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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

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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

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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

References

Adamson, L. B., & Frick, J. E. (2003). The still face: A history of a shared experimental paradigm. Infancy, 4(4), 451-473.

Ambrosini, E., Costantini, M., & Sinigaglia, C. (2011). Grasping with the eyes. J Neurophysiol, 106(3), 1437-1442. doi:10.1152/jn.00118.2011

Ambrosini, E., Reddy, V., de Looper, A., Costantini, M., Lopez, B., & Sinigaglia, C. (2013). Looking ahead: anticipatory gaze and motor ability in infancy. PLoS One, 8(7), e67916. doi:10.1371/journal.pone.0067916

Bache, C., Springer, A., Noack, H., Stadler, W., Kopp, F., Lindenberger, U., & Werkle-Bergner, M. (2017). 10-Month-Old Infants Are Sensitive to the Time Course of Perceived Actions: Eye-Tracking and EEG Evidence. Front Psychol, 8, 1170. doi:10.3389/fpsyg.2017.01170

Barton, A., & Bertenthal, B. I. (2013). Infants differentially anticipate the goals of ipsilateral and contralateral reaches. Journal of Vision, 13(9), 283.

Batki, A., Baron-Cohen, S., Wheelright, S., Connellan, J., & Ahluwalia, J. (2001). How important are the eyes in neonatal face perception? Infant Behavior & Development, 23, 223-229.

Bertenthal, B. I. (1999). Variation and selection in the development of perception and action. In G. Savelsbergh (Ed.), Nonlinear analyses of developmental processes. Amsterdam: Elsevier Science Publishers.

Bertenthal, B. I., & Boyer, T. W. (2011). Brief familiraization primes covert imitation in 9-month-old infants. Paper presented at the Proceedings of the 33rd Annual Conference of the Cognitive Science Society, Boston, MA.

Bertenthal, B. I., & Boyer, T. W. (2015). Development of social attention in human infants. In A. Puce & B. I. Bertenthal (Eds.), The many faces of social attention (pp. 21-66). New York: Springer.

Bertenthal, B. I., Boyer, T. W., & Harding, S. (2014). When Do Infants Begin to Follow a Point? Developmental Psychology, 50(8), 2036-2048. doi:Doi 10.1037/A0037152

Bertenthal, B. I., Gredebäck, G., & Boyer, T. W. (2013). Differential Contributions of Development and Learning to Infants' Knowledge of Object Continuity and Discontinuity. Child Development, 84(2), 413-421. doi:Doi 10.1111/Cdev.12005

Bertenthal, B. I., & Longo, M. R. (2008). Motor knowledge and action understanding: A developmental perspective. In R. L. Klatzky, M. Behrmann, & B. MacWhinney (Eds.), Embodiment, ego-space, and action: 34th Carnegie symposium on cognition (pp. 323-368). Mahwah, NJ: Erlbaum.

Bertenthal, B. I., Longo, M. R., & Kosobud, A. (2006). Imitative response tendencies following observation of intransitive actions. Journal of Experimental Psychology-Human Perception and Performance, 32(2), 210-225. doi:Doi 10.1037/0096-1523.32.2.210

Bertenthal, B. I., & von Hofsten, C. (1998). Eye, head and trunk control: The foundation for manual development. Neuroscience and Biobehavioral Reviews, 22(4), 515-520.

Bigelow, A. E., & Walden, L. M. (2009). Infants' Response to Maternal Mirroring in the Still Face and Replay Tasks. Infancy, 14(5), 526-549. doi:10.1080/15250000903144181

Biro, S., & Leslie, A. M. (2007). Infants' perception of goal-directed actions: development through cue-based bootstrapping. Developmental Science, 10(3), 379-398. doi:DOI 10.1111/j.1467-7687.2006.00544.x

42

Boyer, T. W., & Bertenthal, B. I. (2015). Infants' observation of others' actions: Brief action-specific visual experience facilitates covert imitation. British Journal of Developmental Psychology, Submitted for publication.

Brandone, A. C., & Wellman, H. M. (2009). You can't always get what you want: infants understand failed goal-directed actions. Psychological Science, 20(1), 85-91. doi:10.1111/j.1467-9280.2008.02246.x

Calvo-Merino, B., Glaser, D. E., Grezes, J., Passingham, R. E., & Haggard, P. (2005). Action observation and acquired motor skills: An fMRI study with expert dancers. Cerebral Cortex, 15, 1243-1249.

