To elucidate the working mechanism behind anthropomorphism, this study investigated whether human participants would anthropomorphize a robot more if they move synchronously versus non-synchronously with it, and whether this is affected by which of the two initiates the movements. We tested two competing hypotheses. The feature-overlap hypothesis predicts that moving in synchrony would increase perceived self-other feature overlap, which in turn might spread activation to codes of features related to humans—which should increase anthropomorphization. In contrast, the autonomy hypothesis predicts that unpredictability increases anthropomorphization, and thus that whenever the robot initiates movements, or when the human initiates movements to which the robot moves non-synchronously, there is an increased perception of the robot as a more human-like, intentionally acting creature, which in turn should increase anthropomorphization. We performed a study with synchrony as within-subjects factor, and initiator (robot or human) as between-subjects factor. To study the impact of synchrony on self-other overlap and perception of human likeness, participants completed two tasks that served as implicit measures of state anthropomorphization, and two questionnaires that served as explicit measures of state anthropomorphization toward the robot. The two implicit measures were the joint Simon task and one-shot Dictator Game. Additionally, participants filled in a trait anthropomorphization questionnaire, to enable correction for baseline tendencies to anthropomorphize. The synchrony manipulation did not affect the joint Simon effect, although there was an effect on average reaction time (RT), where in the group in which the robot initiated the movement, RTs were slower when the human and robot moved non-synchronously. The Dictator Game offer and the state anthropomorphization questionnaires were not affected by the synchrony manipulation. There was, however, a positive correlation between current anthropomorphization of the robot and amount of money offered to it. Given that most measures were not systematically affected by our manipulation, it appears that either our design was suboptimal, or that synchronization does not affect the anthropomorphization of a robot.

Keywords: anthropomorphization, robot, synchrony, Simon task, Dictator Game, imitation, agency, self-other overlap

Edited by:

Eszter Somogyi, University of Portsmouth, United Kingdom

#### Reviewed by:

Barbara C. N. Müller, Radboud University Nijmegen, Netherlands Bruno Lara, Universidad Autónoma del Estado de Morelos, Mexico

> \*Correspondence: Saskia Heijnen<EMAIL_ADDRESS>
#### Specialty section:

This article was submitted to Cognition, a section of the journal Frontiers in Psychology

Received: 19 June 2018 Accepted: 04 December 2018 Published: 08 January 2019

#### Citation:

Heijnen S, de Kleijn R and Hommel B (2019) The Impact of Human–Robot Synchronization on Anthropomorphization. Front. Psychol. 9:2607. doi: 10.3389/fpsyg.2018.02607

### INTRODUCTION

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Anthropomorphization is commonly defined as the attribution of human mental states and characteristics to non-human animals and objects. There are two components to anthropomorphization: attributing human physical features to non-human animals and objects (e.g., seeing a face in the clouds), and attributing a human mind to non-human animals and objects (Waytz et al., 2010).  Anthropomorphization has a strong impact on how humans perceive, appreciate, and interact with artificial systems and robots in particular. Ample evidence suggests that a greater tendency to anthropomorphize—be it due to individual traits or situational factors—increases the acceptability of robots and the degree to which people enjoy interacting with and trust robots (for reviews, see Hancock et al., 2011; Fink, 2012; Zlotowski, 2015).

The present study investigated the effect of synchronous movement on the anthropomorphization of robots. In humans, moving in synchrony has been shown to have a strong impact on the interpersonal relationship and self-other representation. For instance, individuals who synchronized their behavior felt more connected and thought the other was more similar to themselves (Valdesolo et al., 2010). Synchronized behavior also led to increased similarity ratings, compassion, and a higher tendency to display altruistic behavior by helping the person that had been synchronized with (Valdesolo and DeSteno, 2011). We consider the possibility that synchronized movement might not only affect the relationship and perceived similarity between two humans but also between a human and a robot. As we will explain more elaborately below, this might depend on the overlap of the representations of the self and the other. That such representations can be extended to non-biological objects is consistent with findings that non-biological objects can become part of one's own body representation: Ma and Hommel (2015) have demonstrated ownership illusions for a balloon and a rectangle in the condition in which the object moved in synchrony with the participant's hand.

We hypothesized that synchronous movement could affect anthropomorphization of a robot in two, opposing, ways. On the one hand, synchrony may increase the perceived similarity between human and robot, because moving in the same way would be an event feature that human and robot would share, and this might increase anthropomorphization—the feature overlap hypothesis. On the other hand, however, one may also argue that non-synchronous behavior of a robot increases the perception of its autonomy which, as perceived autonomy (or agency) may contribute to anthropomorphization, may lead to stronger anthropomorphization—the autonomy hypothesis.

### The Feature Overlap Hypothesis

The first hypothesis is derived from the Theory of Event Coding (TEC: Hommel et al., 2001), which assumes that the same codes are used to represent perception and action features (Prinz, 1990). Thus, watching someone ride a bike involves the activation of codes that largely overlap with those activated by actually riding a bike oneself. Events are thus represented by networks of feature codes referring to the perceptual and action-related aspects of the event, weighted by the contextual relevance of the involved feature dimensions (Memelink and Hommel, 2013). Two implications of this approach are important for our hypothesis. First, the activation of features follows a pattern-completion logic: if one code of an event representation is activated, activation will spread to the remaining members of the representational code network, so that seeing a bike wheel will not only activate the feature bike wheel but will also spread to the codes representing bike, chain, saddle, and pedal, whether these are currently visible or not. Second, TEC does not distinguish between social and non-social events (Hommel et al., 2009), suggesting that it can be applied to humans and non-humans alike.

Combining these two implications allows us to derive a straightforward prediction with respect to the possible impact of synchronous movement. If a human participant and a robot are instructed to move synchronously, as compared to non-synchronously, they share a salient, task-relevant feature. This would render the self-representation of the human and his/her representation of the robot more similar, which should reduce self-robot discriminability. Reducing the discriminability between the representations of two events is likely to allow for feature migration from one representation to the other. For simple objects, this has been first demonstrated by Treisman and Gelade (1980), who found that distracting attention increases the probability of attributing the features of one object to another, simultaneously visible object. Extending the logic of this approach to social situations, Ma et al. (2016) have shown evidence of feature migration from a virtual face that moved in synchrony with the movements of a human participant: in contrast to a condition with non-synchronous movements, the synchrony condition led to more positive mood and better performance in a mood-sensitive creativity task when the avatar started smiling—suggesting that the avatar's mood migrated to the participant. If we assume that feature migration goes both ways—i.e., features of the other may affect features I associate with myself; features I associate with myself may affect features I associate with the other—it is possible that a synchronously moving robot leads human participants to attribute more human features to the robot, which in turn should lead to stronger anthropomorphization.

Empirical support for this consideration can be found in Morewedge et al. (2007), who demonstrated that when an animal, a robot, or an animated blob move at a speed that is closer to the average human speed of moving, it is anthropomorphized more. Along the same lines, a gender-neutral robot talking in a human-like voice (but not one talking in a robot-like voice) was anthropomorphized more when the gender of the participant matched the gender of the voice (Eyssel et al., 2012). Given that in-group members are seen to overlap with the self more than out-group members (Tropp and Wright, 2001), it is interesting to note another study which showed that a robot was anthropomorphized and liked more when it was presented as in-group, as compared to out-group (Kuchenbrandt et al., 2013). Participants were primed with either a picture of the robot or a picture of a computer, and then had to indicate whether a target word was a primary (e.g., happy) or secondary (e.g., hopeful) emotion, or no emotion at all. When the participants were told that they were in the same group as the robot, being primed with the robot coincided with quicker responses to secondary emotions, than being primed with the computer did. Given that secondary emotions are considered exclusively human (Leyens et al., 2000, 2001), the authors interpreted this as meaning that the in-group robot activated the concept "human."

### The Autonomy Hypothesis

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In their three-factor theory of anthropomorphization, Epley et al. (2007) suggest that unpredictability leads to increased anthropomorphization of a target. Humans generally like to interact effectively with the environment, and this is easier when the environment is predictable. The authors suggest that by attributing human characteristics, such as goals and intentions, to the unpredictably behaving non-human target, people become better able to predict its behavior, and thus resolve the tension between the desire to predict and the actual unpredictability. From that perspective, one might argue that the tendency to anthropomorphize should increase with the degree of unpredictability of another agent. Indeed, Epley et al. (2007) suggest that unpredictability of another agent induces the impression of this agent to be more autonomous a feature that characterizes humans—which in turn should facilitate the attribution of other human characteristics to the agent. This implies that a robot that moves nonsynchronously with a human participant, or that initiates unpredictable movements, should elicit a stronger tendency to anthropomorphize than a robot that moves synchronously with the human.

### The Current Study

To test the feature-overlap hypothesis against the autonomy hypothesis (for the first time, to the best of our knowledge), we exposed human participants to a robot with whom the participants were to interact. This interaction entailed making head movements that were the same as or different from the action partner's before a computer task that required head movements for responses—thus rendering head movements task-relevant. Three kinds of dependent measures were taken to assess various aspects and implications of anthropomorphization.

First, we used the joint Simon task as a measure of spatial self-other discrimination, and thereby as implicit measure of anthropomorphization. In the regular Simon task (Craft and Simon, 1970; Simon, 1990), one person responds to the identity of one of two different stimuli with a left or right button press on each trial. The stimuli are randomly presented either to the left or the right of a fixation cross, which consistently yields faster and more correct responses if the location of the stimulus and location of the response correspond (the congruent trials)—i.e., the stimulus is presented on the right and the correct response is the right-hand button—than if they do not correspond (the incongruent trials). This difference is called the Simon effect. Interestingly, the effect is also obtained if only one of the two keys is operated by the participant while the other is operated by another agent, whether this is another human being (Sebanz et al., 2003), a wooden hand or a Japanese waving cat (Dolk et al., 2013; Stenzel and Liepelt, 2016). In this version, called the 'joint Simon task,' the task is essentially a go/no-go task, requiring a response only when one of the two stimuli appears. The congruency effect in this paradigm is called the 'joint Simon effect.' Importantly for our purposes, the joint Simon effect was also obtained in a study where a human participant worked side-by-side with a robot (Stenzel et al., 2012), and the effect was larger when participants were either told that the robot was programmed in a "biologically inspired, autonomous way" than when they were told that it was programmed in a "purely deterministic way." Another recent study found a joint Simon effect in virtual reality both when the co-actor was a human hand and when it was a robotic hand (Bunlon et al., 2018). Stenzel et al. (2013) similarly found a joint Simon effect for a robotic co-actor, but failed to find a relationship between the size of the effect and explicit self-other inclusion, as measured by asking participants which of six images ranging from widely separated to highly overlapping circles best described the relation between the participant and the robot (the Inclusion of the Other in the Self scale, IOS). The latter is striking from the point of view of the feature overlap hypothesis, though it might be accounted for by the fact that there was no manipulation of self-other similarity. Likewise, Wen and Hsieh (2015) have found a joint Simon effect in participants undergoing fMRI who believed they were performing the task together with a robot, although they found reduced activation in areas associated with thinking about beliefs and intentions of others when compared to neuronal activation of participants who believed they were performing the task with another human. Here too, a manipulation of self-other similarity may have made a difference.

In line with Dolk et al. (2014), we interpret the joint Simon effect as the degree to which the presence of another agent is considered in (i.e., related to) one's own representation of the task. Since this makes it more difficult to determine whose turn it is on a given trial, the more the other is considered in one's own task-representation, the greater is the need to distinguish between oneself and the other. An obvious way to distinguish oneself from the other is via location, which makes location task-relevant. This increases attention to location—the feature that produces the Simon effect. Greater self-other similarity, and the subsequent greater reliance on location information that is required to deal with this similarity in order to perform on the task, leads to a more pronounced Simon effect. Hence, a larger joint Simon effect indicates larger self-other similarity, which, according to the feature-overlap hypothesis, is grounds for migration of self-related features to the other, resulting in increased anthropomorphization. However, in a task that requires two agents to take turns, greater self-other similarity might impair response selection even independently from the Simon effect proper. If so, one would not (or not only) expect synchrony between human robots to increase the size of the Simon effect but it may also affect reaction time (RT) in general.

