention to gaze cues, by testing 3- to 4-month-old infants responses to a
digitized, color image of an adult face with blinking eyes that subsequently shifted their gaze to
the left or right. Infants oriented their attention faster to a peripheral target in the cued than the
non-cued direction, even though the cue was not predictive of target location. This result thus
suggested that infants covertly oriented in the same direction as the gaze shift which facilitated
their responding more quickly in that direction.
Similar findings are reported when the spatial cue is a reaching or pointing hand, except
that differential responses to these spatial cues emerge at somewhat older ages. Infants between
5- to 7-months of age respond to a static image of a grasping hand (Daum & Gredebäck, 2011),
and infants around 12 months of age respond to a pointing hand (Daum, Ulber, & Gredebäck,
2013). Interestingly, these developmental findings suggest that action perception follows the
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development of action execution since reaching begins to emerge around 4 months of age and
pointing begins to emerge around 9 to 12 months of age. There are, however, exceptions to this
developmental sequence. For example, some studies (Bertenthal et al, 2014; Rohlfing, Longo, &
Bertenthal, 2012) report that infants begin orienting in the direction of a point as early as 4
months of age. Apparently, there is more to explaining action understanding than that it is
associated with motor development. This is a critical issue that will require further discussion
later in this chapter.
Predictive and postdictive measures of action understanding
One specific measure of action understanding is goal prediction. In order to assess
infants’ prospective understanding of actions, their eye movements are recorded while observing
a goal-directed action, such as reaching for an object on a table. If infants’ gaze shifts to the
target prior to the completion of the reach, they are credited with predicting the goal of the
action. In some situations, this requires that infants disengage from the moving hand and shift to
the target in as little as just a few hundred milliseconds. Although this behavior is referred to as
goal prediction, it is measured with an attentional response (i.e., overt orienting) involving the
movement of the head and eyes to detect the target prior to the arrival of the hand (Daum &
Gredebäck, 2015). Thus, we see again that there is an intimate relationship between attention
and action understanding, and that these two processes are difficult to dissociate.
In order to fairly evaluate the contributions of motor experience for understanding goal
prediction, it is important to place this skill in context. Infants reveal a broad ability to predict
future events from very young ages. In addition to evidence from the domain of action
perception (e.g., Hunnius & Bekkering, 2014; Gredebäck & Falck-Ytter, 2015), this skill has
been demonstrated with regard to visual expectations (e.g., Haith, 1994), object tracking (e.g.,
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von Hofsten et al., 2007), and social interactions (e.g., Adamson & Frick, 2003). Predicting
when and where an event occurs is indispensable for understanding and coordinating one’s own
behavior with others’ actions in everyday settings (Hommel, Musseler, Aschersleben, & Prinz,
2001). In many of these domains, infants are capable of predicting events prior to their
developing the requisite actions, themselves, or they predict non-biological events that do not
involve any human movements at all. Their success in predicting these events seems to
challenge the proposal that the development of motor representations is necessary for predicting
future events. In most of these cases, however, it is still not clear whether infants actually rely
on real-time processing of observed actions when predicting their future trajectory (Bache,
Springer, Noack, Stadler, Kopp, Lindenberger, Werkle-Bergner, 2017). Even less clear is what
specific information infants predict given that the outcome of an event can be defined in terms of
where, when, what, or why. If infants’ understanding of these different dimensions do not
develop at the same time, then conclusions regarding prediction of action events will depend on
the specific criterion selected. One very reasonable hypothesis is that a motor representation is
necessary for addressing the prediction of some of these dimensions (e.g., when), but perhaps
others are less dependent on this same representation (e.g., location).
A second measure of action understanding is the evaluation of the outcome. Once the
action is completed, the observer compares the outcome with some expectation dependent on
their knowledge of the action. Critically, the process available to evaluate the observed outcome
is different than that available to predict the outcome or goal before it takes place (Daum, Attig,
Gunawan, Prinz, & Gredebäck, 2012). In the former case, the observed action either matches
or does not match one’s expectation, but the evaluation occurs only after the action is completed,
whereas in the latter case the process is necessarily predictive. Consider, for example, infants
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observing a person lifting a cup to their mouth or their ear (Stapel, Hunnius, van Elk, &
Bekkering, 2010). If they are to predict the goal of the action, then they must shift their gaze to
the mouth before the cup reaches that location. By contrast, they will decide whether the action
is a violation of their expectation only after the action is completed. Thus, it is not necessary for
them to know the correct outcome when observing an unexpected event and the timing of their
response is less critical. Instead, they simply need to respond to the unfamiliarity of the observed
action by displaying some form of increased attention. Changes in attention are assessed using a
number of different measures including looking time (e.g., Daum, Prinz, Aschersleben, 2009;
Woodward, 1998), pupil dilation (e.g., Gredebäck & Melinder, 2010), and event related
potentials (e.g., Stapel et al., 2010; Reid, Hoehl, Grigutsch, Groendahl, Parise, & Striano, 2009).
The time course of these measures varies from as much as minutes to milliseconds depending on
whether the experiment involves a behavioral, physiological, or neural response. It is important
to appreciate that each of these measures are capturing different levels of information processing,
and thus neural or physiological measures of unexpected events will likely be observed earlier
than comparable behavioral measures of the same events.