Cannon, E. N., & Woodward, A. L. (2008). Action anticipation and interference: A test of prospective gaze. Paper presented at the Proceedings of the 30th Annual Conference of the Cogntiive Science Society, Austin, TX.

Cannon, E. N., Woodward, A. L., Gredebäck, G., von Hofsten, C., & Turek, C. (2012). Action production influences 12-month-old infants' attention to others' actions. Dev Sci, 15(1), 35-42. doi:10.1111/j.1467-7687.2011.01095.x

Chaminade, T., Meltzoff, A. N., & Decety, J. (2002). Does the end justify the means? A PET exploration of the mechanisms involved in human imitation. NeuroImage, 15, 318-328.

Claxton, L. J., McCarty, M. E., & Keen, R. (2009). Self-directed action affects planning in tool-use tasks with toddlers. Infant Behav Dev, 32(2), 230-233. doi:10.1016/j.infbeh.2008.12.004

Cook, R., Bird, G., Catmur, C., Press, C., & Heyes, C. (2014). Mirror neurons: From origin to function. Behavioral and Brain Sciences, 37(2), 177-192. doi:Doi 10.1017/S0140525x13000903

Corbetta, M., & Shulman, G. L. (2002). Control of goal-directed and stimulus-driven attention in the brain. Nature Reviews Neuroscience, 3(3), 201-215. doi:Doi 10.1038/Nrn755

Csibra, G. (2007). Action mirroring and action interpretation: An alternative account. In P. Haggard, Y. Rosetti, & M. Kawato (Eds.), Attention and performance (Vol. XXII, pp. 435-459). Oxford, UK: Oxford University Press.

Custance, D. M., Whiten, A., & Bard, K. A. (1995). Can Young Chimpanzees (Pan Troglodytes) Imitate Arbitrary Actions? Hayes & Hayes (1952) Revisited. Behaviour, 132(11-12), 837-859.

Daum, M. M., Attig, M., Gunawan, R., Prinz, W., & Gredebäck, G. (2012). Actions Seen through Babies' Eyes: A Dissociation between Looking Time and Predictive Gaze. Front Psychol, 3, 370. doi:10.3389/fpsyg.2012.00370

Daum, M. M., & Gredebäck, G. (2011). The development of grasping comprehension in infancy: covert shifts of attention caused by referential actions. Exp Brain Res, 208(2), 297-307. doi:10.1007/s00221-010-2479-9

Daum, M. M., Prinz, W., & Aschersleben, G. (2009). Means-End Behavior in Young Infants: The Interplay of Action Perception and Action Production. Infancy, 14(6), 613-640. doi:Pii 917026622 Doi 10.1080/15250000903263965

Daum, M. M., Ulber, J., & Gredebäck, G. (2013). The development of pointing perception in infancy: effects of communicative signals on covert shifts of attention. Developmental Psychology, 49(10), 1898-1908. doi:10.1037/a0031111

Decety, J., Chaminade, T., Grezes, J., & Meltzoff, A. N. (2002). A PET exploration of the neural mechanisms involved in reciprocal imitation. NeuroImage, 15, 265-272.

43

Decety, J., & Sommerville, J. A. (2003). Shared representations between self and others: A social cognitive neuroscience view. Trends Cogn Sci, 7, 527-533.

Diamond, A. (1991). Neuropsychological Insights into the Meaning of Object Concept Development. In S. Carey & R. Gelman (Eds.), The Epigenesis of Mind: Essays on Biology and Cognition (pp. 67-110). Hillsdale, NJ: Erlbaum.

Driver, J., Davis, G., Ricciardelli, P., Kidd, P., Maxwell, E., & Baron-Cohen, S. (1999). Gaze perception triggers reflexive visuospatial orienting. Visual Cognition, 6(5), 509-540.