Second, we used the Dictator Game to assess altruism, and thereby as implicit measure of anthropomorphization. Originally a method in experimental economics (Kahneman et al., 1986), the Dictator Game is often used to study fairness, rejection, and altruism, among other things (List, 2007), although it should be noted that other factors such as experimental demand characteristics and social norms play a role as well (Bardsley, 2008). In the Dictator Game, one person is the "dictator" who decides how a given amount of money will be distributed between him- or herself and another player. The other player has no choice but to accept the proposed distribution, hence the term "dictator" to characterize the former player. Since the human and robot were performing the Simon task together, and no competitive elements were present nor highlighted, we expected that the participant would consider the robot as a collaborator. Ben-Ner and Kramer (2011) have shown that collaborators are given higher stakes than neutral and competitive opponents, so we expected that more anthropomorphization of the robot would go along with more money given to it. One might object that giving money to a robot could seem counterintuitive (after all, what is it going to use it for?), but previous studies suggest that people are not entirely reluctant to give money to robots (Torta et al., 2013; de Kleijn et al., 2019). Given that synchronization promotes altruism (Valdesolo and DeSteno, 2011), we predicted that synchronized movement with a robot would lead to more money given to it in a one-shot Dictator Game.

Third, three questionnaires were used, two to assess state anthropomorphization (e.g., "Overall, do you believe QBo is capable of having intentions?"; Kozak et al., 2006; Epley et al., 2007; Torta et al., 2013) and one designed to assess trait anthropomorphization (e.g., "To what extent does the average reptile have consciousness?"; Waytz et al., 2010). The state anthropomorphization questionnaires served as explicit measures of anthropomorphization toward the robot, whereas the joint Simon task and Dictator game served as implicit measures of anthropomorphization toward the robot.

In sum, we tested how human participants would be affected by synchronously and non-synchronously moving with a robot in terms of explicit anthropomorphization and implicit measures that would be expected to relate to the degree of anthropomorphization. We distinguished between explicit and implicit measures due to evidence that these may diverge (Kim and Sundar, 2012). Based on the feature-overlap hypothesis, we expected that synchronous movement, compared to non-synchronous movement, would result in a larger joint Simon effect, higher stakes offered in the Dictator Game, and higher state anthropomorphization scores. In contrast, the autonomy hypothesis would predict that synchronous and/or predictable movement (i.e., the robot synchronizing with humaninitiated movement) should lead to lower anthropomorphization scores, a smaller joint Simon effect, and lower stakes in the Dictator Game, as compared to non-synchronous and/or unpredictable movement (i.e., the robot moving differently compared to the human-initiated movement, or the robot initiating movements).

### MATERIALS AND METHODS

### Participants

An a priori power analysis using G∗Power <IP_ADDRESS> (Faul et al., 2007) indicated a required sample size of 52 participants, based on an expected effect size of d = 0.4, informed by an informal review of the literature. Fifty-four participants were recruited (35 female), most of which (36) were Leiden University students. They were recruited through advertisements, word of mouth, and via e-mail invitations. One participant was excluded from analysis due to evident failure to understand the instructions. The mean age was 23.3 years (total range: 19–30). Inclusion criteria were: healthy adults between 18 and 30 years of age with normal or corrected-to-normal vision. Exclusion criteria were: autism spectrum disorder and the use of psychoactive medication. The study was approved by the Leiden University Psychology Research Ethics Committee. All participants gave written informed consent before participation, following the Declaration of Helsinki, and were given monetary compensation for their time and efforts.

### Manipulation

All participants completed two sessions, during one of which they moved in synchrony with the robot, i.e., mirroring movements, while in the other (order counterbalanced), participants and robot moved non-synchronously, i.e., avoiding mirroring or copying the other's movements. For half of the participants, the robot was the initiator of the movements in both sessions, with the participant as the follower. The other half of the participants were the initiator themselves in both sessions, with the robot as the follower. This distinction was made because it was thought that there may be differential effects depending on who initiates the movement. No specific direction was predicted. The design resulted in four scenarios: (I) human initiator, synchronous condition; (II) human initiator, non-synchronous condition; (III) robot initiator, synchronous condition; and (IV) robot initiator, non-synchronous condition.

In scenario (I), the participant was instructed to start making movements with his or her head, left and right at various speeds and to various degrees, which the robot would then copy. This copying was accomplished by use of a motion tracker sewn onto a cap that the participant wore throughout the session, which communicated with the computer that controlled the robot's movement. In scenario (II), the participant was instructed to make any of those movements with his/her head, and was told the robot would avoid copying the movements. In scenario (III), the participant was instructed to copy exactly the head movements that the robot made. In scenario (IV), the participant was instructed to avoid moving his/her head in the exact way the robot was at the time the robot was making the movement. The robot's head movements in these latter three scenarios were randomly generated. It was stressed that in the non-synchronous condition, participants should not make the exact opposite of the robot's movements, as that is really just like copying. Participants could thus freely move to the opposing or same direction, as long as they moved with a different speed and/or to a different angle compared to the robot at any specific point in time. See **Figure 1** for a sketch of the manipulation. Participants either went through scenarios (I) and (II) (those in the human initiator condition), or they went through (III) and (IV) (those in the robot initiator condition), order counterbalanced.

### Measurements

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#### Joint Simon Task

The task was presented on a 21-inch monitor. Each trial started with a fixation cross presented for 500 ms. After this, a blue or a red solid square was presented at either the left or the right of a fixation cross until a response was recorded. Depending on the session's instructions either the robot or the participant had to respond to the stimulus by turning their head to either the left or the right (see **Figure 2**). Color and side were counterbalanced between participants, so where one participant may have received the instructions to respond to red squares with a head turn to the right, another may have received instructions to respond to red squares with a head turn to the left, and yet another to respond to blue squares with a head turn to the left. Participants were always informed that the robot would respond to the other color, and with a head motion to the opposite side. Following the response, the next trial was initiated. Participants wore an InterSense InertiaCube4 motion tracker stitched to a cap on their head, which recorded the response onset (i.e., head turn to the left or right) in relation to the stimulus onset in miliseconds, which was used as RT measurement. Participants first completed a practice block of 8 trials, followed by 4 blocks of 64 trials, which made for 256 recorded trials in total.

### Dictator Game

After the joint Simon Task, participants performed a one-shot Dictator Game with the robot as the opponent. They were presented with a stake, which could be 2, 5, 8, 10, or 20 EUR (randomly drawn each session), and they were asked to decide how much of this stake, if any, they would want to give to the robot. The stakes were varied to control for size, and the outcome measure was the proportion of the stake participants were willing to give to the robot.

#### Questionnaires

At the end of both sessions, participants were asked to fill out three questionnaires: the Individual Differences in Anthropomorphism Questionnaire (IDAQ; Waytz et al., 2010) to assess trait anthropomorphization; the Mind Attribution Scale (MAS, Kozak et al., 2006) to assess state anthropomorphization; and another state anthropomorphization scale taken from Torta et al. (2013), which is based on Epley et al. (2007; henceforth: Torta state questionnaire). The IDAQ trait anthropomorphization questionnaire inquires into general tendency to anthropomorphize, with questions such as "To what extent does a car have free will?". We expected that people with a high, compared to low, tendency to anthropomorphize would show a larger joint Simon effect and offer more money in the Dicator game, hence we wanted to be able to control for its effects. The state anthropomorphization questionnaires asses anthropomorphization toward something recently interacted

#### FIGURE 1 | Continued

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initiator, non-synchronous condition. The participant initiates a large head movement to the left, the robot does not mirror this, but makes a small head movement to the right. (C) Robot initiator, synchronous condition. The robot initiates a large head movement to the right, with which the participant synchronizes with a minimal delay by making a large head movement to the left. (D) Robot initiator, non-synchronous condition. The robot initiates a large head movement to the right, the participant avoids mirroring this by making a small head movement to the right.

with, and were modified to inquire about the robot, TheCorpora's QBo rather than "your opponent" or "this person," i.e., "Overall, do you believe the opponents you have encountered have free will" became "Overall, do you believe QBo has free will" in the Torta state questionnaire; and "This person has complex feelings" became "QBo has complex feelings" in the MAS. All questionnaires were answered on a 7-point Likert scale. The IDAQ is originally rated on a 10-point Likert scale, but to increase consistency between the questionnaires, and because there is evidence that there is not much difference in answers to Likert scales of seven or more options (Cox III, 1980; Weng, 2004; Dawes, 2008), the response options were reduced to seven. Participants completed all questionnaires in both sessions. After the second session, participants answered five open questions that would give us insight into their experience. All questionnaires can be found in **Appendix A**.

### The Robot

TheCorpora's QBo was used, which is a small, semi-humanoid robot of 45.6 cm high, 31.4 cm wide and 29.25 cm deep, with a curved trunk and round head. It has two large wheels on its sides and one small wheel on the front (reminiscent of a vacuum cleaner), no limbs, but it does have a head that can move in all directions (see **Figure 3**). The head has two webcams for eyes, a led-light for a nose, and 20 led-lights for a mouth. QBo is mostly white, with elements of green. In scenarios (II), (III), and (IV), the robot received instructions from the computer controlling it for randomly determined head movements. The participant's motion tracker's data was disregarded in these scenarios. For scenario (I), the computer controlling the robot received input from the motion tracker, which was translated for the robot to mirror the motion the participant made in realtime. During the joint Simon task, at the start of every trial to which the robot was to respond, a message was sent from the experiment computer (E-Prime in Windows) to the robot computer (Linux) to initiate the appropriate response shortly after stimulus onset. There was no variation in the robot's response latency, and there were no pre-programmed erroneous responses, although there was a sporadic miscommunication between the computers leading some response omissions on the robot's end. The number of trials to which the robot failed to respond was not recorded.

### Design and Procedure

The current investigation was a two-session, 2 × 2 mixed design study, with synchrony as within-subjects factor (synchronous vs. non-synchronous) and initiator as between-subjects factor

FIGURE 2 | Joint Simon task setup. In this example of the joint Simon task, the participant has to respond to red stimuli, whereas the robot has to respond to blue stimuli. The participant has to respond with a large head movement to the left; the robot has to respond with a large head movement to the right. (A) Congruent trial for the participant (stimulus on the participant's (Continued)

#### FIGURE 2 | Continued

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side of the screen); no-go trial for the robot. (B) Incongruent trial for the participant (stimulus on the robot's side of the screen); no-go trial for the robot. (C) Congruent trial for the robot (stimulus on robot's side of the screen); no-go trial for the participant. (D) Incongruent trial for the robot (stimulus on the participant's side of the screen); no-go trial for the participant.

(human initiator vs. robot initiator). Participants completed two sessions of 60 min, 1 week apart. Assignment to conditions and group was performed using http://www.randomization.com/. The study was single-blind: the experiment leader was aware of the condition the participant was in. This was deemed unavoidable due to the novelty of the procedure and the necessity of the experimenter to observe the procedure to ensure it was executed correctly. This could only be accomplished by knowing which movements were required according to the current condition.

At the start of each session, the participant and robot practiced both the synchronous and non-synchronous movements for half a minute, so the participant could experience what the alternative was like. Subsequently they performed the synchrony manipulation that belonged to the current session for 4 min. After every block of 64 trials in the joint Simon task, the manipulation was repeated for 2 min to ensure that the effect did not wear off.

Upon arrival in the first session, participants were informed verbally and by means of an information letter about the study they were about to take part in. After giving written informed consent, they were taken into a room with a oneway mirror, where the experiment took place. The experiment leader was stationed behind the mirror and monitored whether the robot and the program were functioning appropriately, and that the synchronization procedure was executed correctly, not explicitly observing the participant's behavior for other purposes. Participants were informed of this fact, so as to minimize any effects of observation. The remaining procedure was the same for both sessions, the only difference being the synchronization type. Participants started with a practice session of the synchronization manipulation as explained above, followed by 4 min of the manipulation. After this, they received instructions for the joint Simon task and went through an 8 trial practice block. Thereafter they started on the joint Simon task, with repeats of the manipulation after every block. After the joint Simon task, they completed the one-shot Dictator Game. Finally, they filled out the trait and state anthropomorphization questionnaires. After the second session they filled out some additional questions about their experience of the experiment, which was followed by debriefing and payment.

### RESULTS

### Data Preparation

Before analysis, the data were prepared and filtered in the following way. The Dictator Game offer was coded as a proportion of the total stake, which was used for further analyses.

Principal component analyses with direct oblimin rotation were performed on the three questionnaires to ascertain the structure of the measures. For the Torta state anthropomorphization questionnaire, the Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy was above the recommended 0.6 with a value of 0.864, and the determinant was satisfactory as well (0.065). The communalities were good, ranging from 0.547–0.781. All items were significantly correlated to one another, but none of the correlations were extremely high, indicating there was no reduncancy in the items (range of correlations: 0.479–0.766). The results indicated a one-factor solution, explaining 68.2% of the variance, for the Torta state anthropomorphization questionnaire. Hence, the ratings of each session were added to form one Torta state anthropomorphization score (one for synchronous, one for non-synchronous).