Action Understanding and Motor Experience
It is currently hotly debated whether the mirror system in humans evolved as an
adaptation of the brain or instead develops after birth as a function of perceptual experience and
associative learning (e.g., Cook, Bird, Catmur, Press, Heyes, 2014; Ferrari, Tramacere, Simpson,
Iriki, 2014; Rizzolatti & Fabbi-Destro, 2008). Either way, this shared representation for the
observation and execution of actions constitutes one mechanism by which infants could
understand and predict others’ goal-directed actions. Less certain is whether motor experience is
necessary for action understanding. As previously mentioned, this is clearly not true for adults
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who are capable of predicting the outcomes of actions with semantic knowledge and other higher
level processes. According to one version of this view, observers infer the goal of an action by
assessing what end state would be efficiently achieved given the constraints of the situation
(Csibra, 2007). Although some theorists suggest that this same process is available to infants
(e.g., Csibra, 2007; Southgate, 2013), it is not clear that they would have all the necessary
cognitive skills to explain their precocious understanding of human actions (Bertenthal & Longo,
2008). Moreover, there is considerable evidence suggesting that infants’ motor experience is an
important prerequisite for their action understanding.
In order to avoid any misunderstanding, let me briefly recapitulate the logic for these two
divergent views. Infants’ recognize the goal and movements of an observed action by mapping
its perception to its corresponding motor representation. If the motor representation for the
observed action is not yet developed (i.e., no evidence that the infant can execute the motor
behavior), then infants will presumably be unable to understand the goal or meaning of the
action. One problem with this claim is that the process by which perception is mapped to the
motor representation is not directly tested. Accordingly, it remains unspecified whether the
identification of a goal follows the activation of the motor program or precedes its activation
through an inferential process. In the former case, the motor representation recruits the goal in
order to identify the outcome of the action. In the latter case, the goal recruits the motor
representation in order to predict how it will be achieved (Southgate, 2013).
As just summarized, the development of action understanding is framed by theorists as
either requiring or not requiring motor experience, which is a false dichotomy. The problem
with this framing is that it oversimplifies the complex ways in which experience interacts with
the task and developmental status of the child. In the remainder of this section, we present a
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selective review of infants’ action understanding demonstrating that the evidence for or against
the contributions of motor experience are often more nuanced than suggested by the authors of
this research.
Infants’ analysis of goal-directed actions
Some of the earliest evidence showing that infants’ could perceive the goals and not just
the physical movements of others’ actions was based on looking time experiments. When
infants were familiarized to a goal-directed action, such as reaching for a toy, their looking time
to the event decreased over trials (Woodward, 1998). Looking time increased when the goal was
changed, but not when the reach trajectory changed suggesting that the representation of others’
actions was structured by the relation between the agent and her goal. Infants as young as 5 to 6
months of age respond accordingly when observing simple instrumental actions, such as goal-
directed reaching. By 9 to 12 months of age, infants’ looking times in similar experimental
paradigms suggest their understanding of the goal of a more distal action, such as looking or
pointing (Johnson, Ok, Luo, 2007, Sodian & Thoermer, 2004; Woodward, 2003), reaching over
obstacles (Brandone & Wellman, 2009), or using a tool as a means to capturing an object (Hofer,
Hauf, Aschersleben, 2005; Sommerville & Woodward, 2005). Critically, some studies reveal
that infants do not show preferential looking in control studies involving ambiguous human or
non-human movements (Thoermer, Woodward, Eisenbeis, Kristen, & Sodian, 2013; Woodward,
1998). Overall, these findings suggest that infants’ action understanding is accomplished at an
abstract level of analysis involving goals, which are not directly observed, and not movements of
the actions which are directly observed (Woodward & Gerson, 2014).
Additional evidence for goal understanding comes from infants’ pointing at one year of
age to absent referents making it clear that they understand that pointing is not simply a cue for
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attracting another’s attention to a specific object, but instead is a means to orient them mentally
to some shared representation (Tomasello, Carpenter, & Lizkowski, 2007). Infants also begin to
show comprehension of pointing which requires more than merely following the direction of a
point; they search for invisibly displaced objects in locations that are specified by an adult’s
point and visually search even longer when the object is not found at the pointed location
(Liszkowski, Carpenter, & Tomasello, 2007). Taken together, these findings suggest that infants
are not merely following the direction of a pointing gesture, but instead understanding the
communicative intent of the actor.
It is noteworthy that in general the findings conform to a developmental sequence
consistent with motor development. For example, infants understand simple goal directed
actions at the same age they begin to reach for objects, and they begin to understand pointing
gestures at the same age they begin to point. Likewise, infants begin to understand a sequence of
actions as a means to an end (i.e., a higher goal) at the same age that they begin to execute one
action as a means to achieving a separate goal. One example of this behavior is pulling a cloth in
order to obtain a toy sitting on the cloth (Sommerville & Woodward, 2005). Although these
studies offer indirect evidence to suggest that infants’ action understanding is linked to their
motor development, there are reasons to be circumspect.
One challenge to this conclusion is that some studies (e.g., Biro & Leslie, 2007; Luo,
2011) have tested infants with two-dimensional geometric stimuli in place of human actions. If
action understanding is tutored by one’s own motor experience then we would not expect infants
to understand the goal-directed actions of these stimuli at the same age. Contrary to this
expectation, infants as young as 3 and 6 months of age demonstrated that they were sensitive to
goal-directed actions exhibited by these non-human agents as long as the stimuli were associated
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with specific animacy cues (e.g., self-propulsion, action variation with equifinality, cause-effect
relations). A second challenge to this conclusion is exemplified by findings suggesting that 6-
month-old infants attribute a goal to a person walking (Kemewari, Kato, Kanda, Ishiguro, &
Hiraki, 2005), even though their responses to a mechanical claw or animated box were
indeterminate (Woodward, 1998). At this age, most infants are not yet capable of crawling let
alone walking; thus, self-generated motor experience is not a prerequisite for understanding a
goal associated with walking. By contrast, visual experience seems an important factor given
that infants are familiar with humans walking, but not with a mechanical claw or animated box.