Elsabbagh, M., Fernandes, J., Webb, S. J., Dawson, G., Charman, T., Johnson, M. H., & British Autism Study of Infant Siblings, T. (2013). Disengagement of visual attention in infancy is associated with emerging autism in toddlerhood. Biol Psychiatry, 74(3), 189-194. doi:10.1016/j.biopsych.2012.11.030

Falck-Ytter, T., Gredebäck, G., & von Hofsten, C. (2006). Infants predict other people's action goals. Nat Neurosci, 9(7), 878-879. doi:10.1038/nn1729

Ferrari, P. F., Tramacere, A., Simpson, E. A., & Iriki, A. (2013). Mirror neurons through the lens of epigenetics. Trends Cogn Sci, 17(9), 450-457. doi:10.1016/j.tics.2013.07.003

Filippi, C. A., Cannon, E. N., Fox, N. A., Thorpe, S. G., Ferrari, P. F., & Woodward, A. L. (2016). Motor System Activation Predicts Goal Imitation in 7-Month-Old Infants. Psychological Science, 27(5), 675-684. doi:10.1177/0956797616632231

Flanagan, J. R., & Johansson, R. S. (2003). Action plans used in action observation. Nature, 424(6950), 769-771. doi:10.1038/nature01861

Friesen, C. K., & Kingstone, A. (1998). The eyes have it: reflexive orienting is triggered by non-predictive gaze. Psychonomic Bulletin and Review, 53, 490-495.

Gallese, V., Fadiga, L., Fogassi, L., & Rizzolatti, G. (1996). Action recognition in the premotor cortex. Brain, 119 ( Pt 2), 593-609.

Gallese, V., & Sinigaglia, C. (2011). What is so special about embodied simulation? Trends Cogn Sci, 15(11), 512-519. doi:10.1016/j.tics.2011.09.003

Gangitano, M., Mattaghy, F. M., & Pascual-Leone, A. (2001). Phase-specific modulation of cortical motor output during movement observation. Neuroreport, 12, 1489-1492.

Gazzola, V., Rizzolatti, G., Wicker, B., & Keysers, C. (2007). The anthropomorphic brain: The mirror neuron system responds to human and robotic actions. NeuroImage, 35(4), 1674-1684. doi:10.1016/j.neuroimage.2007.02.003

Gerson, S. A., & Woodward, A. L. (2012). A claw is like my hand: comparison supports goal analysis in infants. Cognition, 122(2), 181-192. doi:10.1016/j.cognition.2011.10.014

Gerson, S. A., & Woodward, A. L. (2014). The joint role of trained, untrained, and observed actions at the origins of goal recognition. Infant Behav Dev, 37(1), 94-104. doi:10.1016/j.infbeh.2013.12.013

Gottlieb, G. (1976). The roles of experience in the development of behavior and the nervous system. In G. Gottlieb (Ed.), Neural and behavioral specificity. Neww York: Academic Press.

Grafton, S. T., Arbib, M. A., Fadiga, L., & Rizzolatti, G. (1996). Localization of grasp representations in humans by positron emission tomography. 2. Observation compared with imagination. Experimental Brain Research, 112, 103-111.

Gredebäck, G., & Daum, M. M. (2015). The Microstructure of Action Perception in Infancy: Decomposing the Temporal Structure of Social Information Processing. Child Dev Perspect, 9(2), 79-83. doi:10.1111/cdep.12109

44

Gredebäck, G., & Falck-Ytter, T. (2015). Eye Movements During Action Observation. Perspectives on Psychological Science, 10(5), 591-598. doi:10.1177/1745691615589103

Gredebäck, G., & Melinder, A. (2010). Infants' understanding of everyday social interactions: A dual process account. Cognition, 114(2), 197-206. doi:10.1016/j.cognition.2009.09.004

Green, D., Li, Q., Lockman, J. J., & Gredebäck, G. (2016). Culture Influences Action Understanding in Infancy: Prediction of Actions Performed With Chopsticks and Spoons in Chinese and Swedish Infants. Child Development, 87(3), 736-746. doi:10.1111/cdev.12500

Greenwald, A. G. (1970). A choice reaction time test of ideomotor theory. Journal of Experimental Psychology, 86, 20-25.

Haith, M. M. (1994). Visual expectations as the first step toward the development of future-oriented processes. In M. M. Haith, J. B. Benson, R. J. Roberts, & B. F. Pennington (Eds.), The development of future-oriented processes (pp. 11-38). Chicago: University of Chicago Press.