For the MAS state anthropomorphization questionnaire, the KMO was satisfactory as well with a value of 0.839, as was the determinant (0.015). The communalities were good, ranging from 0.508 to 0.758. Most items were significantly correlated (36 out of 45), with a range of 0.177 to 0.655 in correlation coefficients among the significant correlations. The results indicated a twofactor solution, explaining 60.1% of the variance, contrary to the three-factor solution suggested by the authors (Kozak et al., 2006). Factor loadings are presented in the **Appendix B**. The first factor seemed to be related to ascription of phenomenal consciousness, combining all but one of the items of the emotion and cognition scales that Kozak et al. (2006) identified, whereas

the second seemed to reflect ascription of agency, and included one of the cognition scale items ("QBo has a good memory") in addition to the items that Kozak et al. (2006) found to be in the intentionality scale. Based on these analyses, two MAS scores were calculated for each session: an overall MAS score (for both the synchronous and non-synchronous session), and an agency MAS score (for both the synchronous and non-synchronous session).

Waytz et al. (2010) reported a two-factor solution to best suit the IDAQ items, using both the anthropomorphization and control items in the factor analysis. In our sample, however, a two-factor model explained only 29.6% if the variation. Based on the criterion of Eigenvalue > 1, a 10-factor model emerged, with a low KMO value (0.664), low communalities (ranging from 0.007 to 0.640), and an unsatisfactory determinant (0.0000014), indicating that our sample was not large enough to support this model. It was therefore decided to use only the anthropomorphization items. Based on the criterion of Eigenvalue > 1, a four-factor model emerged explaining 63% of the total variance, one factor representing all items related to technology, one representing all items related to animals, and the items about nature distributed over two factors. A satisfactory KMO value of 0.728 and higher communalities (ranging from 0.295 to 0.829) indicated that this solution was better compared to the model using all items. Waytz et al. (2010) suggested a distinction between anthropomorphization toward animate versus inanimate targets, hence we also ran a two-factor analysis of the data. The animate versus inanimate distinction was, however, not reflected in the two-factor model, nor was any other pattern evident. This model explained only 46.3% of the variance. The KMO was satisfactory (0.728), but the communalities were lower (ranging from 0.179 to 0.744). All things considered, a three-factor model seemed to most sensibly capture the data, one factor representing items related to technology, one representing items related to animals, and one representing items related to nature, in total explaining 56.1% of the variance. KMO was satisfactory (0.728), as was the determinant (0.002), and the communalities were better than for the two-factor model (ranging from 0.293 to 0.744). Having established the structure of the questionnaire, and having assured that all items contributed to the scale, a total IDAQ score was computed for each session.

The session 1 (M = 41.7, SD = 9.6) and session 2 (M = 40.8, SD = 10.4) IDAQ trait scores were combined and averaged, assuming that the average of two moments in time of filling in a questionnaire gives a better indication of general anthropomorphization tendencies than does a single one, and the resulting score was used in further analyses. Indeed, the correlation between the two showed a good test-retest reliability [r(53) = 0.841, p < 0.001]. Please refer to **Table 1** for descriptive statistics for all measures.

The data of the Torta questionnaire, the joint Simon task, and the Dictator Game did not meet the assumption of normally distributed residuals. A log transformation did not sufficiently eliminate this problem. However, given that there is evidence that ANOVAs are robust against violations of this assumption (Blanca et al., 2017a,b), the planned mixed ANOVAs were performed. To determine the mean RTs, we used a recursive outlier detection method with a moving criterion (Selst and Jolicoeur, 1994), which has been shown to be relatively insensitive to sample size and skew compared to non-recursive methods (e.g., 2.5 SD from the mean) and recursive methods without moving criterion. This is appropriate due to the natural skewness of RT data.

To determine whether IDAQ trait anthropomorphization interacted with the independent variables and thus whether it could be used as a covariate for the mixed ANOVAs on RT, Dictator Game offer, and the state anthropomorphization questionnaires, we performed linear regression analyses. We ran separate analyses per outcome variable and per timepoint (synchrony condition), and used IDAQ and the interaction between initiator and IDAQ as predictors. For each of the analyses, the interaction was significant [RTsynchronous: F(3,6036) = 134.345, p < 0.001, R <sup>2</sup> = 0.063; RTnon−synchronous: F(3,6042) = 95.722, p < 0.001, R <sup>2</sup> = 0.045; DGsynchronous: F(3,49) = 144.786, p < 0.001, R <sup>2</sup> = 0.899; DGnon−synchronous: F(3,49) = 172.051, p < 0.001, R <sup>2</sup> = 0.913; MASsynchronous: F(3,49) = 155.929, p < 0.001, R <sup>2</sup> = 0.905; MASnon−synchronous: F(3,49) = 159.343, p < 0.001, R <sup>2</sup> = .907; Tortasynchronous: F(3, 49) = 229.920, p < 0.001, R <sup>2</sup> = 0.934; Tortanon−synchronous: F(3,49) = 191.557, p < 0.001, R <sup>2</sup> = 0.921], meaning the intended covariate was not independent, thus it could not be added without violating the assumption. We therefore ran the mixed ANOVAs without IDAQ trait anthropomorphization, and added Spearman correlation analyses to inquire into the relationship of IDAQ trait anthropomorphization and the dependent variable. The correlations reported below are all Spearman rho's (ρ), since they all involve questionnaire data. Results of all mixed ANOVAs described below are displayed in **Table 2**. All mixed ANOVAs were backed up by Bayesian mixed ANOVAs, the results of which are to be found in **Table 3**.

### Joint Simon Effect

We ran a mixed ANOVA on mean RT, with two withinsubjects factors (synchrony: synchronous vs. non-synchronous; and congruency: congruent vs. incongruent) and one betweensubjects factor (initiator: robot vs. human). There was a significant main effect of congruency [F(1,51) = 30.306, p < 0.001, η 2 <sup>p</sup> = 0.373], where responses on congruent trials (M = 431, SD = 8.2) were faster than on incongruent trials (M = 446, SD = 9.0), thus replicating the joint Simon effect with a robotic partner. Additionally, there was a significant synchrony ∗ initiator interaction [F(1,50) = 7.148, p = 0.01, η 2 <sup>p</sup> = 0.123], where those in the human initiator group had shorter RTs in the non-synchronous (M = 432, SD = 12.6) than in the synchronous condition (M = 439, SD = 11.9), whereas those in the robot initiator group had shorter RTs in the synchronous (M = 435, SD = 12.2) than in the non-synchronous condition (M = 451, SD = 12.8), see **Figure 4**. Follow-up paired t-tests showed that this effect was driven by a significant synchrony effect in the robot initiator group [t(25) = 2.644, p = 0.014]; the difference did not reach significance in the human initiator group [t(26) = 1.212, p = 0.236]. Notably, a number of participants in the robot initiator

#### TABLE 1 | Descriptive statistics.

fpsyg-09-02607 December 26, 2018 Time: 19:0 # 9

#### TABLE 2 | Results for all mixed ANOVAs.

TABLE 3 | Bayes Factors for inclusion of specified terms compared to models without those terms.

group reported difficulty during the non-synchronous session's manipulation. They found it taxing to simultaneously monitor the robot's movements, plan their own movements, and make sure they were not the same. However, as this was spontaneous self-report, and not systematically assessed, we cannot take this into account in analyses.

To provide stronger evidence for the current results, a Bayesian mixed ANOVA with the same factors was conducted. To determine which effects are likely predictors of RT, we looked at the Bayes Factors for addition of each of the terms to a model without that specific term (Jarosz and Wiley, 2014;

Wagenmakers et al., 2018), i.e., Inclusion Bayes Factor based on matched models. The results concur with the regular mixed ANOVA, and provided very strong evidence that congruency (BFinclusion = 2843.892) and the synchrony <sup>∗</sup> initiator interaction (BFinclusion = 111.516) were predictors in explaining the RT data. The correlation between the congruency effect (synchronous and non-synchronous averaged) and IDAQ trait anthropomorphization was not significant [ρ(53) = 0.187, p = 0.181], indicating that there was no relationship between baseline tendency to anthropomorphize and the congruency effect. Similarly, and following up on the synchrony <sup>∗</sup> initiator interaction, there was no significant correlation between the synchrony effect (average synchronous RT – average nonsynchronous RT) and the IDAQ trait anthropomorphization for either the human or robot initiator group [human initiator: ρ(27) = 0.237, p = 0.234; robot initiator: ρ(26) = −0.025, p = 0.904].

We also looked into the correlations between the intention subscale of the MAS state anthropomorphization questionnaire and the joint Simon effect for the synchronous and nonsynchronous sessions, since this subscale seems to give an indication of ascription of agency to the robot ("QBo is capable of doing things on purpose"; "QBo is capable of planned action"; "QBo has goals"; "QBo has a good memory"). There was no significant correlation [synchronous: ρ(53) = 0.121, p = 0.389; non-synchronous: ρ(53) = −0.099, p = 0.480], indicating that there was no relationship between ascription of agency and congruency effect. The same held for the correlations between the subscale of the MAS and the overall RTs, indicating that the interaction reported above was not driven by (explicit) ascription of agency.

Finally, we looked into order effects, since the nature of the initial interaction with the robot may affect the perception of the robot in the later session: it may be sticky, so to speak. To this end, we performed the mixed ANOVA on mean RT as above, with synchrony and congruency as within-subjects factors, and in addition to initiator, also order (synchronousfirst vs. non-synchronous-first) as between-subjects factor. Order was involved in a significant interaction with congruency and synchrony [F(1,49) = 6.240, p = 0.016, η 2 <sup>p</sup> = 0.113], where both order groups showed a numerical decrease in joint Simon effect in the second session, which was rather pronounced in the group that had the non-synchronous session first (session 1: M = 20.33, SD = 26.9; session 2: M = 8.50, SD = 19.3), and rather negligible in the group that had the synchronous session first (session 1: M = 17.54, SD = 23.4; session 2: M = 12.80, SD = 21.5). However, a follow-up paired t-test comparing the session 1 and session 2 joint Simon effects for both of the order groups showed that the difference was non-significant in both cases [synchronous first: t(26) = 1.463, p = 0.156; non-synchronous first: t(25) = 2.048, p = 0.051], so that we are reluctant to interpret the interaction.

### Dictator Game

A mixed ANOVA on Dictator Game offer was performed, with one within-subjects factor (synchrony: synchronous vs. nonsynchronous) and one between-subjects factor (initiator: robot vs. human). There were no significant effects, all ps > 0.067. The correlation between IDAQ and the difference between the DG offers (synchronous – non-synchronous) was not significant [ρ(53) = −0.103, p = 0.462], indicating that there was no relationship between tendency to anthropomorphize and altruism toward the robot. To confirm that the offer did not differ as a result of our manipulation, we conducted a Bayesian mixed ANOVA. The results indicate weak support for the synchrony <sup>∗</sup> initiator interaction (BFinclusion = 1.187).

As with the joint Simon effect, we looked at the correlations between the intention subscale of the MAS state anthropomorphization questionnaire and the Dictator Game offer for the synchronous and non-synchronous sessions. There was no significant correlation [synchronous: ρ(53) = 0.265, p = 0.055; non-synchronous: ρ(53) = 0.223, p = 0.109], indicating that there was no relationship between ascription of agency and proportion offered in the Dictator Game.

The Dictator Game offer thus did not vary as a function of our manipulation. It did, however, correlate positively with anthropomorphization of the robot: the offer on the synchronous session correlated positively with both state anthropomorphization questionnaires [MAS: ρ(53) = 0.361, p = 0.008; Torta: ρ(53) = 0.423, p = 0.002], and the offer on the non-synchronous session correlated positively with the Torta state anthropomorphization questionnaire [ρ(53) = 0.336, p = 0.014]. There were no correlations with the MAS intention subscale, suggesting that this relationship did not depend on perceived autonomy.

Finally, we looked into order effects by running the aforementioned mixed ANOVA with synchrony as withinsubjects factor, and initiator and order as between-subjects factors. Order was not a significant contributor, indicating that the Dictator Game offer was not affected by the order of the manipulation.