A final reason to question the developmental relation between action understanding and
motor development is that the evidence is all correlative, and thus it is possible that some third
variable could be responsible for the synchronous development of the motor response and its
understanding by infants. One solution to this problem is to experimentally manipulate motor
experience. This was accomplished in a clever study that fabricated Velcro-covered “sticky”
mittens for 3-month-old infants (Sommerville, Woodward, & Needham, 2005). Although infants
by this age are capable of extending their hands and arms and sometimes contacting objects, the
objects are not grasped. Velcro-covered mittens constituted a ‘game changer’ for infants,
because then they were able to apprehend Velcro-taped objects in their field of view. When
infants were given experience retrieving objects with these sticky mittens prior to testing them
for their understanding of the relation between an agent and her goal, they preferred looking at a
novel goal as opposed to a novel means (arm movement to a different location) after being
familiarized to a goal-directed action. Critically, infants who only observed an adult wearing a
Velcro-covered mitten reaching and apprehending objects during the training phase, did not
show any preference for the new goal or new location on the test trials suggesting that
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observational experience did not result in an understanding of the relation between the agent and
her goal.
Although these findings represent an important step in the right direction, they were not
conclusive because motor experience necessarily involves correlated visual experience which
might be different than the passive observational experience provided to the control group of
infants (cf. Held & Hein, 1963). This difference between active and passive visual attention is
readily appreciated by all of us when driving a motor vehicle to a destination as opposed to being
a passenger in that same vehicle. We may see the same view of the road, but the passenger is
much less likely to encode the same level of detail as the driver. In other words, we are
necessarily more focused on the task and relevant cues when we are actively involved.
One gallant attempt to surmount these problems was to employ a ‘yoked design’ in which
3-month-old infants in the passive observational condition received training that was more
closely matched to the experience of the infants in the active condition (Gerson & Woodward,
2014). This design tried to equate the visual experiences of the infants in the active and passive
conditions, but infants in the passive condition were still deprived of correlated visual-motor
experiences which is necessary for the development of spatially coordinated behaviors (Held &
Hein, 1963). Further reservations about these findings were revealed by a second experiment in
which the training objects differed from the test objects. Unlike the findings from previous
experiments, 3-month-old infants did not selectively prefer the new or the old goal events
suggesting that they had not encoded the agent-goal relation. It thus appears that the visuomotor
experience that contributes to action understanding is very specific, at least at young ages, and
highlights the reciprocal role of visual attention and motor performance.
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In related research, 2- to 3-month-old infants were given much more extensive
experience playing with blocks while wearing sticky mittens (i.e., two hours of object directed
training over a two week period) and this training resulted in improved reaching behavior as well
as changes in their visual exploration of agents and objects (Libertus & Needham, 2010). Infants
who only watched their parents playing with the blocks for an equivalent amount of time did not
show much of a change in manual or visual behaviors. Critically, active experience led to
improvements in both reaching as well as the deployment of visual attention. As such, these
findings are consistent with the view that visual attention and motor performance are reciprocally
related.
In spite of this claim, the majority of training studies, like the sticky mitten experiments,
fail to find a direct relation between attention and action understanding. Infants are tested for
action understanding following one of two types of training. One group of infants receives
active training and the other group receives observational training in which infants are shown
different exemplars of reaching or tool-use events, but do not have the opportunity to perform
these actions themselves. For example, Sommerville et al. (2008) tested 10-month-old infants
for their understanding of the goal structure of an event involving the pulling of a cane to retrieve
a toy after they learned to pull the cane, themselves, or observed an adult repeatedly performing
this action. The results revealed that only the infants in the active training group showed
sensitivity to the goal structure of the event. Similarly, these training studies were effective
when teaching 7-month-old infants how a claw-shaped tool grasped toys if the experimenter first
used the claw to give toys to the infant (Gerson & Woodward, 2012). This procedure ensured
that infants’ grasping co-occurred with the joint action of the experimenter. Following this
training, infants responded systematically to the experimenter’s goal in an imitation task. By
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contrast, this result was not observed if infants simply watched the experimenter, or were given
an opportunity to play with the tool.
Do these results invalidate our claim for a reciprocal relation between action
understanding and attention? It is most likely premature to offer a definitive answer, because all
of the preceding examples demand more focused attention when infants execute an action as
opposed to merely observing the action. One factor often overlooked in these studies is the
important role that variability of performance plays in learning. Infants will be much more
variable in their performance from one action to the next than will adults. For example, infants
wearing sticky mittens will introduce much more variability in their goal-directed actions than
will an experimenter grasping the same toys. Variability and opportunistic selection is one of the
engines by which children learn (Bertenthal, 1999). As a consequence, the opportunities for
learning from their own self-generated actions will be far greater than the opportunities provided
by observing the experimenter. Furthermore, infants are more likely to engage in endogenous as
opposed to exogenous orienting while executing an action themselves as opposed to observing
the experimenter perform the action.
The likelihood of engaging in endogenous attention increases with age (e.g., Elsabbagh,
Fernandes, Webb, Dawson, Charman, & Johnson, 2013). As infants continue to develop beyond
the first few months, their visual attention becomes more selective and more often guided by
their own goals and intentions. This means that attention is no longer governed merely by object
salience, such as a face-like stimulus or a moving or sounding toy. Instead, infants begin
modulating their attention in response to the actions of their social partner as well as the context.
Indeed, this is exactly what is necessary for infants to distribute their attention between a social
partner and the referent of their gesture or gaze (Bertenthal & Boyer, 2015). By learning how to
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modulate attention, infants become better tuned to the critical information communicated by the
actions and social cues of a social partner. This is why even at 6 months of age infants show
predictive looks to the mouth when observing a person grasp a cup and to the ear when they see
someone pick up a phone (Stapel et al., 2010). In this case, it is unlikely that motor experience is
responsible for infants’ goal predictions, but rather it is the repetitiveness and consistency of
these events that enable infants to begin learning the statistical regularities that will guide their
attention and predictive gaze (Saffran & Kirkham, 2018).