Hamilton, A. F. D., & Grafton, S. T. (2006). The motor hierarchy: from kinematics to goals and intentions. In P. Haggard, Y. Rosetti, & M. Kawato (Eds.), Sensorimotor foundations of higher cognition. Attention and performance XXII (pp. 381-408). Oxford, England: Oxford University Press.

Hasson, U., & Frith, C. D. (2016). Mirroring and beyond: coupled dynamics as a generalized framework for modelling social interactions. Philosophical Transactions of the Royal Society B-Biological Sciences, 371(1693). doi:ARTN 20150366 10.1098/rstb.2015.0366

Hayhoe, M., & Ballard, D. (2005). Eye movements in natural behavior. Trends Cogn Sci, 9(4), 188-194. doi:10.1016/j.tics.2005.02.009

Held, R., & Hein, A. (1963). Movement-produced stimulation in the development of visually guided reaching. Journal of Comparative and Physiological Psychology, 56, 872-876.

Hofer, T., Hauf, P., & Aschersleben, G. (2005). Infant's perception of goal-directed actions performed by a mechanical device. Infant Behavior & Development, 28(4), 466-480. doi:DOI 10.1016/j.infbeh.2005.04.002

Hommel, B., Musseler, J., Aschersleben, G., & Prinz, W. (2001). The theory of event coding (TEC): A framework for perception and action planning. Behavioral and Brain Sciences, 24, 849-937.

Hood, B. M., Willen, J. D., & Driver, J. (1998). Adult's eyes trigger shifts of visual attention in human infants. Psychological Science, 9(2), 131-134. doi:Doi 10.1111/1467-9280.00024

Hunnius, S., & Bekkering, H. (2014). What are you doing? How active and observational experience shape infants' action understanding. Philos Trans R Soc Lond B Biol Sci, 369(1644), 20130490. doi:10.1098/rstb.2013.0490

Iacoboni, M., Woods, R. P., Brass, M., Bekkering, H., Mazziotta, J. C., & Rizzolatti, G. (1999). Cortical mechanisms of human imitation. Science, 286, 2526-2528.

Jacob, P. (2013). How from action-mirroring to intention-ascription? Conscious Cogn, 22(3), 1132-1141. doi:10.1016/j.concog.2013.02.005

James, W. (1890). The principles of psychology (Vol. 1). New York: Dover Publications. Jeannerod, M. (1994). A theory of representation-driven actions. In U. Neisser (Ed.), The

perceived self: Ecological and interpersonal sources of self knowledge (pp. 68-88). New York: Cambridge University Press.

Johnson, M. H. (2011). Developmental cognitive neuroscience (Third ed.). Oxford: Wiley-Blackwell.

45

Johnson, M. H., & Morton, J. (1991). Biology and Cognitive Development: The Case of Face Recognition. Oxford: Blackwell.

Johnson, S. C., Ok, S. J., & Luo, Y. (2007). The attribution of attention: 9-month-olds' interpretation of gaze as goal-directed action. Dev Sci, 10(5), 530-537. doi:10.1111/j.1467-7687.2007.00606.x

Kamewari, K., Kato, M., Kanda, T., Ishiguro, H., & Hiraki, K. (2005). Six-and-a-half-month-old children positively attribute goals to human action and to humanoid-robot motion. Cognitive Development, 20(2), 303-320. doi:10.1016/j.cogdev.2005.04.004

Kanakogi, Y., & Itakura, S. (2011). Developmental correspondence between action prediction and motor ability in early infancy. Nat Commun, 2, 341. doi:10.1038/ncomms1342

Kilner, J. M. (2011). More than one pathway to action understanding. Trends Cogn Sci, 15(8), 352-357. doi:10.1016/j.tics.2011.06.005

Kochukhova, O., & Gredebäck, G. (2010). Preverbal infants anticipate that food will be brought to the mouth: an eye tracking study of manual feeding and flying spoons. Child Development, 81(6), 1729-1738. doi:10.1111/j.1467-8624.2010.01506.x

Kuhn, G., & Kingstone, A. (2009). Look away! Eyes and arrows engage oculomotor responses automatically. Atten Percept Psychophys, 71(2), 314-327. doi:10.3758/APP.71.2.314

Lew, A. R., & Butterworth, G. (1995). The effects of hunger on hand-mouth coordination in newborn infants. Developmental Psychology, 31, 456-463.

