In conclusion, observation of behaviors in condition C2 across sessions indicates that after the early successes of the first sessions, infants' behavior changed in sessions 2–4. Instead of immediately pulling the rake, they either pointed to the toy, sometimes after discarding the rake, or they grasped the rake and explored it. Thus, in those sessions, infants tended to pay attention either to the toy or to the rake but they seldom connected the two objects and when they did, it was not to retrieve the toy. These switches between different strategies across sessions are comparable to the overlapping wave patterns described by Chen and Siegler (2000) in their microgenetic study of tool use at 18–35 months of age.

If, as we suggest, the early successes in toy retrieval in condition C2 were only due to the physical proximity between rake and toy (so that any movement of the rake would tend to bring the toy closer), rather than to a true understanding of the rake's functionality, this may explain why there was no rapid transfer from "successes" in C2 to successes in C4 and C5.

We will next analyze behaviors in conditions C4–C5 in order to elucidate how children understood how to use the rake when the toy was clearly separated from the tool.

#### *Toy not near the rake (C4 and C5)*

We have seen that despite all their experience of success (expected or not) when the toy was inside the rake, when it was clearly separate from the rake (in C4 and C5) it took the infants several sessions and many trials to understand how to use the rake to retrieve the toy. In particular, it took the infants 23–35 trials in all in C4 and C5 (median: 28 trials) across 4–6 sessions (mean: 5) to succeed, and they were aged 16–20 months (mean 17.8 months) when they reached this stage. If the infants did not learn much from their own "unexpected" success in C2, then how did they learn to use the rake in conditions C4 and C5? By exploring the rake? By trial and error? By watching a demonstration by an adult? In the following section we explore these alternatives by checking which behaviors preceded success in C4 and C5.

*Exploring the rake alone and in connection with the toy.* In this section we ask whether exploring the affordances of the rake over successive sessions allowed the child to accumulate enough knowledge to finally make the link between rake and tool, and thereby accomplish the task.

First of all, exploring the rake itself ("R") was very frequent over the successive sessions (see **Figure 6**). It was the second most frequent behavior (20.5%, all sessions considered) after behavior "T" (36.4%). Connecting the rake with the toy (T+R) was less frequent (16.4%). Note that the "T+R" behaviors of the first sessions seemed not to be directed toward retrieving the toy (see **Video S2**), and were very different from behaviors 16 or 17 of S1 (see **Table 1**) observed in the last sessions where infants clearly connected the rake with the toy to try to retrieve it even though they failed. Hitting the toy with the rake seemed to be a game *per se* in the first sessions, and infants who used this strategy did not even grasp the toy systematically when it happened to come within reach after they hit it.

A second point is the following: individual patterns showed that all five infants fluctuated between the different strategies across sessions (see **Figure 7**). Sometimes they mostly pointed toward the toy, sometimes they mostly explored the rake, and at other times they mostly connected rake with toy. Doing statistics on the evolution of the different strategies across sessions would be misleading as it is clear that the five infants switched in different ways between pointing to the toy, exploring the rake, and connecting the rake with the toy (T+R) during sessions preceding success. What is common across infants is the large amount of fluctuation and the lack of a clear, single tendency: we might have expected, for instance, to observe an increase in the connection

between rake and toy in the session preceding success, but this was not the case.

Thus, we found little evidence that gradual accumulation of knowledge about rake affordances leads to the ability to make the connection between rake and toy. There was frequent rake behavior but it did not gradually increase; nor was rake + toy behavior systematically preceded by frequent rake behavior.

*Learning from trial and error.* While the infants appeared not to have learned from their unexpected successes in C2 during the first session, we wondered if they learned from their errors in C4–C5. In other words, did they correct their movements after trying unsuccessfully to grasp the toy with the rake? There is some indication of this, since behavior S1, which reflects awkward or partly successful attempts to use the rake to obtain the toy (trial and errors), was more frequent in the first half of the first successful session (22.2%) than in the second half of the

same session (17.5%), whereas S2 increased from 1.6 to 11.1% (see **Video S3**).