It is also important to note that infants are more likely to disengage rapidly when they
have had sufficient visual experience with an action (Southgate, 2013). As a consequence, they
are better able to focus their attention on the cause-effect relations of the action. For example,
infants learn over time to focus on the relevant cues associated with a goal-directed action (e.g.,
reaching with a whole-hand grip for a large object or a precision grip for a small object), and
thus the detection of these cues will eventually suffice for their predicting the action goal. As
such, infants learn associations between movement cues and goals that do not necessarily depend
on specific motor experience.
In sum, motor experience is surely contributing to the development of action
understanding, but it is unclear as to whether it holds a privileged status. This assessment may
be at least partly attributable to testing action understanding at an interpretive or evaluative level.
In a looking time experiment, infants are evaluated on the basis of whether they devote more
attention to a novel than a familiar event. There are numerous perceptual and cognitive
processes that contribute to infants’ duration of looking, and therefore it is difficult to discern
what specific process is responsible for infants looking more at a change in the goal structure of
the observed action. As a consequence, looking time studies are unable to offer definitive
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evidence that motor experience is a necessary prerequisite for the development of action
understanding. In the next section we consider whether the evidence is any stronger when
testing infants’ predictions of action goals.
Infants’ prediction of goal-directed actions
Additional evidence for infants’ understanding of goal-directed actions is provided by
eye tracking studies demonstrating that infants can anticipate the goal or the effect of an action.
When adults perform a goal-directed action their eyes precede their hands in moving toward the
goal (Flanagan & Johansson, 2003; Hayhoe & Ballard, 2005). Likewise, when observing
someone else perform a goal-directed action, the eyes move to the goal before the agent
completes the action (Flanagan & Johansson, 2003; Gredebäck & Falck-Ytter, 2015). One
interpretation for this response is that observers motorically simulate the perceived action, which
includes a prospective eye movement since this is necessary for guiding the goal-directed action
when it is executed (Flanagan & Johansson, 2003). As such, predictive gaze shifts to the goal of
an observed action are viewed as evidence for direct mapping of the observed action to the
corresponding motor routine in the brain. Recent experimental manipulations of motor activity
during observation tasks support this interpretation by revealing that prospective eye movements
are either delayed or cancelled when instructions to perform a secondary task involve the same
effector as that involved in the observed action (Ambrosini, Costantini, & Sinigaglia, 2011;
Cannon & Woodward, 2008). Given the time scale in which this behavior occurs, it is highly
probable that it is embodied and automatic and does not require more time consuming higher-
level cognitive processing. Thus, action prediction differs from the previously discussed
evaluative processes in terms of time scale and processing demands.
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In one of the first studies to test this behavior in infants, 12-month-old infants showed
anticipatory eye movements when observing goal-directed actions (i.e., placing objects in a
container) performed by a human agent, but not when observing a ‘mechanical motion’ event in
which the objects moved without being handled by a human agent (Falck-Ytter, Gredebäck, &
von Hofsten, 2006). This latter result revealing differences between the observation of human
actions and mechanical events is similar to some of the looking time findings suggesting that the
mapping between the observation and simulation of actions is restricted to the perception of
human actions (but see section II.3. on matching of non-human actions for a different
interpretation).
Although some of the early evidence suggested that infants’ goal prediction of others’
actions did not emerge until a year of age, more recent findings suggest that the goal prediction
associated with direct reaching for a visible object emerges by 6 months of age (Ambrosini,
Reddy, Looper, Costantini, Lopez, & Sinigaglia, 2013; Kanakogi & Itakura, 2011). One rational
interpretation for these discrepant findings is that infants’ action understanding is linked to their
motor experience. Whereas 6-month-old infants are already motorically capable of reaching for
an object, they are not capable of placing an object in a container. This difference in motor
experience could explain why infants’ goal prediction does not emerge at one specific age, but
rather emerges gradually as a function of the complexity and difficulty of the goal-directed
action.
In order to provide a more convincing test of this account, motor skill was independently
assessed in some studies and the results revealed that predictive eye movements and measures of
manual coordination covaried. For example, infants younger than 15 months of age are not very
proficient when trying to press a small button with a single finger because they are unable to
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modulate the speed of their movement. Likewise, it is not until 15 months of age that infants are
able to predict whether a target is a large or small button from observing the velocity of a
reaching hand with extended finger (Stapel, Hunnius, & Bekkering, 2015). In another study,
different measures of reaching for an object were correlated with infants’ goal predictions at 6
and 8 months of age (Kanakogi & Itakura, 2011). Similarly, the number of times an infant
placed an object in a container was correlated with their goal prediction of an adult placing an
object in a container (Cannon, Woodward, Gredebäck, von Hofsten, & Turek, 2012). Critically,
these last two experiments partialled out the effects of age, which often lead to spurious
correlations in developmental studies.
Nevertheless, these findings are at best only suggestive of a relation between motor
experience and goal prediction. First, there is still the possibility of a third variable, such as
attention or cognitive development contributing significantly to the correlation. Simply put,
correlation does not mean causation. Second the measures of motor skill were not identical to
the observed motor behaviors making it difficult to translate the motor skill measures into some
metric of motor experience. It is furthermore not clear whether the significant but modest
correlations were primarily attributable to mixing levels of analysis: infants’ action
understanding was measured at the level of goal prediction whereas their motor skill was
measured at the level of their kinematics. As implied earlier, there are differences in action
understanding as a function of the level of analysis, but these differences are often ignored.