### Trait Anthropomorphization

fpsyg-09-02607 December 26, 2018 Time: 19:0 # 11

The IDAQ trait anthropomorphization questionnaire showed good internal consistency (αsynchronous = 0.724; αnon−synchronous = 0.760) in addition to the aforementioned good test-retest reliability.

An independent samples t-test was run to compare the two initiator groups on IDAQ trait anthropomorphization, to make sure there were no baseline differences between the groups. The result was non-significant [Mhuman = 41.0, SDhuman = 11.1; Mrobot = 41.5, SDrobot = 8.0; t(51) = 0.180, p = 0.858], meaning there were indeed no baseline differences in terms of tendency to anthropomorphize between the two initiator groups.

### State Anthropomorphization

The Torta state anthropomorphization questionnaire showed high internal consistency (αsynchronous = 0.787; αnon−synchronous = 0.892). A mixed ANOVA on the Torta state anthropomorphization questionnaire was performed, with one within-subjects factor (synchrony: synchronous vs. nonsynchronous) and one between-subjects factor (initiator: robot vs. human). There were no significant effects, meaning that state anthropomorphization as measured by the Torta questionnaire did not differ as a result of our manipulation.

To confirm that Torta state anthropomorphization did not vary as a function of our manipulation, we ran a Bayesian mixed ANOVA with the same factors as above. The inclusion Bayes Factors were very low (all below 0.508), indicating that the null model was the best explanation of the data, and confirming that this measure did not vary as a function of our manipulation.

Here too we looked into order effects by running the above mixed ANOVA with synchrony as within-subjects factor, and initiator and order as between-subjects factors. The absence of significant effects of order indicated that the order of the manipulation did not affect anthropomorphization of the robot as measured by the Torta state anthropomorphization questionnaire.

The MAS state anthropomorphization questionnaire showed high internal consistency (αsynchronous = 0.801; αnon−synchronous = 0.824). A mixed ANOVA on the MAS state anthropomorphization questionnaire was performed, with one within-subjects factor (synchrony: synchronous vs. nonsynchronous) and one between-subjects factor (initiator: robot vs. human). This too yielded no significant effects, indicating that state anthropomorphization as measured by the MAS did not differ as a result of our manipulation.

To confirm that the MAS state anthropomorphization questionnaire did not vary as a function of our manipulation, we ran a Bayesian mixed ANOVA with the same factors as above. The inclusion Bayes Factors were very low (all below 0.594) in this case as well, indicating that the null model was the best explanation of the data. Neither of the state anthropomorphization questionnaires thus showed an effect of the manipulation.

Order effects were examined by running a mixed ANOVA on the MAS state anthropomorphization questionnaire scores with synchrony as within-subjects factor, and initiator and order as between-subjects factors. There was a significant synchrony <sup>∗</sup> order interaction [F(1,49) = 16.967, p < 0.001, η 2 <sup>p</sup> = 0.257]. For both order groups, the robot was numerically anthropomorphized less in the second session. This seemed to be more pronounced in the non-synchronous-first group (session 1: M = 28.73, SD = 6.2; session 2: M = 24.50, SD = 7.0) compared to the synchronous-first group (session 1: M = 29.70, SD: 10.2; session 2: 28.11, SD = 11.6). A follow-up t-test indicated that this was significant in the non-synchronous-first group [t(25) = 3.784, p = 0.001], while it failed to reach significance in the synchronousfirst group [t(26) = 1.736, p = 0.094]. Hence, while the previous questionnaire was not affected by the order of the manipulation, the MAS state anthropomorphization questionnaire was. This may be explained by a difference in the two questionnaires; while they have largely overlapping items, the MAS state anthropomorphization questionnaire has some additional items that are not captured by the Torta state anthropomorphization questionnaire ("QBo is capable of planned actions"; "QBo has a good memory," "QBo can engage in a great deal of thought," and "QBo has goals"), which might be interpreted as related to rational cognitive function.

A correlation analysis was performed with IDAQ trait anthropomorphization and each of the state anthropomorphization scores (synchronous and nonsynchronous scores for each questionnaire separately). The IDAQ was positively correlated to each [Tortasynchronous: ρ(53) = 0.595, p < 0.001; Tortanon−synchronous: ρ(53) = 0.584, p < 0.001; MASsynchronous: ρ(53) = 0.373, p = 0.006; MASnon−synchronous: ρ(53) = 0.392, p = 0.004], meaning that the higher the tendency to anthropomorphize, the higher the actual anthropomorphization of the robot in the experiment.

### DISCUSSION

This study investigated whether anthropomorphization of a robot could be influenced by moving with it either synchronously or non-synchronously, and whether this would be affected by who initiated the movements. We pitted two hypotheses against each other: the feature-overlap hypothesis and the autonomy hypothesis. The former predicted that the robot would be anthropomorphized more following synchronous movement while the latter predicted the robot would be anthropomorphized more following unpredictable movement, i.e., non-synchronous when the human initiated the movements, or either synchrony condition when the robot initiated the movements.

In the joint Simon task, we replicated the joint Simon effect with a robotic co-actor, concurrent with previous studies (Stenzel et al., 2012; Stenzel et al., 2013; Wen and Hsieh, 2015; Bunlon et al., 2018). Contrary to expectations, the size of the joint Simon effect was not affected by our manipulation. The manipulation did, however, affect RTs overall: for the group in which the human initiated the movements, the RTs were larger when the robot synchronized with the human than when

the robot did not synchronize with the human. Conversely, for the group in which the robot initiated the movements, the RTs were larger when the human was instructed not to synchronize with the robot compared to when the human was told to synchronize with it. This pattern of results fits neither of the advanced hypotheses. The autonomy hypothesis would have predicted the opposite pattern in the group in which the human initiated the movements, and additionally there should not have been a difference in the group in which the robot initiated the movements—which there is. Additionally, there was no relationship between the questionnaire items assessing ascription of agency and the joint Simon effect, nor with overall RT, which leaves the autonomy hypothesis with even less support.

The feature overlap hypothesis would have predicted the increase in RT in the synchronous condition when the human initiated the movements, but would have also predicted to find this in the group in which the robot initiated the movements. It thus seems that neither hypothesis is sufficient to explain the results. Perhaps they can be explained by a difference in difficulty between the manipulations: In the human initiator condition, participants could safely ignore the behavior of the robot, which also did not overlap with their own action or action planning. In the robot initiator condition, however, they had to take the behavior of the robot into account, and it makes sense to assume that this required less cognitive effort in the synchrony as compared to the non-synchronous condition, where the behavior had to be mentally "inverted" to specify one's own action plan. This may have made the non-synchronous condition cognitively incompatible, which is known to impair action planning and response selection (Proctor and Vu, 2006). The potential asymmetry in the manipulation in terms of difficulty is therefore an unforeseen shortcoming of the current design.

The Dictator Game offer seemed entirely unaffected by our manipulation. Like the joint Simon task, there was no relationship with ascription of agency either. There was, however, a correlation between anthropomorphization of the robot and the size of the offer: the more the participant anthropomorphized the robot, the larger the proportion of the stake the participant offered. While this is consistent with previous findings suggesting a connection between trust and anthropomorphization (Hancock et al., 2011), it does not suggest a moderating role of synchrony. It may shed some light on inconsistent findings reported by Müller et al. (2014). After watching either a fragment of Pinocchio or a Dutch romantic comedy in one study, and after watching a fragment of Pinocchio or a documentary in which a wooden puppet is made in another study, participants were asked to choose a seat in a row of chairs with a wooden doll on the one end and a backpack (implying a human) on the other end, and were then asked to distribute seven lottery tickets worth €5 each between the human and a wooden puppet. In the second study, participants then also filled in a few questions about their perception of Pinocchio. In both studies, they found that participants sat closer to the wooden doll following the Pinocchio fragment compared to the other fragment. Additionally, they found an effect of movie fragment upon distribution of money in the former (with seating distance as covariate), but not in the latter study. Finally, they report negative correlations between seating distance and ascription of intentionality and will to the wooden doll, indicating that the more the participant perceived the doll as having an own will and intentionality, the closer they decided to sit to it.

To link these findings to the current study, two things are to be noted. (i) The studies differ in that in the former, only those in the Pinocchio fragment condition are exposed to a wooden doll prior to selecting the chairs, whereas in the latter study, both groups of participants are exposed to a wooden doll. (ii) The negative correlations reported pertain to the whole sample, thus not only to those in the condition in which the wooden doll might be expected to be perceived more human-like (i.e., the Pinocchio fragment). Linking our findings to (i), in our study, all participants were exposed to the robot in both sessions, rendering our design analogous to the second experiment. One explanation of our nullfindings based on synchronization condition thus is that exposure to the robot is all that determines altruism toward it. Since exposure is equal, no difference is to be expected. Linking our findings to (ii), the Müller et al. (2014) study leaves open the possibility that anthropomorphization of the wooden doll affects the amount of money allocated to it: they report that higher ascription of agency relates to closer seating next to the doll; and since closer seating next to the doll is taken as covariate in analyzing the allocation of money, possible variation due to anthropomorphization of the doll is taken out. Hence, their findings may be taken together with ours to suggest that mere exposure as well as baseline tendency to anthropomorphize affect altruism toward inanimate objects, so that differences in altruism can be found when comparing differential exposure to and/or differences in levels of anthropomorphization of the inanimate object.

Our manipulation had no effect on explicit anthropomorphization of the robot, as indicated by a lack of difference on the state anthropomorphization measures (Kozak et al., 2006; Torta et al., 2013). We did, however, find that a higher tendency to anthropomorphize (as measured by the IDAQ, Waytz et al., 2010) translated into more actual anthropomorphization of the robot, lending credibility to both measures. Additionally, we have found all questionnaires to have good internal consistency, and have found that the trait anthropomorphization questionnaire showed good test-retest reliability.

Interestingly, there was some indication that the order in which the synchronization manipulations were experienced affected anthropomorphization of the robot. Although this was not the case for all measures, the joint Simon effect and the MAS state anthropomorphization questionnaires showed an order effect that followed a similar pattern: anthropomorphization was reduced in the second as compared to the first session, and this was particularly so for the group that had the non-synchronous session first. We may draw two tentative conclusions from this: that more exposure to the robot does not lead to more anthropomorphization and that having had a non-synchronous interaction before a synchronous interaction leads to a stronger reduction of anthropomorphization in the latter.

Where do the results leave the two possible hypotheses? Unfortunately, it seems that either our manipulation was not ideal for testing the hypotheses, or that neither of the mechanisms has an effect: most measures showed similar results across conditions. There was an effect of our manipulation on RTs in the joint Simon task, but this may have been due to a difference in difficulty of the manipulation. The agency-related items of one of the questionnaires did not relate to this effect, leaving that hypothesis with less support—at least at the level of selfreport. However, since we have not used a similar measure of self-reported self-other overlap—a shortcoming of the current design—we cannot make any similar claims about the featureoverlap hypothesis. Other possible reasons for the lack of an effect include sample size, the distinct non-human appearance of the robot, and more interestingly: the motion patterns of the robot. The movement of the robot, though superficially mimicking human motion, has a monotonic speed, whereas human (and other biological) motion does not. On the one hand, previous findings do not suggest that monotonic speed as such stands in the way of social interactions with robots: for instance, van den Brule et al. (2014) found no impact of motion style on the trustworthiness of robotic agents. On the other hand, however, our synchrony manipulation might have increased the salience of the non-biological nature of the robotic movements, which in turn might have emphasized the perceived dissimilarity between the human and the robot. Future studies might overcome this possible obstacle by using humanoid robots programmed to move in a more biologically plausible way. For the time being, however, our findings do not

### REFERENCES

point to a strong role of behavioral synchrony in human-robot interaction.

### DATA AVAILABILITY STATEMENT

Datasets are available on request.

### AUTHOR CONTRIBUTIONS

All authors developed the study concept, contributed to the study design, and provided critical revisions to and approved the final version of the manuscript. SH programmed the tasks, collected and analyzed the data, and drafted the manuscript. RdK programmed the robot and motion tracker.

### FUNDING

This work was supported by an Advanced Grant of the European Research Council (ERC-2015-AdG-694722) to BH.