*Learning from demonstration by an adult.* Another mechanism to learn how to use a rake might be to observe others doing it. This would be a more economical method than trial and error. As mentioned above, in all sessions, after the first failure in C4 and C5, infants received a demonstration from either the parent or one of the experimenters (usually two demonstrations in a row). Infants clearly did not learn much from the adult's demonstration until late in the study. With only one exception (infant 1, session 3), none of the infants succeeded in retrieving the toy with the rake in C4 or C5 right after a demonstration before the sixth session. In addition, infant 1 did not repeat her success before the sixth session, either before or after demonstration. To check whether the behavior had been influenced by the demonstration despite not sufficing to lead to retrieval of the toy, we compared the level of performance, indexed by the obtained score, on the trials preceding and following demonstration for C4 and C5 considered together (see **Figure 8**). It can be seen that the score on trials just following demonstration did not differ greatly from the score of the trials preceding a demonstration until the last session. An ANOVA was performed on the score as a function of condition (×2, before and after the demonstration), and of session (×4, we choose to start at session 3 to be able to include infant 2) with repeated measures. It showed no main effect of condition, a significant and large main effect of session [*F*(3*,* 12) = 31*.*3, *p <* 0*.*001; partial η2 = 0*.*89], and a significant and moderate condition x session interaction [*F*(3*,*12) = 7*.*5, *p <* 0*.*01; partial η2 = 0*.*65]. A *post-hoc* LSD test indicated that on the last session the score after demonstration differed significantly from the score before demonstration (*p <* 0*.*0001). Thus, infants started to benefit from demonstration relatively late, and not before 18 months.

In sum, when the toy was not inside the rake, infants started to use the rake to retrieve the toy between 16 and 20 months of age. Before that, they either explored the rake *per se* or focused on the toy, or to a lesser extent made some connection between rake and toy but apparently without the intention to retrieve the toy with

the rake. When successes first appeared, they often were awkward and partial, or they happened after demonstration by an adult. But neither of these behaviors was observed during the first sessions. It could be that the capacity to correct inadequate motor planning (trial and error strategy), and the capacity to benefit from a demonstration (observational learning) require that the infant already have some intuition of the solution.

### **DISCUSSION**

As noted in the introduction, few controlled experimental studies have considered in detail what mechanisms might underlie the acquisition of the use of a rake-like tool in infancy, and among these, only one is longitudinal. The essential conclusion from the existing studies is that spatial proximity, number of planning steps, and familiarity with the tool are factors that play a role. However these studies present no hypotheses about what drives progress in tool acquisition. In particular, they do not elucidate the question of whether the child learns to use the rake through progressive familiarization with use of the rake in interacting with other objects, or whether more or less sudden insight is involved.

Even though our conclusions are incomplete, the present longitudinal study makes some preliminary qualitative steps toward answering this question, and toward sketching out possible mechanisms underlying tool acquisition. The approach was to study a small number of infants, and analyse their detailed behavior at regular intervals. In this respect, the study differs from most contemporary approaches, and comes closer to the old, more qualitative observational methods of Piaget. As such the conclusions do not have the same statistical value as is usual in today's studies, but they provide valuable ideas for further work.

A first interesting point that our results brings to light concerns the interpretation of early successes observed in the literature in cases when there is no spatial gap between rake and toy.

#### **EARLY SUCCESSES WHEN THERE IS NO SPATIAL GAP**

Our study confirms previous work showing that situations where there is no spatial gap between the rake and the toy, infants as young as 9–12 months can have little difficulty retrieving the toy (Bates et al., 1980).

But our results allow us to provide more insight into these early successes than has previously been coming forth.

First, with respect to the situation where the toy is attached to the tool: here our results clearly show that at 12 months (and most probably before that) children already know that they can move one part of a rigid object by moving another part: all infants succeeded as of the first trial and looked clearly at the toy from the start of their pulling movement. The result is compatible with extensive work using purely perceptual measures at even earlier stages of development (e.g., Spelke and Van de Walle, 1993).

But second, an important contrast exists with respect to the situation where the toy is contiguous but not attached: it can be touching or with a small spatial gap but within the trajectory of the rake. Here our results show quite distinctly that successes in such cases do not correspond to real understanding of the function of the rake as a tool, but to the fact that because of its spatial proximity, playing with the rake will likely cause the toy to move. Evidence that the infant had no notion that the rake would bring the toy closer is first: when the child moves the toy with the rake but not far enough to grasp it, the child will often not continue using the rake but stretch out with its hand to try to get the toy; and second, after a successful trial, in a subsequent trial an infant will often grasp the tool and move it around the toy before pointing to the toy (see Voulomanos, 2011, for other examples of u-shape developmental curves).

#### **MEANS-END BEHAVIOUR**

The conclusion from these considerations is thus that real understanding of the use of the rake as a tool only emerges in our data after about 18 months, and that early successes without a spatial gap do not correspond to proper understanding. This is consistent with our previous cross-sectional study (Rat-Fischer et al., 2013), but it raises the question of the relation to the literature on means-end behavior.