Third, the interpretation of goal prediction as a function of simulation is often confounded with
the development of infants’ overt attention. More specifically, the shifting of the observer’s eyes
to the goal of another’s action could be primarily a function of the observed action cueing
attention and triggering a gaze shift. It is well established that during joint attention we
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reflexively orient in the direction cued by a gaze shift or a pointing gesture (Bertenthal et al.,
2014; Driver et al., 1999). Although this type of orienting can occur covertly and need not
necessitate an eye movement, overt orienting occurs consistently when the response measure
includes an eye movement (Kuhn & Kingstone, 2009). For similar reasons, a goal-directed
reach is likely to automatically cue our attention in the same direction, thus resulting in an
automatic gaze shift (Barton & Bertenthal, 2014). Accordingly, there is more than one
interpretation for a gaze shift preceding an action to a goal, and it need not be a function of motor
simulation.
Certainly, the capacity for prediction is a basic principle for processing incoming sensory
information and adults are capable of predictive tracking of many events that do not involve
human actions. Indeed, the smooth pursuit of any moving target could not occur without
prospective control of eye movements (Bertenthal & von Hofsten, 1998). When a moving target
is briefly occluded, the observer will predict its reappearance by extrapolating from the spatial
and temporal information that was available before the target disappeared (Bertenthal, Longo, &
Kenny, 2007). This capacity for prospective gaze shifts is not based on some higher-level
cognitive process, because it is present at very young ages. Infants begin predicting the location
of a briefly occluded moving target at 4 months of age (von Hofsten et al., 2007), and are
capable of predicting the location of alternately appearing targets at even younger ages (Haith,
1994). It is difficult to imagine how these gaze shifts could be a function of motorically
simulating the observed events. Instead, these predictive behaviors are attributable to infants
learning to respond repeatedly to the same generic events via some associative learning
mechanism. For example, infants experience everyday people and other moving objects that are
repeatedly occluded, and over the course of time learn to anticipate their reappearance in order to
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continue tracking their whereabouts. Given the natural statistics of the infants’ visual world and,
in particular, the prevalence of these moving stimuli that are tracked during infancy, it is
reasonable to consider this behavior a form of statistical learning. Consistent with other forms of
statistical learning, some regularities in the visual world are learned very rapidly. For example,
5-month-old infants are capable of learning to predictively track a briefly occluded moving
object over the course of just a few trials (Bertenthal, Gredebäck, & Boyer, 2012).
These caveats and reservations about the primacy of motor learning are especially well
illustrated in a recent experiment testing 8-month-old Chinese and Swedish infants predicting
actions performed with chopsticks and spoons (Green, Li, Lockman, & Gredebäck, 2016).
Previous research revealed that 6-month-old infants predict eating actions by a single individual
with a spoon, and that 12-month-old infants predict one person feeding another with a spoon
(Gredebäck & Melinder, 2010; Kochukhova & Gredebäck, 2010). These findings are significant
because infants are not yet performing these specific actions themselves, although they are
directing hand movements to their mouths even before birth (Lew & Butterworth, 1995).
Moreover, their visual experience with spoons and chopsticks are culturally modulated. Whereas
both Swedish and Chinese infants are fed with spoons (albeit very different looking: long handle,
flat circular bowl/Swedish; short handle, deep oval bowl/Chinese), only the Chinese infants
observe people using chopsticks on a regular basis. When infants viewed videos of actors
feeding themselves from a bowl of puffed corn snack crackers, the Swedish infants predicted the
Swedish-looking spoon reaching the mouth earlier in time than the chopsticks, whereas the
results were the opposite for Chinese infants. By contrast, neither group of infants predicted the
goal of picking up the crackers in the bowl. Critically, infants at 7 to 9 months of age do yet not
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perform object-directed actions, although they are very likely to bring a tool to their mouth
(Claxton, McCarty, & Keen, 2009; Ruff, 1984).
These results thus suggest that infants are capable of predicting actions similar to their
own motor capability, like transporting objects to their mouths, but visual experience with
spoons or chopsticks also constrains performance. One important question not addressed by this
study is whether it is necessary to distinguish between objects and tools. Both spoons and
chopsticks were used as tools, and thus they were extensions of the hands in peripersonal space,
but it is currently unknown whether this distinction makes a difference (see the next section for
further discussion of this issue).
It should by now be evident that the relation between motor experience and infants’ goal
prediction is complicated. It is undeniable that infants engage in predictive tracking, whether it
is the goal of an action or the outcome of an event, but the mechanism responsible for this
prospective response is by no means limited to motor simulation. Although it is true that motor
experience is correlated with the types of actions predicted at different ages, it is not logically
necessary that the driver for this development is active motor experience. Each action executed
by an infant requires a motor representation of its movements and goals, which could be
mediated by motor experience, but it is also modulated by selective attention. Moreover, the
observation of others’ actions and events will also contribute to the encoding of the statistical
properties of the environment, and thus increase the likelihood of infants predictively tracking
those events that are regularly observed. Currently, there is insufficient evidence to know
whether infants’ predictions of actions are specialized and mediated primarily by motor
simulation, but this seems unlikely and maladaptive given the multifarious mechanisms available
for learning about the social and physical events in the world.
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Coding goals vs. movements
In theorizing how motor experience contributes to action understanding, it is important to
recall that actions are represented at multiple, hierarchically-nested levels ranging from specific
muscle synergies to more abstract distal goals. As discussed in the preceding two sections, this
failure to appreciate the multi-level representation of actions, contributes to some of the
confusions and contradictions in the literature. It is often assumed that the mapping between
observed and executed actions occurs exclusively at the level of the goal or the effects of the
action. By defining actions in terms of goals, infants can generalize their representations more
readily to others’ goal-directed actions even if the specific movements vary (Rizzolatti &
Sinigaglia, 2012; Woodward & Gerson, 2014).