### SUPPLEMENTARY MATERIAL

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpsyg. 2018.02607/full#supplementary-material

partners: co-representation of robotic actions. J. Exp. Psychol. Hum. Percept. Perform. 38, 1073–1077. doi: 10.1037/a0029493

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2019 Heijnen, de Kleijn and Hommel. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Development of Infant Reaching Strategies to Tactile Targets on the Face

Lisa K. Chinn<sup>1</sup> , Claire F. Noonan<sup>1</sup> , Matej Hoffmann<sup>2</sup> and Jeffrey J. Lockman<sup>1</sup> \*

<sup>1</sup> Department of Psychology, Tulane University, New Orleans, LA, United States, <sup>2</sup> Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czechia

Infant development of reaching to tactile targets on the skin has been studied little, despite its daily use during adaptive behaviors such as removing foreign stimuli or scratching an itch. We longitudinally examined the development of infant reaching strategies (from just under 2 to 11 months) approximately every other week with a vibrotactile stimulus applied to eight different locations on the face (left/right/center temple, left/right ear, left/right mouth corners, and chin). Successful reaching for the stimulus uses tactile input and proprioception to localize the target and move the hand to it. We studied the developmental progression of reaching and grasping strategies. As infants became older the likelihood of using the hand to reach to the target – versus touching the target with another body part or surface such as the upper arm or chair – increased. For trials where infants reached to the target with the hand, infants also refined their hand postures with age. As infants became older, they made fewer contacts with a closed fist or the dorsal part of the hand and more touches/grasps with the fingers or palm. Results suggest that during the first year infants become able to act more precisely on tactile targets on the face.

Keywords: reaching, tactile localization, prehension, motor development, multisensory coordination, hand-tomouth coordination

### INTRODUCTION

The ability to act on one's own body by reaching to specific locations on the body is critical for many tasks of daily living. Although most individuals reach to body locations automatically and with apparent ease, this act involves a coordinated set of perceptual and motor skills. Reaching to a stimulus on the body uses perceptual inputs including touch, proprioception, and sometimes vision to localize a stimulus and to guide a motor action to that location (Longo et al., 2010; Heed et al., 2015). Even though reaching to the body is performed habitually, most reaching studies to date have focused on extending the hand to objects in external peripersonal space. In contrast, little research has addressed reaching to targets on the body or how this ability develops. Here, we longitudinally examine the motor strategies that infants use across the first year as they reach to and grasp a vibrating target placed at different locations on the face.

### Reaching to External Space Versus the Body

Previous work on reaching during infancy has mainly involved the presentation of objects in peripersonal space, external to the body (e.g., Morange and Bloch, 1996). For example, infants from

#### Edited by:

Claudia Gianelli, Universität Potsdam, Germany

#### Reviewed by:

Verónica C. Ramenzoni, Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Argentina Elias Manjarrez, Benemérita Universidad Autónoma de Puebla, Mexico

#### \*Correspondence:

Jeffrey J. Lockman<EMAIL_ADDRESS>
#### Specialty section:

This article was submitted to Cognition, a section of the journal Frontiers in Psychology

Received: 31 August 2018 Accepted: 04 January 2019 Published: 21 January 2019

#### Citation:

Chinn LK, Noonan CF, Hoffmann M and Lockman JJ (2019) Development of Infant Reaching Strategies to Tactile Targets on the Face. Front. Psychol. 10:9. doi: 10.3389/fpsyg.2019.00009

9 to 20 weeks can first reach to objects placed in front of the ipsilateral shoulder (100% at 9 weeks), then to the midline (33% at 9 weeks and 93% at 17 weeks), and then to contralateral objects (0% at 9 weeks to 71% at 17 weeks; Provine and Westerman, 1979). By 18–20 weeks all infants studied by Provine and Westerman (1979) made contralateral reaches. Studies have also shown that reaching to an object in external space becomes faster, more efficient, and more direct during the first year (Thelen et al., 1993; Berthier and Keen, 2006; Rönnqvist and Domellöf, 2006; D'Souza et al., 2017; Corbetta et al., 2018). Furthermore, reaching is not limited to stimuli that are perceived visually. Infants are also capable of reaching to auditory targets in external space (Clifton et al., 1991).

In contrast to reaching to targets in external space, much less is known about the development of reaching to tactile targets on the body. How is reaching to tactile stimulation on the skin accomplished? Neural research has shown that somatosensory (tactile and proprioceptive) stimulation leads to activations in the somatosensory cortex of the brain, which has been referred to as the "sensory homunculus" (Penfield and Boldrey, 1937). Infants evidence at least a rudimentary somatotopy in these brain regions. By 2 months hand, foot, and lip stimulation leads to different locations of peak somatosensory-evoked potentials recorded with EEG (Saby et al., 2015; Meltzoff et al., 2018). However, such activation per se does not mean that the infant localizes the stimulus in the sense that she can reach to it. For that, the stimulation needs to be associated with other sensorimotor laws or contingencies (O'Regan, 2011; Hoffmann et al., 2017).

Reaching to tactile stimuli may initially also be reflexive and controlled in part by spinal or subcortical circuitry. A wiping/scratch reflex has been demonstrated in frogs (Fukson et al., 1980; Berkinblit et al., 1986) and cats (Tapia et al., 2013). Although the existence of such a reflex is debated in humans (MacKay-Lyons, 2002), we cannot exclude the possibility that early reaches to the face – the mouth region in particular – may be brought about by similar mechanisms. However, even if this were the case early in infancy, we would expect these behaviors to become progressively more complex and voluntary over time.

### Processes of Tactile Localization

To localize a tactile stimulus placed on the skin, somatosensory information is "remapped" to an external reference frame (such as body-centered or gaze-centered) in order for a person to reach to the target (e.g., Medina and Coslett, 2010; Heed et al., 2015). The distinctiveness of these skin-based and external representations of the stimulus location can be demonstrated in crossed-limb paradigms where, for instance, the anatomically left hand is located in the right side of external space. Such conflicts are often examined using the temporal order judgment task (Heed and Azañón, 2014) in which adults are slower at identifying the order of touches when the hands are crossed versus uncrossed. Furthermore, in the first half year, a developmental progression occurs in the response to tactile stimuli in crossed feet postures, suggesting that by 6 months infants are beginning to code the position of the crossed feet with respect to external space (Begum Ali et al., 2015). Neural responses associated with limb mapping in external space continue to develop between 6 and 10 months (Rigato et al., 2014).

The previous lines of research associated with tactile perception and body location have mainly focused on behavioral or neural responses that do not involve direct reaching to tactile targets on the body surface. Less is known, however, about the functional ability to reach to target locations on the body and how this sensorimotor skill becomes refined throughout infancy. One sensorimotor ability that may provide a foundation for reaching to some tactile targets, particularly on the face, is the hand-tomouth transport system (Lew and Butterworth, 1997). Research suggests that hand-mouth coordination is already evident to some degree in the prenatal period, but becomes more skilled and direct in the months immediately following birth (Rochat et al., 1988; Rochat, 1989; Lew and Butterworth, 1997).

### Reaching and Grasping

Being able to transport the hand to the mouth or more generally, contact a stimulus on the face, is only one element of the reaching act. Successful reaching to a stimulus, whether it is located on the body or in external space, typically involves the coordination of at least two different action systems: reaching and grasping (Jeannerod, 1996). Effective reaching requires individuals not only to extend their hands to the location of a stimulus, but open and orient the hand to prepare to grasp the stimulus. Developmentally, research indicates that the reaching system comes online before the grasping system (Piaget, 1952; Bruner, 1973), reflecting a proximodistal sequence in the development of prehension (Lockman and Ashmead, 1983). In particular, before 4 months, infants develop the ability to extend their hand to the location of an object (Piaget, 1952; Bruner and Koslowski, 1972), but during this period the hand is often fisted when it contacts the object. By 4 months, however, infants begin to open the hand in advance of contacting the object. Likewise, with regard to self-touch, closed hand contacts prevail in the first 2 or 3 months, and open hand contacts begin to increase in frequency between 3 and 5 months (Thomas et al., 2015). Nevertheless, it is important to note that with respect to the goal of the reaching act, research on self-touch where infants spontaneously contact a part of their body with their hand might not be directly comparable to research on reaching, where infants are presented a discrete stimulus to reach to in external space.

### The Current Study

In the present work, we consider the problem of reaching to discrete tactile stimuli on the face. We conducted a longitudinal study during the first year in which we placed vibrating targets, one at a time, at different locations on the infant's face. Because the targets were not accessible to vision, infants had to execute reaches on the basis of tactile and associated proprioceptive information.

In this work, we addressed two main issues. One centered on the different effector systems available to infants for reaching to stimuli on the body and whether infants privilege different effector systems to contact different areas of the face. Specifically, we asked when does the manual effector system become the dominant mode for contacting stimuli on the face. In principle,

other movable parts of the body can be used to contact face stimuli. The tongue has the potential to touch external stimuli located near the mouth. Both the head and shoulder can move to establish contact with stimuli on the lower side of the face or the ears. The manual effector system, however, might embody a more effective means for reaching to face stimuli because of the extent to which the arms can move and the precision afforded by fingers that can grasp. To explore these ideas, we asked to what extent infants recruit other parts of the body (e.g., tongue, head, and shoulders) to contact stimuli on the face. If infants, especially at younger ages, touch targets on the face with effectors other than the arms and hands, this would suggest an early awareness at some level of the affordances of the body for reaching to other parts of the body.

The second set of issues that we focused on centered on the manual effector system alone. Specifically, we asked how does grasping become adapted for reaching to targets on the face. We describe how infants' hand postures when contacting tactile targets and grips on the targets on the face vary with age. We expected that closed fist contacts would decrease with age, while open handed contacts and grips would increase with age. This prediction would be consistent with the idea that infants' reaching to the face is becoming more skilled and that infants were attempting to grasp these stimuli, which were not a permanent part of the body. Additionally, we were interested in the possibility that different locations on the face might call forth different hand postures depending upon ease or comfort. Modulation of grip strategies or hand postures based on the location of the target might suggest that infants adjust hand posture according to the demands associated with carrying out the reach.

### MATERIALS AND METHODS

### Participants

A total of 24 infants (10 female; starting age just under 2 to 6 months) were recruited from local daycares, the psychology department of the University, and family-oriented events in the greater New Orleans area. The racial/ethnic backgrounds of participants were Caucasian (N = 16), Black/African American (N = 3), more than one race (N = 3), American Indian (N = 1), and Asian (N = 1). Three infants did not complete every study visit (one family moved, one had schedule conflicts arise, one dropped out without providing a reason). These infants are included in the data analyses, which were able to accommodate missing data.

### Materials

During the task, gently vibrating targets were fixed to eight locations on infants' faces/heads one at a time using double-sided skin-safe tape. The target was a disk shape approximately 1.25 cm in diameter, 0.75 cm in height, and 3.5 grams in weight. Inside the target was a flat coin 3-volt DC 70 mA 12000 RPM micro motor that provided vibration similar to vibrating teething rings or mobile phones. The stimuli were coated with black liquid tape to provide a soft and smooth texture. Each testing session was recorded with two mounted video cameras. The experimenter also recorded target location and target contact success on paper, but coding of data analyzed here was done entirely from the videos.

### Procedure and Design

Parents of all subjects provided written informed consent, in which they consented to participating in the study and having the sessions videotaped. They could also choose whether or not to allow images/videos from testing to be used in presentations and written products. The research was approved by the Tulane University Institutional Review Board (reference number 153903) and was consistent with the Declaration of Helsinki. Families were invited to come in for the study every second week until the infant was able to reach to all eight target locations in one visit. Adherence to a schedule with two visits per month was not always possible due to parent schedules or illness (average time between visits = 21.7 days; see **Figure 1**). The target locations were the left/right corner of the mouth, below the left/right earlobe, on the center of the chin, on the center temple (i.e., forehead), and on the left/right temples (see **Figure 2**). The order of trials was randomized. When the experimenter applied the lateralized targets, the opposite side of the infant's face was touched simultaneously at the corresponding location so as not to draw attention to one side of the face over another. For the midline targets, there was no opposite side so the target was placed at midline with no other touch to the face. During each visit, each target was left on the infant's face until the infant removed it or for approximately 30 s, whichever came first.

Videos of each testing session were coded for factors of target location (chin, left/right mouth, below the left/right ear, and left/right/center temple), whether or not the infants successfully contacted each target (yes, no), how the target was first contacted (left/right hand, left/right arm, head-to-torso, tongue, and head-to-chair), and hand posture when they grasped or contacted the target (closed fist, dorsal hand, palm, finger

touch, pincer grasp, and four-finger opposing thumb grasp). When first contact was coded as "head-to-chair," infants turned the head toward the chair and rubbed the target against the chair. Contacts were not coded as "head-to-chair" if the infant was moving the head in a seemingly random fashion both before and after target placement and then appeared to accidentally graze the chair with the target. In the hand posture coding, the dorsal hand code included only the area on the back of the hand between the wrist and the knuckles; contact with the back of the fingers was coded as finger touch. The palm code included the area of the palm between the wrist and the base of the fingers. Grasps were coded as pincer grips when the index finger and thumb grasped the target.