In the literature it is sometimes claimed (Willatts, 1999) that means-end behavior of various types is observed as early as 8 months, examples being given of the case of a cloth support, string, or of an extended tool like a stick, to obtain an out of reach object.

Our results lead us to ask whether success in such studies could be reinterpreted in a way similar to what we proposed for the rake task in the no-spatial-gap condition: Could it be that in many classical means-end tasks, successes before the second year of life were accidental, and due to the fact that any small motion of the cloth/string/tool will have tended to bring the object into motion, thereby drawing attention toward the object, causing the child to look at it, and then allowing the child to attain it by manual grasping. For instance, Willatts' (1999) experiment showing apparent clear presence of intentional cloth-pulling to retrieve a toy at 8 months can be re-interpreted as infants' having (1) an automatic cloth-pulling action which they put into play whenever confronted with the cloth/toy situation; and (2) having a larger attentional span in peripheral vision, and as a consequence being more likely to notice the toy moving and thus to look at it; and (3) having overall larger arm motions, thus making the cloth move further on every pull. These three mechanisms would result in coding as "intentional" (measured among others by probability of attaining the toy, probability of looking at it). A further suggestion that younger infants might not actually fully, practically, understand the function of the tool, can be got from experiments in which the infant is given the choice of several strings, or between different tools, in order to solve the task. In such situations it is known that children do not succeed immediately until well into the second year (Brown, 1990). Similarly, in one study on 14 infants aged 16 months, we also observed that infants rarely chose the correct string among a set of four when three were non-connected (Rat-Fischer et al., under revision). It can always be claimed that difficulty in such situations derives from confusion, attentional load, or goal/sub-goal competition induced by the visually more complicated set-up, but a more parsimonious account of the results when taken together with our present findings, might be that infants in fact do not have proper practical understanding of the notion of tool as a means to attain an object until about 18 months. Sommerville and Woodward's (2005) observation that 10-month old infants, as a group, do not "planfully" succeed in a cloth support task is consistent with these ideas. Note, however, that in the same study, the authors observed that when a rectangular box was substituted for the cloth, 10-month-old infants "planfully" succeeded in pulling the box to retrieve the toy, thereby demonstrating a sensivity to the causal structure.

The above re-interpretation of 8-month-old's successes at many classical means-end tasks, does not, we suggest, apply to our 12-month-old's success at C1 (toy attached to the rake). There we claim the children's behavior is truly intentional, reflecting knowledge that moving one part of the rake will move another part. This seems likely because the children were older, but also the data clearly demonstrate that all infants succeeded as of the first trial and looked clearly at the toy from the start of their pulling movement.

# **PATH TO SUCCESSFUL USE OF THE TOOL WHEN THERE IS A SPATIAL GAP**

A major purpose of the present study was to try to cast light on the process that leads to infants finally understanding the notion of tool. We were hoping that among the different behaviors, behavior T+R, that is, the behavior of bringing the rake into contact with the toy, would allow the infant to test the affordances of the rake and bring the child closer to understanding its functionality. We thus expected that T+R would generally increase before the child demonstrates success. Such findings would have been in line with Kahrs et al.'s (2012) observation of progress in the kinematics of banging movements between 7 and 14-months, that the authors considered as a pre-adaptation for later instrumental hammering, as well as with the observation of "non-random errors" and exploration of objects preceding tool-use in young animals (Meulman et al., 2014).

Curiously however this was not what we found. Taking together the data for all infants, we found that the T+R category of behaviors was not obviously correlated with subsequent successes at C4–C5, and occurred about equally often in all sessions preceding Sessions 4 and 5 where successes started occurring. Looking at the data individually for each infant also did not reveal any tendency for T+R or any other behavior to increase clearly just before success for any infant.

#### **FACTORS LIMITING SUCCESS**

One first limiting factor could have been that infants actually did not have the goal of retrieving the toy. However this does not seem to be the case. Even though some infants showed an interest in playing with the rake, the desire to get the toy was evident at some point in all sessions for all infants.

As already mentioned, in C4–C5 infants frequently pointed toward the toy as their first action. This pointing might be an example of pre-potent action patterns that young learners must inhibit in order to solve the problem (by using the tool). The difficulty of overcoming prepotent actions has been demonstrated with young animals (cf. review by Meulman et al., 2014). Inhibition of prepotent action patterns may be facilitated by maturation of the prefrontal cortex (Diamond and Gilbert, 1989).