In spite of the attractiveness of coding actions at the more abstract level of goals, we wish
to caution against dismissing the importance of movements, per se, in mapping the observation
of actions to their execution. Rizzolatti and colleagues speculated that there are two distinct
resonance mechanisms2 in humans: a high-level resonance mechanism coding actions in terms
of goals, and a low-level resonance mechanism coding the movements of an action (Rizzolatti et
al., 2001). An example of this low level mechanism in humans involves recording motor evoked
potentials3 from arm muscles while participants observe a hand reaching and grasping an object
(Gangitano, Mottaghy, & Pascual-Leone, 2001). The recorded motor potentials from the
participants vary systematically with the changing size of the finger aperture as the hand
approaches the object. As such, this finding is consistent with the motor representation coding
the manner in which the action is performed over time rather coding its goal or end state.
2 Neural resonance refers to the observation of a goal-directed action resulting in the subthreshold activation of a similar action in the observer’s brain. 3 Motor evoked potentials (MEP) are recorded from muscles following stimulation of motor regions of the brain..
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Some of the best evidence for this low-level resonance mechanism in infants comes from
observing their perseverative search errors. In the classic, Piagetian A-not-B error, 8– to 12-
month-old infants first search correctly for an object they see hidden in one location (A-location)
on one or more trials, but then continue to search at that same location after seeing the object
hidden in a new location (B-location). Recent accounts of this error emphasize the role of
repeated reaching to the initial location biasing infants to continue reaching to the same location
even when no longer correct (e.g., Diamond, 1991; Smith, Thelen, Tizer, & McLin, 1999). If
infants are capable of mapping observed movements to their motor representations, then they
should commit the same search error on the B-trial even when they only observe someone else
finding the object on the initial A-trials. Just to be clear, we assume that this mapping process
activates the motor representation in a manner similar to what happens when a reach is executed.
The main difference is that the activation from observing an action results in a covert as opposed
to an overt response. Empirical support for this mapping hypothesis has been repeatedly
confirmed with 9-month-old infants, but only if the experimenter who recovers the hidden object
on the A-trials reaches with his ipsilateral hand (i.e., the hand on the same side of the body as the
object) (Bertenthal & Boyer, 2011; Boyer & Bertenthal, 2015; Longo & Bertenthal, 2006).
Why should infants be more likely to simulate the observed actions associated with an
ipsilateral than a contralateral reach (i.e., the hand crosses the body midline when reaching for an
object)? One likely reason for this finding is that infants begin to reach contralaterally about 2 to
3 months later than they begin to reach ipsilaterally, which starts around 4 to 5 months of age
(Bertenthal & von Hofsten, 1998). This developmental lag translates to infants’ showing a bias
to reach ipsilaterally throughout their first year, and results in a less developed motor
representation for contralateral reaching at the age when tested for the search error.
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Some support for this interpretation comes from a training study where 9-month-old
infants were familiarized with an experimenter reaching repeatedly for toys with only his
contralateral hand, and then searching for the hidden toy on the A-trials of the search task with
only his contralateral hand (Boyer & Bertenthal, 2015). Unlike the results from previous studies,
infants committed the search error even though contralateral reaching was observed.
Presumably, the familiarization with contralateral reaching during the training phase served to
“prime” the motor representation for contralateral reaching, and thus it was more responsive to
the experimenter’s searching during the A-not-B search task. This increased activation to the
experimenter’s actions resulted in a search bias just as the observation of the experimenter’s
ipsilateral searching resulted previously in a search bias. In a follow-up experiment, a new group
of infants was tested following familiarization with ipsilateral reaching. Even though the search
task was identical in this new condition (i.e., observation of the experimenter searching with a
contralateral reach for the hidden object), infants did not demonstrate a search bias and look for
the object more often than chance at the incorrect location. If action understanding was
exclusively a function of encoding the goal of the reaching action (i.e., retrieving the object),
then both training conditions should have primed the infant’s search bias. Instead, it was
specifically focusing the infants’ attention on the contralateral movements that increased the
likelihood that this action would be covertly simulated.
According to the mirroring hypothesis, infants observing actions performed by non-
human agents should not be mapped to their motor representations (Woodward & Gerson, 2014).
Indeed, most of the evidence with adults suggests that the observation of robotic or mechanical
actions results in less activation of the motor system (e.g., Liepelt, Prinz, Brass, 2010; Tai,
Scherfler, Brooks, Sawamoto, Castiello, 2004), and thus at the very least a diminished neural as
32
well as behavioral response. This result is typically interpreted as supporting the hypothesis that
an observation-execution matching system is limited to actions within the motor repertoire of the
observer, or that the observer codes the action at the level of its intention which cannot be
attributed to a non-human agent (e.g., Calvo-Merino, Glaser, Grezes, Passingham, Haggard,
2005; Teufel, Fletcher, Davis, 2010).
This hypothesis was tested by substituting two mechanical claws for the arms-and-hands
of the human experimenter in the A-not-B testing paradigm (Boyer, Pan, & Bertenthal, 2013).
Although the initial experiment appeared to support the mirroring hypothesis because infants
failed to show the perseverative search error, follow-up experiments suggested that the
explanation is more nuanced. As previously discussed, unfamiliar actions, such as those
produced by a claw, are likely to distract infants from directing their attention to relevant cues,
especially since the means by which a claw will grasp an object is novel and unfamiliar. In order
to minimize these effects, infants were familiarized to the appearance of the claws in Experiment
2 and they were familiarized to the appearance and function of the claws in Experiment 3. The
results revealed that familiarization to the appearance of the claws was inconsequential, but
familiarization to both the appearance and function of the claws significantly changed infants’
responses on the search task. Unlike many of the other training studies that involved self-
produced experience with unfamiliar tools, this study was limited to two minutes of infants
observing an experimenter use the claw to retrieve objects. In spite of this modest visual
experience, a significant number of infants now showed the search error suggesting that they had
mapped the actions of the claw to their own motor system.