Here we focus on the development of manual strategies used for successful reaches. In order to accommodate binary outcome variables (e.g., whether the target was first contacted with the hand or not), missing data, and data clustered within each subject, generalized estimating equations (GEEs) were used (See Hardin and Hilbe, 2012). A binomial distribution, a logit link function, and an exchangeable correlation matrix were used. GEEs allow significance testing, while also providing predicted average responses. For example, when a binomial GEE reveals a significant age effect on performance for a measure with a 0/1 scale, it also produces a curve showing predicted average probability of scoring a 1 on the 0/1 scale as age increases.

### RESULTS

### Preliminary Analyses

A primary coder coded 100 percent of the data, and a secondary coder coded an overlapping 20 percent. Inter-rater reliability was achieved for all categorical variables analyzed (mean Cohen's k = 0.87, range = 0.71–1.00). Preliminary analyses found no significant effect of sex or laterality (left versus right target placement and left versus right hand use) on reaching success, so these variables were excluded from further analyses. Further,

the age that an infant started the study was not significantly correlated with the age that the infant graduated from the study, indicating that enrolling at a younger age did not result in learning the task earlier.

### How Do Infants Contact Targets?

The first set of analyses looked at whether infants chose to use the hand (versus another body part or object) to make contact with the target. Specifically, the first GEE analysis examined the effects of age and target location and an Age x Target Location interaction on hand versus non-hand contact with the target. For 779 out of 1763 total trials (44.19%) infants successfully contacted the target, either using the hand or something else, such as the arm, head-to-torso, tongue, or head-to-chair. Out of 770 of trials where the target contact strategy was visible in our recordings, 599 (77.79%) of these initial contacts were made with the hand (Nine trials that were recorded as successful reaches by the experimenter on paper had a video recording error and are excluded here). As infants became older the likelihood of first contacting the targets directly with the hand versus some other body part or external surface increased significantly (Wald x<sup>2</sup> <sup>1</sup> = 41.46, p < 0.001; **Figure 3**). Further, the GEEpredicted likelihood of hand contact varied by location (Wald x 2 <sup>4</sup> = 10.17, p < 0.05; **Figure 4**). GEE predicted the highest percentage of hand contact for the center temple (92%), followed by the mouth (86%), chin (82%), lateral temples (66%), and ears (63%). The Age x Target Location interaction was not statistically significant.

Although the numbers of each type of non-hand contact were too low to analyze statistically (**Figure 4**), the non-hand strategies used seemed to vary based on the location of the target on the

body. Most trials where the head moved to rub the target on the chair involved trials in which the target was placed at the ears or lateral temples and were thus closest to the chair. The head and torso (shoulders or upper chest) came together most often for targets that were placed at the chin or ears – the locations most accessible to the torso. Finally, only mouth and chin targets could be contacted by the tongue, given anatomical constraints of the body.

### Hand Posture and Grips

Next we looked at how hand posture changed with age for trials where infants achieved target contact with the hand. Specifically, we considered the effects of age and target location on whether or not the hand was fisted when it contacted the target, whether the dorsal part of the hand contacted the target, whether the palm/fingers contacted the target, and whether infants used the finger(s) and opposing thumb to grasp the target.

### Fisted Target Contacts

The first analysis looked at whether infants became less likely to use a closed hand posture, specifically a closed fist, to contact targets as they became older. Out of 599 trials where initial target contact was made with the hand, 96 contacts (16%) were made with a closed fist. A GEE testing the effects of age, target location, and the Age x Target location interaction revealed that infants became significantly less likely to contact targets with a closed fist as they became older (Wald x<sup>2</sup> <sup>1</sup> = 28.69, p < 0.001; **Figure 5**). The Age x Target location interaction was statistically significant (Wald x<sup>2</sup> <sup>4</sup> = 10.26, p < 0.05). However, this interaction was difficult to interpret because it largely stemmed from the center temple location, where there were only six fisted target contacts.

### Dorsal Target Contacts

The next analysis looked at whether infants became less likely to use the dorsum of the hand to contact targets as they became older, suggesting that infants were attempting instead to touch or grasp the target with the fingers and/or palm. Out of 599 trials

FIGURE 5 | The effect of age on fisted versus non-fisted contact with the targets. The solid line represents the GEE-predicted probability of fisted hand contact with the targets, and the open circles represent the raw data (fisted

where the hand contacted the target, 138 contacts (23%) were with the dorsal part of the hand. A main effect of age showed significantly less dorsal contact as infants became older (Wald x 2 <sup>1</sup> = 15.03, p < 0.001). This main effect, however, was qualified by a significant Age x Target Location interaction on dorsal hand contact (Wald x<sup>2</sup> <sup>4</sup> = 10.08, p < 0.05; **Figure 6**). Follow up tests showed that dorsal hand contact became significantly less likely at the lateral temples, center temple, ears, and chin (ps < 0.01–0.001) as infants became older. For the mouth, age did not significantly affect whether infants used the dorsal part of the hand to contact the target, suggesting that infants may have been attempting another goal with targets located at the mouth.

### Palm and Fingers

hand contact or non-fisted hand contact).

In this section, we look at whether palm and finger (ventral or dorsal) contacts versus other forms of contact increase with age. Out of 599 trials where initial target contact was made with the hand 365 (60.93%) contacts used the palm or fingers, and 234 (39.07%) did not use the palm or fingers. As infants became older they were significantly more likely to make contact with the fingers or palm (Wald x<sup>2</sup> <sup>1</sup> = 40.44, p < 0.001; **Figure 7**). The main effect of target location and the Age x Target Location interaction were not statistically significant.

### Opposing Thumb Grasps

Next, we looked at whether infants became more likely with age to grasp the target with the opposing thumb and finger(s). Only 63/599 trials (10.52%) involved an opposing thumb grasp, indicating that this strategy was not particularly common in the age range under study. We divided opposing thumb grasps into two different types that we saw infants in this study use - pincer grips (37 trials) and grips with all four fingers opposing the thumb

non-palmar/finger contact with the targets. The solid line represents the GEE-predicted probability of palmar or finger hand contact with the targets, and the open circles represent the raw data (palmar/finger target contact or non-palmar/finger target contact).

(26 trials). Because there were a limited number of grasp trials, we could only analyze the effect of age in GEE and not the effects of target location and the Age x Target Location interaction. A GEE testing the effect of age on whether the infants used a pincer grip to contact the target showed that pincer grips became more common with age (Wald x<sup>2</sup> <sup>1</sup> = 24.85, p < 0.001). Four finger grips also increased with age (Wald x<sup>2</sup> <sup>1</sup> = 7.52, p < 0.01).

### DISCUSSION

The ability to reach to a source of stimulation on the face is highly adaptive but little studied. Infants reach to stimulation on the face to scratch an itch, but also to remove foreign, potentially dangerous stimuli. Although recent work has shown that the ability to contact vibrotactile targets on the body improves during the first and second years of life (Chinn et al., 2017), this previous work focused on whether infants were able to reach to targets, without examining specific motor strategies through which they do so. Little is known about the motor strategies that infants use to reach to the face. To address this question, we conducted a longitudinal study over the first year in which vibrotactile targets were placed one at a time at different locations on the face. Because the locations of these targets were not accessible to vision, infants had to rely on tactile and proprioceptive information to localize and reach to these targets.

In this study, we found that when a vibrotactile target is applied to the face, infants are more likely to reach to the target with the hand rather than using other effectors or strategies (e.g., rubbing the target on the chair) and that hand versus non-hand use increases with age. They also become more likely to use the palmar surface or fingers of the hand than the dorsum, and they grasp the targets more as they become older. We consider these findings in more detail below.

### Motor Strategies for Target Contact

A primary goal of the current study was to look at the motor strategies that infants used to contact tactile targets on the face. Most studies on reaching to objects in external space focus on the arm and hand. The predominance of the hand and arm in the reaching literature makes sense given that other parts of the body are not configured to grasp targets as well as the hand. However, it is possible to use other body parts or external surfaces to contact a target location on the body.

Here we addressed whether infants contact stimuli on the face with external objects or body parts other than the hand and if these strategies change with age. We found that the hand was used for most reaches throughout the age range under study, but nevertheless and as hypothesized, its use relative to nonhand contact options increased with age. This result suggests that across the first year infants are becoming more likely to reach with the effector best at grasping.

Although the percentages of each type of non-hand contact were low (**Figure 4**), the non-hand strategies used seemed to vary based on the location of the target and the anatomy of the body. Most trials where infants turned their heads to rub the target on the chair were trials in which the target was placed to the side of the face (ears or lateral temples) and was, therefore, closest to the chair. The head and torso (shoulders/upper chest) came together most often for targets that were placed at the chin or ears –

the locations most accessible to the torso. Only mouth and chin targets were contacted by the tongue, which makes sense given anatomical constraints. For tongue contacts of the mouth and chin targets, however, we cannot entirely rule out the possibility that the rooting reflex, although very weak during the age range under study, contributed to this response.

A possible future research direction would be to study localization strategies in infants or children with disorders affecting sensory processing and/or motor skills. For example, children with autism spectrum disorder are sometimes less responsive to tactile stimulation versus neurotypical controls (Tomchek and Dunn, 2007). It is possible that differences in performance on this task for children with known sensory or motor deficits could help our understanding of the processes involved in reaching to vibrotactile targets on the face.

### Reaching to the Body and Arm/Hand Movements

Another main goal of the current study was to look at hand postures and grasping strategies used for target contacts made with the hand. We found that – as predicted – across the first year, infants became less likely to contact targets with a closed fist and with the dorsal part of the hand. Conversely, they became more likely to use the palm or fingers to contact targets, versus the dorsal hand or a closed fist. They also became more likely to grasp the targets with the finger(s) and opposing thumb with age, although this strategy did not predominate by the end of the age range under study. It is known that the pincer grasp for reaching to external objects is beginning to emerge near the end of the first year, consistent with the results of this study on reaching to targets on the face.

More generally, the developmental patterns we saw for hand postures during body reaches are similar to developmental changes in hand posture during reaches to objects in external space (Piaget, 1952; Bruner, 1973). During the first half-year, reaching motions with the arm develop before the ability to open the hand and then grasp an object in external space. These patterns of development also mirror the order of developmental changes in previous findings on hand position during self-touch by Thomas et al. (2015). They found that fist contacts were common in early infancy, followed by an increase in palmar hand contacts, and then followed by a decrease in grasps on the clothing or body parts during self-touch in the first half-year.

Although the order of changes in reaching posture in our study was similar to Thomas et al. (2015) (decreasing dorsal and closed fist, whilst palmar and grasps increased), our results were not identical. Infants in their study appeared to make grasping motions during self-touch at a younger age than the age at which infants in our study grasped discrete vibrotactile targets on the face. For example, at just 20–24 weeks (∼5–6 months), their infants were on average using grasping motions slightly over 15% of the time. At this age infants in our study were still grasping targets less than 10% of the time. One explanation is that because it is uncertain whether spontaneous self-touch is directed toward a specific location, the demands of planning and executing a reach are less than when reaching to a discrete target on the body. Future work could directly test self-touch, reaching to body targets, and reaching to external objects in the same infants to study whether they use different motor strategies during these different types of reaching.

In some instances, hand posture varied based on target location. Specifically, dorsal contacts of targets decreased with age for all locations except the mouth. One explanation is that motions directed toward the mouth may have been more defensive in nature than reaches to other locations on the face. If infants reacted to mouth targets by wanting to rapidly contact them, they may have been more likely to reach to them with a strategy that they were already familiar with (dorsal hand contact) than one that involved orienting and using the fingers for grasping. Future work may use motion tracking to compare the development of reaching speeds for different tactile target locations, in part to determine whether infants are reacting to some tactile stimuli defensively and trying to remove or brush them aside quickly. Kinematic motion tracking is able to measure details of arm movements such as spatial location, acceleration of movement, and velocity in the age range under study (e.g., Ouss et al., 2018). In our current paradigm, motion tracking markers or cables, however, would have interfered with reaching to our targets. In the future, a markerless technology might be used to overcome this challenge and examine reaching trajectories to tactile face targets.