Attentional limitations might be another limiting factor. In C4-C5 it is generally the case that after first trying to attain the toy by pointing toward it, infants lose interest and then switch their attention to the rake. However this attention shift does not imply that infants know that the rake can be used to get the toy. On the contrary, our evidence suggests that infants' goal is now purely to explore the rake for its own sake. After some tool exploration, infants then often revert to pointing toward the toy. It could be the case that dividing attention between the task at hand (how to retrieve the toy?) and the affordance of a novel object (what kind of actions can be done with a rake?) involves excessive cognitive load for the infant.

Another limiting factor to be considered is manual dexterity. It could be argued that physical inability to move the tool with an effective movement limits the chance of success. There are two reasons why we do not think this to be the case: first, once the infants started to try to use the rake to retrieve the toy, these partial successes were very rapidly followed by efficient successes, within the same session. In other words, after trying to use the rake to retrieve the toy, infants might be awkward for the first trial but corrected their error almost immediately. Second, in another study, pure visual exposure to a parent using the rake several times at weekly intervals, without the infant itself being allowed to manually manipulate the rake, was enough to significantly advance the age of success by between two weeks and two months (Somogyi et al., under revision).

#### **LACK OF LEARNING FROM OBSERVATION IN OUR STUDY**

Another piece in the puzzle that must be integrated into a theory explaining the emergence of rake use is our striking result on the effect of demonstration from an adult: infants were only able to profit from a demonstration precisely around the age when they would in any case be able to do the task spontaneously1. This is consistent with our previous cross-sectional study bearing on 60 infants, aged 14, 16, 18, 20, and 22 (Rat-Fischer et al., 2013) and with other work showing that proper understanding of the causal structure of means-end tasks in observational learning only matures in the second half of the second year (Meltzoff, 1995; Bellagamba and Tomasello, 1999; Huang et al., 2002).

However, it is in contrast to some other recent research which has investigated the ability of infants to solve means-end problems by observing an adult perform the task. In these experiments it was found that in certain means-end tasks, infants are able to profit from observation of a demonstration as early as 12 months (Provasi et al., 2001; Esseily et al., 2010; see Elsner, 2007, for a review). Such findings seem incompatible with our current finding that even after demonstration, infants were unable to succeed in using the rake until about 18 months.

As a way to explain the incompatibility, a possibility might be to claim that the particular materials employed by Esseily et al. and Provasi et al. had the property that even a fairly approximate imitation of the adult's demonstration would tend to lead to success. The means-end tasks used by these authors thus more closely resembled the *no spatial gap* conditions of our experiment, where infants were frequently successful because, however they moved the rake, the toy was likely to come closer. This is in contrast to

1Although we have very recently demonstrated that emphasizing the demonstrator's intentions may advance the age of success, cf. Esseily et al. (2013).

the spatial gap conditions of our experiment, where a particular, precise form of raking motion is necessary for success.

To explain the ability to learn from demonstration from an adult in Esseily et al. and Provasi et al., we could then appeal to the fact that infants as early as 6 months have the capacity to *imitate* actions that they are shown (or have seen) (see Poulson et al., 1989; Elsner, 2007; Elsner et al., 2007, for reviews). Because of the relative simplicity of the tasks involved in Esseily et al. and Provasi et al., such imitation might then have led to higher success rates in the demonstration conditions. But under this hypothesis, these successes would not have corresponded to real understanding of the functionality of the means that led to success. In our experiment, where the task is somewhat more complex involving two stages (first grasping the rake, then adequately manipulating it), such imitation without understanding will not have led to success.

In conclusion, this longitudinal study of five infants learning how to use a rake reveals the interest (and difficulty!) of studying individual behaviors in a particular task over several months. No single type of behavior in our study seemed to lead systematically to success, leading us to suggest that many processes are involved. It may be that a variety of experiences involving familiarization with objects, exploration of object affordances, attentional factors, social cues, action planning, some of them associated with personal experience, others associated with brain maturation, each contribute small amounts of expertise that all come together fairly suddenly around 18 months to allow the child to understand that the rake can extend the body's range of action. There may be different routes to success and the mechanisms leading to success may differ from one infant to the next. An interesting question for future work will be to manipulate factors or conditions that allow infants to acquire tool use earlier than the second year—an example being our finding that simple visual exposure to the parent using the rake several times at weekly intervals alone can accelerate progress by many weeks (Somogyi et al., under revision). Future work should also include using different materials to check to what extent the children transfer their knowledge to different tools and different situations.