One interpretation for these results is that infants perceived the claw as a tool once they
understood its function, and they were then able to generalize the action of the tool to their own
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reaching actions (cf. Ferrari, Rozzi, & Fogassi, 2005). A second interpretation is that the claw
was seen as an independent agent. Once infants understood its function, they were able to map
the observed goal to their own corresponding motor representation; thus the difference in
kinematics between a claw and a hand was no longer a factor. Similar explanations have been
advanced to account for activation of the mirror system in adults when observing robotic actions
(Gazzola et al., (2007). Although this latter explanation can account for infants’ understanding
of the goal of the reach, it’s less clear that activation of a broadly tuned motor representation can
account for the simulation of the specific movements hypothesized as responsible for the search
bias.
One final point about these findings should not go unnoticed. Even though infants did
not actively manipulate the claws, they appeared to learn from observing the experimenter
operate the claws. We suspect that at least in this situation infants’ observational learning
benefitted from the experimenter not performing the same identical action repeatedly, but rather
varying both the location of the toy as well as the hand used to retrieve it. As we’ve previously
discussed, variation and selection from multiple examples is a well-established mechanism to
facilitate learning (see Gazzola et al., 2007, for a related discussion). This variation is often
overlooked when comparing active and passive experience, but infants’ actions are not yet well
coordinated and thus virtually any action will vary in one or more details each time it is
executed. Accordingly, infants are assured to receive some variable experience when performing
actions themselves, but this will be less likely when modeled by an adult unless the variation is
intentional. This variation that accompanies infants’ active learning during training studies could
be an important factor in explaining why action understanding typically improves more
following active as opposed to passive learning.
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Just to be clear, the previous discussion is not meant to dismiss the importance of infants
mapping goals to their motor representations. Additional findings testing infants’ goal
predictions following ipsilateral and contralateral reaches suggests an advantage for predicting
ipsilateral reaches. Infants between 6 and 12 months of age were tested for predicting the goal of
an actor who was seen facing them while sitting at a table and reaching either ipsilaterally or
contralaterally for an object situated in front and to the side (Barton & Bertenthal, 2014). At
least through 10 months of age infants were more likely to predict the goal on ipsilateral than
contralateral trials. These infants were also tested for their likelihood of reaching ipsilaterally vs.
contralaterally, and as expected the results revealed that contralateral reaching increased with
age. More importantly, the likelihood of contralateral reaching covaried with the likelihood of
contralateral goal prediction, even after partialling out the effects of age and ipsilateral reaching.
See Melzer, Prinz, & Daum (2012) for converging evidence.
Before closing this section, we want to underscore the special importance of these
experiments. Infants served as their own yoked controls, and thus evidence of greater motor
simulation to ipsilateral than contralateral reaches was less likely a function of some spurious
correlation. These results thus add to the likelihood that motor experience and the development
of an observation-execution matching system are related, although determining whether this is a
reciprocal relation or specifically a function of motor experience mediating the mapping between
action observation and execution remains to be determined. In interpreting these results, it is
important to note that the relation between motor experience and action understanding is specific
not only to the prediction of action goals, but also to the mapping between observed and
executed movements. Some theorists (e.g., Csibra, 2007; Kilner, 2011) suggest that the
encoding of abstract or effector-general goals may be more related to a semantic pathway, and
35
thus are not dependent on motor-based representations. If this is correct, then more than one
developmental pathway may be responsible for the development of the response bias discussed
in this section.
Conclusions
The majority of research reviewed above was designed to demonstrate that action
understanding is related to motor experience. In its strong form, authors claim that motor
experience is a prerequisite for action understanding, whereas a more tempered proposal is that
motor experience is reciprocally related to action understanding. As we discussed, there remain
numerous questions and caveats to accepting either conclusion, but much of what is still needed
can be remedied by adopting a developmental systems perspective. Action understanding needs
to be studied as a dynamical system in which its development changes as a function of not only
age and experience, but also as part of a larger system of developing behaviors that interact in
complex and nonlinear ways. In general, recent research on action understanding has been
limited to hypotheses linked to one system at a time, such as the development of motor behaviors
or motor programs in the brain that are deemed responsible for understanding observed actions.
This piecemeal and fragmented approach to the study of actions results in incomplete and
inconsistent data and models. New research is needed to enable the development of more
integrated neurophysiological and behavioral models responsible for the development of action
understanding.
One important step in achieving this goal is to abandon all claims that the development of
action understanding is exclusively a function of any one factor such as motor experience,
attention and visual experience, or inferential processes related to the attainment of efficient
goals and predictive coding. As illustrated above, it is relatively easy to raise questions about
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any of these claims. This problem is at least partly attributable to the lack of precision and
specificity. For example, it is presumed in some studies that predicting the goal of a simple
reaching action will emerge synchronously or soon after infants begin object-directed reaching.
The rub with this claim is that object-directed reaching for stationary objects continues to
develop throughout most of the first year. If we define object-directed reaching using more
precise kinematic measures, the developmental relation between motor experience and action
understanding could easily change depending on the criterion we establish. More generally,
there is a tendency in this literature to measure action understanding more precisely than the
other factors related to this development, such as attention or sensitivity to predictive cues. This
asymmetry thus leaves the age of onset of the other factor more open to interpretation that can be
biased by differing theoretical views.
Regrettably, the current literature is more likely to dismiss opposing theoretical
interpretations than to attempt to integrate them in the models that are developed. Paradoxically,
most of the competing models are interrelated in terms of both common structure and function.
For example, we discussed in the review how eye tracking measures of goal prediction are
confounded with measures of overt attention. Likewise, visual experience cannot be dismissed
from motor experience, and thus cause-and-effect are difficult to disentangle (e.g., Calvo-Merino
et al., 2005). Instead of continuing to focus on research designed to contrast different models of
action understanding, more integrative models are sorely needed.
One potential risk of the current critique is to “throw out the baby with the bathwater.”
Let me be clear that this is not my intention. The study of action understanding in young
children is one of the most productive and exciting areas of research in developmental science.