### CONCLUSION

This study provides new information about the motor strategies infants use to contact stimuli on the face. Our results suggest that early in the first year the hand is already the preferred effector for contacting the face, and it predominates even more as infants become older. At the same time, when infants use non-hand motor strategies to contact face targets, these strategies appear to be based on the location of the targets. For example, targets on the sides of the face, such as near the ears, can be rubbed on the chair or shoulder but cannot be accessed by the tongue. Furthermore, when infants reach with the hand, motor strategies become better adapted for grasping as infants become older. We found that closed fist and dorsal contact decrease with age; palm and finger contact increase with age, and grasping increases with age. These findings on reaching to the face thus support Jeannerod's (1996) distinction between reaching and grasping as constituting separate but integrated systems that underlie prehension. Finally, the results reported here raise questions regarding the mechanism(s) that underlie developmental changes in effector use and hand posture strategy use when infants contact targets on their faces. One possibility is that these changes are driven in part by experience associated with reaching to the face. For instance, selection of the hand to reach to the face might be reinforced because the hand can manipulate and explore objects better than other effectors. Likewise, opening the hand during reaching, although in part driven by central nervous system and maturational changes, may also be influenced by experience. Although we cannot easily vary experiential input to infants, often because of ethical issues, studies that use modeling with artificial agents in which input is systematically varied might help to provide answers to these questions (Hoffmann et al., 2017).

### AUTHOR CONTRIBUTIONS

fpsyg-10-00009 January 21, 2019 Time: 12:25 # 8

LC, MH, JL, and CN conceptualized the questions addressed in this study. JL and CN designed the study procedure. LC and CN performed the data collection. LC, MH, and JL conceptualized the statistical models. LC performed the data analysis and made figures under the guidance of JL. LC, MH, and JL drafted the manuscript. CN provided revisions.

### REFERENCES

### FUNDING

This research was supported by the National Institutes of Health Award 5R01HD067581. MH was supported by the Czech Science Foundation under Project GA17-15697Y.

### ACKNOWLEDGMENTS

We would like to thank the families who participated in our research and the undergraduate research assistants who helped with behavioral data coding.

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2019 Chinn, Noonan, Hoffmann and Lockman. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Body Representation in Children With Unilateral Cerebral Palsy

Arturo Nuara1,2 \*, Pamela Papangelo<sup>1</sup> , Pietro Avanzini<sup>1</sup> and Maddalena Fabbri-Destro<sup>1</sup>

<sup>1</sup> Consiglio Nazionale delle Ricerche, Istituto di Neuroscienze, Parma, Italy, <sup>2</sup> Dipartimento di Scienze Biomediche, Metaboliche e Neuroscienze, Università di Modena e Reggio Emilia, Modena, Italy

Drawings produced by children provide insights about their physical and psychological status. In children suffering from unilateral cerebral palsy (UCP), self-portraits constitute a unique opportunity to study whether and how their disease affects self-body representation. The aim of the present study is to evaluate self-body representation in UCP children, comparing it to the way they portray both healthy and hemiparetic peers. Ten UCP children were asked to perform 3 drawings: a self-portrait, a portrait of their best classmate, and finally a portrait of a hemiparetic peer who had joint them in a childto-child rehabilitation protocol. As controls, 16 typically developing children were asked to perform a self-portrait, and their best-classmate portrait. The asymmetry index (AI), consisting of the difference between the upper limbs length expressed as percentage of their average, resulted greater in UCP than in controls' self-portrait. More interestingly, UCP children portrayed themselves more asymmetrically relative to their classmates and hemiparetic peers. No difference in terms of AI was found between self- vs. classmateportrait in the control group. This study provides evidence that UCP affects body self-representation, but not body-representation in general. In fact, the asymmetry in upper limb representation observed in children with UCP does not constitute a mere picturing of the hemiparesis, but rather reflects the experienced status of functioning, that is valid only for one's own. The inclusion of portraits in pediatric neurorehabilitation programs might enable clinicians to collect additional evidence about the children self-perceived functioning, i.e., an information not easily obtainable in pediatric patients.

Keywords: childhood stroke, perinatal stroke survivors, self-body representation, self-portrait, body image, perinatal stroke

### INTRODUCTION

Children have been using drawings to express themselves since ancient times (Wittmann and Barber, 2013). The idea that spontaneous drawing of young children may reflect their physical, cognitive and affective status, led psychologists to exploit drawings as a useful tool for assessing child development, personality and emotional adaptation (Cooke, 1885; Goodenough, 1975; Matthews, 2003).

One of the most used methods to measure the level of development through drawing is the DAM test (Draw-a-man) (Goodenough, 1975), which is a projective test using portraits: drawing a person, a child "projects himself in all of the body meaning and attitudes that have come to be represented" (Machover, 1949).

#### Edited by:

Eszter Somogyi, University of Portsmouth, United Kingdom

#### Reviewed by:

Herbert Heuer, Leibniz Research Centre for Working Environment and Human Factors (IfADo), Germany Daniela Bulgarelli, University of Turin, Italy

> \*Correspondence: Arturo Nuara<EMAIL_ADDRESS>
#### Specialty section:

This article was submitted to Cognition, a section of the journal Frontiers in Psychology

Received: 31 July 2018 Accepted: 05 February 2019 Published: 19 February 2019

#### Citation:

Nuara A, Papangelo P, Avanzini P and Fabbri-Destro M (2019) Body Representation in Children With Unilateral Cerebral Palsy. Front. Psychol. 10:354. doi: 10.3389/fpsyg.2019.00354

**121**

The body image, regarded as the conscious representation of the body parts and their relative position, involves both the subject's perceptual body experience with the body limits and conceptual understanding of the body in general (Gallagher, 2005). Parallel to the body image is the so-called body schema, i.e., the subconscious ideas about the shape and size of the body and the relationship of the parts of the body to each other. While both these aspects affect the human figure drawing, deficits specific for body schema or body image are very difficult to separate (de Vignemont, 2010). For this reason, several studies refer to overall disorders of body representation to collectively describe these concepts (Lampe et al., 2016).

Among neurological conditions, cerebral palsy (CP) is the one in which brain injury effects on body representation have been more extensively investigated by means of human figure drawing (see for example Lampe et al., 2016). Abercrombie and Tyson (1966) used the DAM test in order to investigate body representation in CP, finding frequent anthropometric deviations and lacking of body parts in a subset of drawings performed by hemiplegic children, probably reflecting children's projection of their own specific physical impairment. However, these observations were not translated in quantitative terms, nor authors required systematically a self-portrait.

The view that the representation of the "self " in the generic DAM test is not firmly established (Harris, 1963) led some authors to prefer the self-portrait as an elective pictorial tool aimed to investigate children's self-body representation. Indeed, Morin and coworkers have shown that the self-portrait may give access to imaginary and symbolic aspects of subjectivity in normal subjects (Morin and Bensalah, 1998), and to the subjective effects of alterations in body representation in patients with brain lesions (Morin, 1998; Morin et al., 2001). In this regard, Morin et al. (2003) collected 161 portraits performed by hemiplegic stroke patients. Interestingly, these authors reported in a subset of right brain injured patients a dissociation between self- and other-portraits: while drawing a "neglected" selfportrait, they spontaneously drew a complete image of others. These discrepancies persuaded the authors to embrace the idea that unilateral defects of portraits may selectively reflect the subjective alteration of the own body representation.

Asymmetrical self-portraits were not a constant feature in adult hemiplegic patients (Morin, 1993; Morin et al., 2003). This finding induced authors to support a brain-damage onsetdependent hypothesis, postulating that body representation (in particular its sensorimotor side, i.e., body schema) mostly forms in the early development (Lacan, 1966; Morin et al., 2003). Thus, the relative timing between the stroke onset and the development of body schema/image could be a key determinant for the presence of asymmetrical features in selfportraits. In this regard, an ideal model is represented by perinatal stroke survivors, whose injury certainly precedes the body schema/image instantiation. Within such population, it is possible to evaluate whether the motor impairment selectively impacts on self-body representation, rather than on body representation in general.

By enrolling a population of children suffering from UCP due to perinatal stroke showing isolated and unilateral motor deficit with prevalent upper limb involvement, we accounted for: (1) the influence of symbolic disturbances or neglect on self-portraying abilities, (2) the impact of motor impairment on the ability to perform a drawing, and (3) the "unawareness" of the impairment due to the hemiparesis onset posterior to body schema/image establishment processes. Using the test of the human figure, we asked children to draw a self-portrait, a portrait of a hemiparetic peer whom they joined in a child-to-child rehabilitation protocol, and a portrait of a healthy classmate. As controls, 18 ageand sex-matched typically developing children were asked to perform a self-portrait and a portrait of the best-classmate. We finally compared the drawings evaluating the asymmetry of representation of upper limbs, thus providing for the first time to our knowledge a quantitative index of self-portraits asymmetry.

In this study, we hypothesized that children with UCP present a larger asymmetry in self-portraits relative to other portraits, and also relative to self-portraits of typically developing children. In addition, the direct comparison between self-portraits and the hemiplegic peer-portraits should reveal whether this asymmetry is specific for self-representation, or vice versa whether it is associated to the "hemiplegic condition" representation.

### MATERIALS AND METHODS

The study was approved by the Local Ethical Committee (Comitato Etico Area Vasta Emilia Nord) and was conducted according to the Helsinki Declaration. Subjects belonging to the clinical group were recruited in cooperation with "Fight The Stroke" association<sup>1</sup> , in the framework of a broader clinical rehabilitative protocol involving children with cerebral palsy. The families of the controls were enrolled in the realm of another study conducted in our Center on primary school children. Written informed consent was obtained from parents of each child involved. Nineteen UCP children undergoing a child-to-child rehabilitative protocol (clinical group) and 18 typically developing children (control group) were enrolled in the study. The rehabilitative protocol in which children with UCP were involved was composed by 30 daily sessions based on child-to-child interaction, with each participant interacting with another hemiparetic child, performing specific hand exercises. The interacting couples of children remained the same throughout the whole program, thus facilitating a social relationship between them.

Inclusion criteria of the clinical group were: age between 5 and 10; confirmed diagnosis of UCP; evidence of ischemic mono-hemispheric damage at brain MRI; Upper limb Modified Ashworth Scale (MAS) sum score < 2; Total IQ ≥ 70. Exclusion criteria were: attentive or sensory impairments; seizures not controlled by therapy; previous orthopedic surgery or botulinum toxin A injection in the upper limb within 6 months prior to study entry. Eighteen age- and sex-matched typically developing children were selected as controls. Evaluation of UCP and controls was conducted during a single session, in a clinical setting, according to the following procedures.

<sup>1</sup>www.fightthestroke.org

During the clinical evaluation, the following data were collected in children with UCP: neurological complete examination (verifying also the absence of body representation disorders in body-part pointing and naming, awareness of spatial notions and left-right orientation), Global hand motor skills using Besta Scale Global Score [Besta GS Rosa-Rizzotto et al. (2014)], upper limb's spasticity by means of Modified Ashworth Scale (MAS) (Bohannon and Smith, 1987), hand manipulative pattern classification (HC) according to Ferrari et al. (Bassi and Ferrari, 2016) and total Intelligence Quotient (IQ) by WISC-IV battery (Wechsler, 2012). Then, visuospatial constructional ability and visual memory were evaluated with Rey-Osterrieth Complex Figure Test (ROFC) (Shin et al., 2006) administered both in copy and early recall conditions (the latter performed 10<sup>0</sup> after figure visualization).

 Children with UCP were asked to perform 3 drawings in the following order: a self-portrait (SP), a portrait of the best classmate-friend (FP), and a portrait of the hemiparetic child who joint them in the child-to-child rehabilitation program (HP). Controls were asked to perform a self-portrait and a portrait of the best classmate. To ensure a spontaneous body representation, no specific indication was given to children.

From the initial set of drawings, 9 triads performed by UCP children and 2 dyads performed by controls were excluded due to the presence of non-anthropomorphic representations or nonmeasurable body parts. Drawings by 10 UCP children and 16 controls were finally considered for analyses. The length of each represented limb, measured as the inter-joint distance between the shoulder and the wrist, was measured. An asymmetry index (AI), consisting in the difference between the upper limbs length expressed as percentage of their average, was computed according to the following formula: AI = Left−Right Left+Right <sup>×</sup> <sup>2</sup> <sup>×</sup> 100. Giving an example: if we consider a portrait with a left and right arm length, respectively of 5 and 4 cm, the AI = | (5–4)/(5+4)| × 2 × 100 = 22.22%.