#### **ACKNOWLEDGMENTS**

J. Kevin O'Regan was supported by ERC Advanced Grant 323674 FEEL.

#### **SUPPLEMENTARY MATERIAL**

The Supplementary Material for this article can be found online at: http://www*.*frontiersin*.*org/journal/10*.*3389/fpsyg*.* 2014*.*00491/abstract

**Video S1 | Infant 1, 15 months, C2: discarding the tool.**

**Video S2 | Infant 3, 12 months, C4: hitting the toy with the rake.**

**Video S3 | Infant 1, 18 months, C5: trial and error and observational learning before first full success.**

#### **REFERENCES**

Barrett, T. M., Davis, E. F., and Needham, A. (2007). Learning about tools in infancy. *Dev. Psychol.* 43, 352–368. doi: 10.1037/0012-1649.43. 2.352

**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.

*Received: 11 February 2014; accepted: 06 May 2014; published online: 23 May 2014. Citation: Fagard J, Rat-Fischer L and O'Regan JK (2014) The emergence of use of a rake-like tool: a longitudinal study in human infants. Front. Psychol. 5:491. doi: 10.3389/fpsyg.2014.00491*

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

*Copyright © 2014 Fagard, Rat-Fischer and O'Regan. 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) or licensor 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.*

# Tool use imagery triggers tool incorporation in the body schema

# *Matteo Baccarini 1,2†, Marie Martel 2,3†, Lucilla Cardinali 1,2†, Olivier Sillan1,2, Alessandro Farnè1,2† and Alice C. Roy 2,3 † \**

*1 Lyon Neuroscience Research Center, INSERM U1028, CNRS UMR5292, ImpAct Team, University Lyon1, Lyon, France*

*2 Hospices Civils de Lyon, Mouvement et Handicap, Neuro-immersion, Lyon, France*

*3 Laboratory on Language, Brain and Cognition (L2C2), CNRS UMR 5304, Cognitive Sciences Institute, University Lyon 1, Lyon, France*

#### *Edited by:*

*Cristina Massen, Leibniz Research Centre for Working Environment and Human Factors, Germany*

#### *Reviewed by:*

*Martina Rieger, UMIT - University for Health Sciences, Medical Informatics and Technology, Austria Irina M. Harris, University of Sydney, Australia*

#### *\*Correspondence:*

*Alice C. Roy, Laboratory on language, brain and cognition (L2C2), CNRS UMR 5304, Cognitive Sciences Institute, University Lyon 1, 167 bd Pinel, Bron 69500, France e-mail<EMAIL_ADDRESS>
*†These authors have contributed equally to this work.*

Tool-use has been shown to modify the way the brain represents the metrical characteristics of the effector controlling the tool. For example, the use of tools that elongate the physical length of the arm induces kinematic changes affecting selectively the transport component of subsequent free-hand movements. Although mental simulation of an action is known to involve -to a large extent- the same processes as those at play in overt motor execution, whether tool-use imagery can yield similar effects on the body representation remains unknown. Mentally simulated actions indeed elicit autonomic physiological responses and follow motor execution rules that are comparable to those associated with the correspondent overt performance. Therefore, here we investigated the effects of the mental simulation of actions performed with a tool on the body representation by studying subsequent free-hand movements. Subjects executed reach to grasp movements with their hand before and after an imagery task performed with either a tool elongating their arm length or, as a control, with their hand alone. Two main results were found: First, in agreement with previous studies, durations of imagined movements performed with the tool and the hand were similarly affected by task difficulty. Second, kinematics of free-hand movements was affected after tool-use imagery, but not hand-use imagery, in a way similar to that previously documented after actual tool-use. These findings constitute the first evidence that tool-use imagery is sufficient to affect the representation of the user's arm.