The accumulation of a huge database of findings in the past decade is precisely the reason why it
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is possible to suggest new directions for future research. Given the general convergence of
findings derived from looking time, eye tracking, reaching, and EEG studies (see Bertenthal &
Boyer, 2015; Gredebäck & Daum, 2015; Gredebäck & Falck-Ytter, 2015; Woodward & Gerson,
2014 for reviews), it is very likely that motor experience and action understanding are related.
Still, one important caveat is that this relation is modulated by age, task, and context.
Conclusions concerning action understanding will depend not only on age, but on multiple other
factors.
Measuring goal prediction, for example, with eye tracking enables investigators to assess
infants’ embodied knowledge of the outcome of an action, but infants’ evaluation of the goal
structure of an action with a looking time measure does not necessitate prediction because the
response is postdictive. Moreover, the contribution of attention is very different in these two
tasks. Whereas the former task requires focused spatial attention triggering a saccadic response,
the latter task requires sustained attention at a global level, and the time demands on responding
are less demanding. Context is also often conflated with task. For example, reaching or
approaching a single object is very different than selecting between two objects, because it could
be the presence of choice that is necessary for attributing a goal (Southgate, 2013). Likewise,
training or intervention tasks designed to demonstrate that active motor experience is responsible
for improving action understanding are different than tasks assessing the effects of motor
experience over developmental time. In the former case, infants may benefit from the short-term
priming of the motor or goal structure, whereas in the latter case, infants benefit from the more
long-term and extensive motor experience which could be responsible for changing the structure
of the motor representation or the cognitive representation responsible for the prediction.
38
What are the implications of these findings for the mirroring hypothesis? This is
somewhat of a sticky question, because there is no consensus with regard to the meaning of
mirroring in the human brain (e.g., Csibra, 2007; Hasson & Frith, 2016; Kilner, 2011; Rizzolatti
& Sinigaglia, 2011). If it is assumed that action understanding relies exclusively on mirroring,
then it would seem necessary for the specific action to be part of the motor repertoire of the
infant before it would be understood. In other words, action understanding would depend on
motor experience, but this causal relation is not supported by the extant evidence. If, however,
mirroring refers to a reciprocal relation between motor experience and cognitive development,
more generally, then it could very well facilitate or attune the development of action
understanding, Currently, some of the strongest evidence suggesting that mirroring supports a
developmental relation between motor experience and action understanding comes from a select
few EEG studies revealing alpha or beta suppression in sensory-motor regions of the brain as a
function of both the observation as well as the execution of reaching actions (e.g. Filippi,
Cannon, Fox, Thorpe, Ferrari, & Woodward, 2016; Saby, Marshall, & Meltzoff, 2012; van Elk,
van Schie, Hunnius, Vesper, & Bekkering, 2008). Although suggestive of mirroring in the
baby’s brain, the evidence is subject to the same alternative explanations discussed with the
behavioral data.
What are the implications of the mirroring hypothesis for studying the development of
action understanding? There is no doubt that the discovery of mirror neurons stimulated an
enormous amount of research in this field, but it came with a cost. The vast majority of studies
have been focused on object-directed reaching, which is consistent with the bias in the field
toward goals rather than movements, per se. As a consequence, much less is known about
infants’ responses to intransitive actions involving vocalizations, facial expressions, and postural
39
responses. These are some of the key behaviors involved in social attention and dyadic social
interaction. Infants begin to mirror their caregivers’ vocalizations and facial expressions by 4
months of age (Bigelow & Walden, 2009). Although there is no direct evidence that this form of
mirroring is mediated by a direct matching mechanism, it is certainly conceivable given that
young infants are capable of vocalizing and smiling. More importantly, these infants are already
developing expectations of their caregivers’ contingent responses, such that they become
distressed when their social partner is instructed to maintain a “still face” following a period of
social engagement (Adamson & Frick, 2003). These expectations of their caregivers’ actions
can be considered another measure of action understanding. An intriguing question is whether
the violation of infants’ expectations is mediated primarily by their accumulated visual
experience with their caregiver or by their caregivers’ vocalizations and smiling mapping to their
motor representations.
Clearly, there is still much to learn about the developing relation between action
understanding and motor experience. One final example of very young infants’ responses to
their mothers’ actions involves their postural anticipation to being picked up (Reddy, Markova,
& Wallot, 2013). Infants as young as 2-months of age demonstrate anticipatory behavioral
adjustments during the approach of their mothers’ arms, and these postural adjustments become
better differentiated with age. Also, infants’ visual attention to the mothers’ hands during her
approach became more selective by 4-months of age. These findings are fascinating because
they reveal an embodied sense of action understanding at even earlier ages than observed with
reaching. They also hint at infants’ perception becoming more specialized as their postural
responses become more differentiated which is consistent with the brain developing greater
interactive specialization with age (Johnson, 2011). These last few examples are meant as a
40
challenge to the field to consider whether infants’ understanding of these sorts of actions directed
to themselves rather than to objects follow the “same rules of engagement”.
In conclusion, infants’ understanding of actions is foundational to how they learn and
socially interact with others. Knowledge by acquaintance is a driving force in young childrens’
understanding of actions, which is why motor experience is a significant contributor to their
action understanding. During the past decade, we have made enormous strides in mapping the
early development of infants’ action understanding and its dependence on multiple factors
including visual as well as motor experience, the development of visual attention, and inferential
processes for cause-effect relations. The next stage in this research enterprise will benefit greatly
from: (1) the specification of more precise models detailing how perceived actions are mapped
to motor representations; (2) more comprehensive views of the multiple ways that motor
experience contributes to action understanding; and (3) the adoption of a developmental systems
perspective emphasizing that behavior is dynamic and multi-causal and unfolds over multiple
time scales.
41
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