After verifying that the normality assumption was not met by AI data, a Kruskal Wallis H test was conducted in order to investigate between-groups differences in AI in portrait types. Within-group AI difference across portrait types has been investigated through a non-parametric repeated measures analysis of variance by ranks (Friedman test). Post hoc comparisons were conducted through non-parametric test (Wilcoxon), and effect size was computed by means of Eta squared and Kendall's W parameters for between- and withingroup analyses. Subsequently, we tested whether asymmetry was correlated to age and/or to clinical variables indexing motor and cognitive functioning. By means of Spearman (ranked) test, the correlation between the AI and Age, IQ, Besta GS and HC were tested. This set of regressors was chosen to test whether age, intelligence level or motor functioning could impact on the AI. Significance threshold was set at 5%.

### RESULTS

The demographic data, clinical features and brain imaging findings of children with UCP are shown in **Table 1**. The mean

M, male; F, female; AH, affected hand; ROCF, Rey-Ostereith Complex Figure Test; Besta GS, Besta global score; ∆BestaGS to peer, difference in Besta Global Score relative to peer (positive values indicate better hand functioning relative to peer); SP-AI, self portrait asymmetry index; HP-AI, hemiparetic portrait asymmetry index; FP-AI, healthy classmate portrait asymmetry index; n.a., not available. Although not part of the analysis, MRI findings have been added in the table in order to demonstrate the presence of a predominantly unilateral brain lesion in the enrolled subjects, as well as to enrich the clinical data of our sample.

age of the 10 analyzed subjects with UCP (7 males, 3 females) was 7.06 ± 1.90 years. Overall, they presented mild hemiparesis with a mild level of spasticity (total MAS = 1.95 ± 1.34), a prevalent upper limb involvement associated to a significant hand motor deficit (Besta GS = 0.48 ± 0.38). According to the HC, 2 subjects belonged to type I ("integrated hand"), 2 to type II ("semifunctional hand"), 3 to type III ("synergic hand"), 3 to type IV ("imprisoned hand"). Visuo-spatial abilities evaluated with ROCF test showed values within ± 2 z-score for both copy and recall conditions (mean z-score = −0.09, range [−2, +1.65], mean z-score = −0.44, range [−1.92, + 0.91], respectively), according to the Italian pediatric normative (Rey, 1968) (see **Table 1** for individual ROCF z-scores collected in copy condition).

Neurological examinations show neither neglect nor hemiasomatognosia. All children were able to name their body parts correctly, no orientation abnormalities were detected, and spatial concepts were preserved. No children were excluded due their clinical profile. Overall, drawing were highly heterogeneous in terms of graphic style, with the precision and richness of details varying according to the age. However, an internal consistency was evident within-subject, with the three drawings presenting recurrent elements and a common graphical style (see **Figure 1A**).

The control group was composed by 16 typically developing children (10 M, mean age 7.37 ± 1.75). As expected, ROCF test performed in controls returned normal values for both copy and recall conditions (mean z-score = 1.51, range [−0.5, 2.5] and mean z-score = 0.92, range [−0.86, 1.85], respectively).

The Kruskal-Wallis H test showed a statistically significant difference in AI in SP between two groups [χ 2 (1) = 11.025, p = 0.001, effect size: η <sup>2</sup> = 0.418]. Post hoc contrasts indicated a significantly greater AI in self-portraits by UCP children relative to Controls (p < 0.001, see **Figure 1B**).

Within UCP group, the Friedman test applied to the AI rendered a chi-square value of 11.4, returning a significant effect of portrait type (p = 0.003, effect size: Kendall's W = 0.57). In particular, UCP children represented upper limbs more asymmetrically in self-portraits relative to other drawings (mean AI for SP: 39%, FP: 14%, HP: 22%). Post hoc contrasts indicated a significantly greater AI in self-portraits in comparison both to FP (p = 0.005) and HP (p = 0.013) (see **Figure 1B**). Moving to control group, no AI significant difference between SP and FP was found.

The study of clinical-demographical regressors on AI of self-portraits did not show any significant correlation. Besides, differential regressors related to the hemiparetic peer did not show significant correlations with the difference between SP and HP asymmetry indexes.

### DISCUSSION

The aim of the present study was to evaluate self-body representation in hemiparetic children affected by UCP with predominant upper limb involvement and to compare this pictorial representation to portraits of both hemiparetic and healthy peers. For this purpose, we evaluated the upper limb asymmetry in the three portrait types, which resulted significantly higher in self-portraits compared to both hemiparetic and healthy peers ones. Of note, self-portraits produced by typically developing children showed no significant difference in asymmetry, neither in comparison to portraits of others performed by the same group, nor relative to the portraits of others performed by children with UCP. This finding led us to regard the asymmetry of upper limbs in self-portraits as a specific signature of hemiparetic children.

The detection of asymmetries in own upper-limb representation in children with UCP is coherent with a previous work conducted by Abercrombie and Tyson (1966) on children suffering from cerebral palsy, in which the occurrence of unbalanced representations of upper limbs were reported in children with an unilateral brain damage. However, these authors used the Draw-a-Man test (Goodenough, 1975) as a projective test, implicitly making children represent their own body image. Differently from these authors, we explicitly asked children to produce both self- and classmate- portraits. The possibility to directly compare these drawings allowed us to verify whether upper limb asymmetry reflects an alteration of the own body image rather than a deviant representation of human body in general. Two are the major strengths of this

FIGURE 1 | (A) Example of portraits performed by a child: self-portrait, portrait of the hemiparetic peer with similar clinical conditions (5 years-old, unilateral cerebral palsy with prominent upper-limb motor impairment), portrait of best classmate. Note – only in self-portrait – the asymmetrical representation of upper-limb, with the paretic hand smaller than the contralateral one and without fingers. (B) Asymmetry index differences across different portrait types in children with UCP and controls. SP, self portrait; FP, portrait of the best classmate-friend; HP, portrait of the hemiparetic peer. Bars indicate SEM; <sup>∗</sup>p < 0.05, ∗∗p < 0.01.

approach. On one side, the within-subject comparison allowed us to rule out the contribution of subject peculiarities in drawing. On the other side, despite diagnosed for UCP, our clinical sample was free from visuospatial and symbolic disturbances, hemiasomatognosia and neglect, thus controlled for major disorders affecting pictorial representation.

The finding of a three-times higher level of asymmetry in self vs. classmate representation is in line with a previous work of Morin et al. (2003). These authors conducted a multivariate analysis evaluating 161 portraits performed by adult stroke patients (including both self-portraits and portraits of others). As expected, authors reported frequent "unilateral lacks" in right brain injured patients' drawings, attributing these difficulties to several aspects of hemineglect. However, some right-hemiparetic patients, despite drawing a "neglected" self-portrait, spontaneously drew a complete image of others, leading to postulate that unilateral defects of portraits may selectively reflect an alteration of body self-representation.

Although in line with our findings, whether this deviant representation constitutes a signature of the self-representation, or rather it is a more general representation of the hemiparetic condition, is still unclear. To address this issue, we required participants to portray also a hemiparetic peer with whom they had been experiencing a daily interaction in the previous month. This condition allow us to demonstrate that the asymmetrical picturing of upper limbs constituted a signature of the self-representation, favoring the view that selfportrait features are grounded in a first-person, sensorimotor bodily experience.

No correlation was found between the asymmetry in upper limb representation and indices of motor functioning. However, the small sample size and the heterogeneity of the investigated population in terms of brain lesions

### REFERENCES

require further studies to reveal a possible link between these two domains.

### CONCLUSION

In conclusion, our data indicate that UCP with predominant upper limb deficit affects body self-representation, but not body-representation in general. We suggest that the upper limb asymmetry does not constitute a picturing of pathological condition, but rather it may reflect the experienced status of motor functioning, that is valid only for one's own. We propose that evaluating self-portrait in hemiparetic children undergoing pediatric neurorehabilitation programs and quantifying the asymmetry of the self-representation could provide a valuable index of self-perceived functioning. Such procedure, well-suited for pediatric age, would enrich the clinical picture of the patient by adding a psychometric information to clinical outcomes, enabling clinicians to collect information not easily obtainable in pediatric patients.

### AUTHOR CONTRIBUTIONS

AN collected the data and drafted the manuscript. PP and PA revised the manuscript. MF-D interpreted the data and revised the manuscript.

### ACKNOWLEDGMENTS

We would like to thank Francesca Fedeli and Roberto D'Angelo (www.fightthestroke.org) for their help in recruiting participant and for their contribution in collecting drawings.

palsy: reliability and validity studies. Eur. J. Phys. Rehabil. Med. 50, 543–556.

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2019 Nuara, Papangelo, Avanzini and Fabbri-Destro. This is an openaccess article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Learning and Acting in Peripersonal Space: Moving, Reaching, and Grasping

Jonathan Juett\* and Benjamin Kuipers\*

*Computer Science and Engineering, University of Michigan, Ann Arbor, MI, United States*

The young infant explores its body, its sensorimotor system, and the immediately accessible parts of its environment, over the course of a few months creating a model of peripersonal space useful for reaching and grasping objects around it. Drawing on constraints from the empirical literature on infant behavior, we present a preliminary computational model of this learning process, implemented and evaluated on a physical robot. The learning agent explores the relationship between the configuration space of the arm, sensing joint angles through proprioception, and its visual perceptions of the hand and grippers. The resulting knowledge is represented as the peripersonal space (PPS) graph, where nodes represent states of the arm, edges represent safe movements, and paths represent safe trajectories from one pose to another. In our model, the learning process is driven by a form of intrinsic motivation. When repeatedly performing an action, the agent learns the typical result, but also detects unusual outcomes, and is motivated to learn how to make those unusual results reliable. Arm motions typically leave the static background unchanged, but occasionally bump an object, changing its static position. The reach action is learned as a reliable way to bump and move a specified object in the environment. Similarly, once a reliable reach action is learned, it typically makes a quasi-static change in the environment, bumping an object from one static position to another. The unusual outcome is that the object is accidentally grasped (thanks to the innate Palmar reflex), and thereafter moves dynamically with the hand. Learning to make grasping reliable is more complex than for reaching, but we demonstrate significant progress. Our current results are steps toward autonomous sensorimotor learning of motion, reaching, and grasping in peripersonal space, based on unguided exploration and intrinsic motivation.

Keywords: sensorimotor learning, autonomous robot learning, peripersonal space, reaching and grasping, intrinsic motivation, developmental robotics

### 1. INTRODUCTION

### 1.1. What Is the Problem?

We observe that human infants are born without the ability to reach, grasp, and manipulate nearby objects. Their motions are seemingly aimless, but careful research has established that infants are biased toward moving objects and toward keeping the hands in view (von Hofsten, 1982, 1984; van der Meer et al., 1995; van der Meer, 1997). After a few months of unguided experience, human infants can reach deliberately to contact nearby objects, and after a few more months, they can grasp nearby objects with a reasonable degree of reliability (Berthier, 2011).

#### Edited by:

*Matej Hoffmann, Faculty of Electrical Engineering, Czech Technical University in Prague, Czechia*

#### Reviewed by:

*Elio Tuci, University of Namur, Belgium Lorenzo Jamone, Queen Mary University of London, United Kingdom Alessandro Roncone, University of Colorado Boulder, United States*

#### \*Correspondence:

*Jonathan Juett<EMAIL_ADDRESS>Benjamin Kuipers<EMAIL_ADDRESS>
Received: *11 August 2018* Accepted: *04 February 2019* Published: *22 February 2019*

#### Citation:

*Juett J and Kuipers B (2019) Learning and Acting in Peripersonal Space: Moving, Reaching, and Grasping. Front. Neurorobot. 13:4. doi: 10.3389/fnbot.2019.00004*

During the early process of learning to reach, children's arm trajectories are quite jerky, suggesting the underdamped behavior of partially tuned control laws (Thelen et al., 1993). A tempting hypothesis about early reaching is that visual servoing brings the images of the hand and the target object close together. However, an elegant experiment (Clifton et al., 1993) refutes this hypothesis by showing that young children's reaching behavior is unaffected when they can see the target object, but not their own hands. During later reach learning, children and adults move the arm and hand more smoothly and directly to the target object, and they start depending on visual access to the moving hand (Berthier, 2011).

We abstract this developmental psychology problem to a problem in robot learning (**Figure 1**): How can a robot learn, from unguided exploratory experience, to reach and grasp nearby objects? We use the term peripersonal space (PPS) for the space immediately around the robot, accessible to its arms and hands for the manipulation of objects.