#### **Keywords: tool-use, mental imagery, body representation, action, kinematics**

# **INTRODUCTION**

Tool-use modifies our perception of the world around us. Several studies on tool-use in both healthy and brain-damaged populations have consistently reported that tool use alters our perception of space. Two main interpretations have been put forward to account for perceptual changes observed following tool-use: either space perception *per se* would be altered in such a way that far stimuli become processed as if they were nearer (Berti and Frassinetti, 2000; Maravita et al., 2001; Farnè et al., 2005; Witt and Proffitt, 2008; Holmes, 2012; Osiurak et al., 2012; Bourgeois et al., 2014), or alternatively tool-use would displace the attentional focus to the tip of the tool (Holmes et al., 2007). These effects have been related to plastic features of the multisensory processing of the peripersonal space, as identified electrophysiologically in non-human primates: in monkeys trained to retrieve distant objects with a rake, Iriki et al. (1996) revealed that visuotactile hand centered receptive fields appeared to extend along the tool axis (see for review, Maravita and Iriki, 2004; Cardinali et al., 2009a; Brozzoli et al., 2012). In addition, tool-use modifies the spatial metric of our own body. When asked to point to touched landmarks on their arm (middle fingertip, wrist, elbow) after using a mechanical grabber to reach and grasp objects, neurotypical participants localized these landmarks as if their touched body-parts were more distant from each other than before tooluse (Cardinali et al., 2009b, 2011a; Sposito et al., 2012; Miller et al., 2013). Most interesting for the present study, besides modifying space and body perceptual metrics, tool-use shapes our actions. The body representation we use for action (i.e., the body schema) is modified when using tools in a way such that the tool is incorporated and becomes part of our body (Baccarini and Maravita, 2013). In humans, we demonstrated that using a mechanical grabber that extends the arm's functional length by 40 cm, extends the subject's arm length representation (Cardinali et al., 2009b, 2012). Our sensorimotor system seems to be able to immediately transfer the control from the arm to the new arm + tool configuration (Van der Steen and Bongers, 2011). The motor control of free-hand reaching movements performed right after use of this tool exhibits an altered kinematics: the representation of an elongated arm in the body schema translates in the later occurrence and reduced amplitude of some kinematics events (acceleration, velocity, deceleration peaks). Such changes in motor control of the arm have been considered as the key kinematics signatures for the incorporation of the tool into the body schema (Cardinali et al., 2011b) and revealed the latter is a highly plastic representation that quickly builds-up on previous experience.

Strikingly, mere mentally simulated motor experiences are sufficient in some cases to trigger subsequent actions modifications and athletes commonly use motor imagery to improve their performance (Driskell et al., 1994; Roure et al., 1999). Motor imagery might be sufficient to acquire functional object knowledge, however the built representations have been shown to be less detailed than when experiencing actual movement with the object (Macuga et al., 2012; Paulus et al., 2012). Moreover, brain areas recruited to perform actual or imagined movement execution are not strictly overlapping (Imazu et al., 2007; see for review Dietrich, 2008). Nevertheless a contagion from movement imagery to movement execution is possible as both evolve on a similar time-scale and follow very similar biomechanical rules. Motor imagery follows so faithfully the constraints imposed to the motor system that the postural adjustments normally accompanying a voluntary reaching movement while standing up are also present in an imagined reaching situation (Boulton and Mitra, 2013). Execution time of mentally simulated movements has been shown to be comparable in duration to actually executed movements (Papaxanthis et al., 2002; for review, see Jeannerod and Frak, 1999; Guillot and Collet, 2005). An important constraint of the motor system is the speed accuracy trade-off known as Fitts law (1954). According to this law, increasing the velocity of execution of an action leads to decrease in accuracy, and conversely, increasing the accuracy demands increases the time needed to perform the task. Several studies have demonstrated that Fitt's law holds in motor imagery, imagined movement times linearly increasing with task difficulty (Decety and Jeannerod, 1995; Maruff et al., 1999). In a prehension task paradigm, Frak et al. (2001) had subjects to physically or mentally grasp a cylinder between the index and thumb while varying the orientation of the axis formed by the opposed fingertips on the object, the so-called opposition axis. When free to adopt a natural finger positioning on the object, subjects typically tend to keep the opposition axis invariant from trial to trial, as changing it determines an additional cost on the musculo-articulatory system (Paulignan et al., 1997). Frak et al. (2001) elegantly demonstrated that prehension movements requiring different pre-determined orientations of the opposition axis induce similar modulations of movement time for both physically executed and imagined movements. Recently, Jacobs et al. (2010) used a similar paradigm to investigate free-hand grasping and grasping with a handheld tool. Subjects' performance during mental imagery respected the bio-mechanical constraints imposed by the tool during real movement execution (see also Rieger and Massen, 2014). Tooluse imagery has been less explored but is known to modify space perception as tool execution does (Witt and Proffitt, 2008; Davoli et al., 2012; Gabbard and Caçola, 2013) and to follow Fitt's law (Macuga et al., 2012). Most recently it has been reported that expert tool-users are sensitive to the held tool during imagery whereas naive tool-users are not (Bisio et al., 2014).