Libertus, K., & Needham, A. (2010). Teach to reach: the effects of active vs. passive reaching experiences on action and perception. Vision Res, 50(24), 2750-2757. doi:10.1016/j.visres.2010.09.001

Liepelt, R., Prinz, W., & Brass, M. (2010). When do we simulate non-human agents? Dissociating communicative and non-communicative actions. Cognition, 115(3), 426-434. doi:10.1016/j.cognition.2010.03.003

Liszkowski, U., Carpenter, M., & Tomasello, M. (2007). Pointing out new news, old news, and absent referents at 12 months of age. Developmental Science, 10(2), 1-7. doi:DOI 10.1111/j.1467-7687.2006.00552.x

Longo, M. R., & Bertenthal, B. I. (2006). Common Coding of Observation and Execution of Action in 9-Month-Old Infants. Infancy, 10(1), 43-59. doi:10.1207/s15327078in1001_3

Luo, Y. Y. (2011). Three-month-old infants attribute goals to a non-human agent. Developmental Science, 14(2), 453-460. doi:10.1111/j.1467-7687.2010.00995.x

Melzer, A., Prinz, W., & Daum, M. M. (2012). Production and perception of contralateral reaching: a close link by 12 months of age. Infant Behav Dev, 35(3), 570-579. doi:10.1016/j.infbeh.2012.05.003

Posner, M. I. (1980). Orienting of attention. Q J Exp Psychol, 32(1), 3-25. Nishitani, N., & Hari, R. (2000). Temporal dynamics of cortical representation for action.

Proceedings of the National Academy of Science, 97, 913-918. Reddy, V., Markova, G., & Wallot, S. (2013). Anticipatory adjustments to being picked up in

infancy. PLoS One, 8(6), e65289. doi:10.1371/journal.pone.0065289 Reid, V. M., Hoehl, S., Grigutsch, M., Groendahl, A., Parise, E., & Striano, T. (2009). The

Neural Correlates of Infant and Adult Goal Prediction: Evidence for Semantic Processing Systems. Developmental Psychology, 45(3), 620-629. doi:10.1037/a0015209

Rizzolatti, G., & Craighero, L. (2004). The mirror-neuron system. Annu Rev Neurosci, 27, 169-192. doi:10.1146/annurev.neuro.27.070203.144230

46

Rizzolatti, G., & Fabbri-Destro, M. (2008). The mirror system and its role in social cognition. Current Opinion in Neurobiology, 18(2), 179-184. doi:10.1016/j.conb.2008.08.001

Rizzolatti, G., Fadiga, L., Gallese, V., & Fogassi, L. (1996). Premotor cortex and the recognition of motor actions. Cognitive Brain Research, 3, 131–141

Rizzolatti, G., Fogassi, L., & Gallese, V. (2001). Neurophysiological mechanisms underlying the understanding and imitation of action. Nature Reviews Neuroscience, 2, 661-670.

Rizzolatti, G., & Sinigaglia, C. (2010). The functional role of the parieto-frontal mirror circuit: interpretations and misinterpretations. Nature Reviews Neuroscience, 11(4), 264-274. doi:10.1038/nrn2805

Rohlfing, K. J., Longo, M. R., & Bertenthal, B. I. (2012). Dynamic pointing triggers shifts of visual attention in young infants. Developmental Science, 15(3), 426-435. doi:DOI 10.1111/j.1467-7687.2012.01139.x

Ruff, H. (1984). Infants' manipulative exploration of objects: Effects of age and object characteristics. Developmental Psychology, 20, 9-20.

Saby, J. N., Marshall, P. J., & Meltzoff, A. N. (2012). Neural correlates of being imitated: an EEG study in preverbal infants. Soc Neurosci, 7(6), 650-661. doi:10.1080/17470919.2012.691429

Saffran, J. R., & Kirkham, N. Z. (2018). Infant statistical learning. Annual Review of Psychology, 69. doi:https://doi.org/10.1146/annurev-psych-122216-011805

Smith, L. B., Thelen, E., Titzer, R., & McLin, D. (1999). Knowing in the Context of Acting: The Task Dynamics of the A-not-B Error. Psychological Review, 106(2), 235-260.