On the one hand, thus, evidence from real tool-use indicates that it modifies the kinematics of subsequent free-hand movements as if they were performed with a longer arm; on the other hand, mental imagery of tool-use seems to reproduce tool-use execution quite accurately. Taken together, these findings raise the question of whether mere tool-use imagery is sufficient to modify the representation of the arm's length. To answer this question we designed an experiment in which the rationale was the following: if imagining using the same mechanical grabber that extends the arm's length by 40 cm (Cardinali et al., 2009a,b, 2012) is sufficient for this tool to be incorporated into the body schema and thus increases the subject's represented arm length, then the real execution of free hand prehension movements subsequent to tool-use imagery should display those kinematics signatures that we observed after actual tool-use. Since motor imagery is known to be modulated by task difficulty, varying task difficulty is an efficient way to control that motor imagery was properly performed (Lotze and Halsband, 2006). We therefore applied the paradigm introduced by Frak et al. (2001), and manipulated the orientation of the opposition axis to be used to grasp a cylinder in order to vary movement's difficulty. In different sessions separated by one day, participants were required to perform prehension movements toward objects with different oppositions axes before and after having mentally simulated these movements with their free hand (as a control), or using the mechanical grabber.

# **MATERIALS AND METHODS**

#### **PARTICIPANTS**

Sixteen neurologically healthy subjects (8 male; mean age 22.4 years; *SD*: 3.7; range from 18 to 32) participated in the study. All were right-handed and had normal or corrected-to-normal vision. All participants gave written informed consent to participate in the study, which was approved by the local ethics committee and conformed to the Helsinki Declaration.

#### **APPARATUS AND PROCEDURES**

Participants were comfortably seated in front of a table with the right hand closed in a pinch-shaped grip on a switch. The left hand, palm down, was pressing a response button. The target object was a plastic cylinder (5 cm in diameter and 17 cm height) placed on the table at a distance of 35 cm along the sagittal axis, in line with subjects' right shoulder. Two colored dots on the upper edge of the cylinder marked the grasp landing positions required for the tips of the thumb (red) and index fingers (yellow). The virtual line connecting these two points of contact determined the Opposition Axis (OA) of the grip. At the beginning of each trial, the cylinder was presented with one of three possible OA, namely −22◦, 0◦ and +22◦ with respect to the subject trunk. Each OA was presented an equal number of times in a pseudorandomized order. A horizontal arrow was taped at 13 cm of height from the table on a wooden block, located about 10 cm to the left of the cylinder and served to indicate the height at which the participants had to lift the object (**Figure 1**).

The experiment consisted of three tasks, each presented over two consecutive days: Pre-imagery free-hand grasping task (18 trials), Motor Imagery task (54 trials), and Post-imagery free-hand grasping task (18 trials). During the Pre- and Postimagery free-hand grasping task, participants were required to reach, grasp and lift the target object up to the arrow with their right hand (see **Figure 2**). They were instructed to grasp the object using a precision grip by placing their thumb and index fingertips on the respective colored dots. Once the trial was performed, participants got back to the starting position, closed their eyes and

**panel).** Subjects placed their right hand on a starting switch (purple) and the left hand on a response button (green). The target object was a cylinder, located 35 cm from the starting point. On its upper side were

waited for an acoustical "go" signal to open their eyes and perform the next trial.

During the Motor imagery task of day 1, subjects were required to imagine using their right hand to reach for, grasp and lift the cylinder up to the height indicated by the arrow. They were instructed to wait for an acoustical go signal to open their eyes and start imagining performing the task. Participants had to raise their left hand to release the switch as they started their imagery the opposition axis, which could be of three orientations: −22◦, 0◦ and +22◦. On the left an arrow indicated the height to which the object should be lifted.

trial, and to put their hand back down to press the switch once it was accomplished (i.e., the object was lifted at the height indicated by the arrow). Participants' right hand was kept still on the right switch during the whole duration of the imagery task. Two pauses were planned after 18 trials and 36 trials respectively. Other pauses were delivered if required. During pauses participants were allowed to open and close the fingers of their right hand and to move their arms. The Motor imagery task of day 2 was identical to that of day 1, except that subjects had to imagine performing the prehension movement with a grabber they were holding still in their right hand. The grabber was constituted of an ergonomic handle (9 cm) fitted with a lever, a 33-cm-long rigid shaft, and a "hand" with two articulated fingers (10 cm). Squeezing the lever (vertically) made the "fingers" of the tool close (horizontally). The grabber used here was identical to that used in previous work documenting effects of actual too-use on subsequent free-hand kinematics (Cardinali et al., 2009b). During the whole duration of the imagery task the "tool fingers" were kept in a pinch grip posture on the start switch. During pauses, subjects were allowed to move the arm, but could not drop the tool. In order to be able to imagine using the grabber, at the end of day 1 subjects were familiarized with the tool by performing 18 grasping trials (6 for each opposition axis). Tool-use imagery never took place on day 1 to avoid potentials tool integration effects to carry over on day 2.