Sodian, B., & Thoermer, C. (2004). Infants' understanding of looking, pointing, and reaching as cues to goal-directed action. Journal of Cognition and Development, 5(3), 289-316.

Sommerville, J. A., Hildebrand, E. A., & Crane, C. C. (2008). Experience matters: The impact of doing versus watching on infants' subsequent perception of tool-use events. Developmental Psychology, 44(5), 1249-1256. doi:Doi 10.1037/A0012296

Sommerville, J. A., & Woodward, A. L. (2005). Pulling out the intentional structure of action: the relation between action processing and action production in infancy. Cognition, 95(1), 1-30. doi:DOI 10.1016/j.cognition.2003.12.004

Sommerville, J. A., Woodward, A. L., & Needham, A. (2005). Action experience alters 3-month-old infants' perception of others' actions. Cognition, 96, B1-B11.

Southgate, V. (2013). Do infants provide evidence that the mirror system is involved in action understanding? Conscious Cogn, 22(3), 1114-1121. doi:10.1016/j.concog.2013.04.008

Stapel, J. C., Hunnius, S., & Bekkering, H. (2015). Fifteen-month-old infants use velocity information to predict others' action targets. Front Psychol, 6, 1092. doi:10.3389/fpsyg.2015.01092

Stapel, J. C., Hunnius, S., van Elk, M., & Bekkering, H. (2010). Motor activation during observation of unusual versus ordinary actions in infancy. Social Neuroscience, 5(5-6), 451-460. doi:Pii 927979693 10.1080/17470919.2010.490667

Tai, Y. F., Scherfler, C., Brooks, D. J., Sawamoto, N., & Castiello, U. (2004). The human premotor cortex is 'mirror' only for biological actions. Current Biology, 14, 117-120.

Tessari, A., & Rumiati, R. I. (2004). The strategic control of multiple routes in imitation of actions. J Exp Psychol Hum Percept Perform, 30(6), 1107-1116. doi:10.1037/0096-1523.30.6.1107

47

Teufel, C., Fletcher, P. C., & Davis, G. (2010). Seeing other minds: attributed mental states influence perception. Trends in Cognitive Sciences, 14(8), 376-382. doi:DOI 10.1016/j.tics.2010.05.005

Thoermer, C., Woodward, A., Sodian, B., Perst, H., & Kristen, S. (2013). To get the grasp: seven-month-olds encode and selectively reproduce goal-directed grasping. J Exp Child Psychol, 116(2), 499-509. doi:10.1016/j.jecp.2012.12.007

Tomasello, M., & Call, J. (1997). Primate cognition. Oxford: Oxford University Press. Tomasello, M., Carpenter, M., & Liszkowski, U. (2007). A new look at infant pointing. Child

Development, 78(3), 705-722. doi:DOI 10.1111/j.1467-8624.2007.01025.x van Elk, M., van Schie, H. T., Hunnius, S., Vesper, C., & Bekkering, H. (2008). You'll never

crawl alone: neurophysiological evidence for experience-dependent motor resonance in infancy. NeuroImage, 43(4), 808-814. doi:10.1016/j.neuroimage.2008.07.057

von Hofsten, C., Kochukhova, O., & Rosander, K. (2007). Predictive tracking over occlusions by 4-month-old infants. Dev Sci, 10(5), 625-640. doi:10.1111/j.1467-7687.2007.00604.x

Woodward, A. L. (1998). Infants selectively encode the goal object of an actor's reach. Cognition, 69, 1-34.

Woodward, A. L. (2003). Infants' developing understanding of the link between looker and object. Developmental Science, 6(3), 297-311.

Woodward, A. L. (2009). Infants' grasp of others' intentions. Curr Dir Psychol Sci, 18(1), 53-57. doi:10.1111/j.1467-8721.2009.01605.x

Woodward, A. L., & Gerson, S. A. (2014). Mirroring and the development of action understanding. Philos Trans R Soc Lond B Biol Sci, 369(1644), 20130181. doi:10.1098/rstb.2013.0181