#### **KINEMATIC RECORDING**

Three infrared light emitting diodes (IREDs) were placed on the subjects' right hand: on the medial lower corner of the thumb nail, on the lateral lower corner of the index finger nail and on the skin proximal to the styloid process of the radius at the wrist. The reaching component of the movement was characterized by the wrist marker displacement, while the grip component was characterized by the thumb and index displacement. Spatial localization of the markers was recorded with an Optotrak 3020 (Northern Digital Inc; sampling rate: 200 Hz; 3D resolution: 0.01 mm at 2.25 m distance). Analyzed parameters included latencies and amplitudes of acceleration, velocity and deceleration peaks for the transport component, and latency and amplitude of the maximum grip aperture for the grip component. The total movement duration of imagined movements (from release to press of the left response button, corresponding to the same events of actual movements) was also extracted.

#### **STATISTICAL ANALYSIS**

To assess the effect of the OA on imagined movements, subjects' average imagined movement durations (MD) were submitted to a repeated measure ANOVA with Effector (hand/tool) and Opposition Axis (−22◦/0◦/+22◦) as within-subject factors. In order to establish the effect of motor imagery with the tool on subsequent free-hand movements, we performed a repeated measure ANOVA on movement kinematic parameters with type of Imagery (hand/tool), Session (pre / post imagery) and Opposition Axis (−22◦/0◦/+22◦) as within-subject factors. When necessary, Newman-Keuls *post-hoc* test were used.

#### **RESULTS**

#### **MOVEMENT DURATIONS DURING MOTOR IMAGERY**

As shown in **Figure 3**, the analysis revealed no significant difference between hand and tool imagined movement durations [*F*(1*,* 15) = 0*.*60, *p* = 0*.*45; *MD* = 2538 vs. 2633 ms]. A main effect of Opposition Axis [*F*(2*,* 30) = 16*.*0, *p <* 0*.*001; η2 *p* = 0*.*52] highlighted that the most difficult OA(−22◦) required longer performance time (*MD* = 2702 ms) compared to the other orientations (0◦ *MD* = 2489 ms; +22◦ *MD* = 2565 ms, all *p*-values *<* 0.002), which tended to differ between them (*p* = 0*.*055). The interaction between Effector and Opposition Axis almost reached significance [*F*(2*,* 30) = 3*.*0, *p* = 0*.*065], potentially suggesting that OA may have a slightly different impact on tool and free-hand imagery.

Taken together these results highlight the difficulty raised by the most unnatural opposition axis (−22◦) irrespective of the used effector, indicating that participants performed free-hand and tool imagery tasks reliably.

#### **EFFECT OF FREE-HAND vs. TOOL MOTOR IMAGERY ON SUBSEQUENT FREE-HAND MOVEMENTS**

To investigate the effects of tool-use imagery on the subsequent free-hand movement execution, the following section focuses on the critical interaction between the factors type of Imagery (hand vs. tool) and Session (pre vs. post imagery) across the kinematic parameters of the transport and grasping components (see **Tables 1, 2** for an exhaustive report of the statistical results and means respectively). Two of such interactions were found to be significant, for the wrist velocity peak [*F*(1*,* 15) = 11, *p <* 0*.*01; η2 *p* = 0*.*42] and the deceleration peak [*F*(1*,* 15) = 9*.*76, *p <* 0*.*01; η2 *p* = 0*.*39; see **Figure 4**]. Free-hand imagery did

not induce any significant modifications on the subsequent movements' kinematics (velocity peak: pre: 773 mm/s vs. post: 793 mm/s, *p* = 0*.*30; deceleration peak: pre: −2511 mm/s2 vs. post: −2632 mm/s2, *p* = 0*.*28). The pre imagery session of day 1 differed from that of day 2, in that subjects reached higher velocity and deceleration peaks -before motor imagery- in day 2 as compared to day 1 (all *p <* 0*.*01), compatible with some practice effects. Critically, participants' free-hand movements performed after tool-use imagery exhibited significantly decreased wrist velocity peak (pre 827 mm/s vs. post: 785 mm/s, *p <* 0*.*02) and deceleration peak (pre: −2829 mm/s2 vs. post: −2569 mm/s2, *p <* 0*.*04) with respect to those performed before tool imagery. As expected, no significant interaction was found on the kinematic parameters of the grasping component.

#### **DISCUSSION**

Here we investigated the effects of tool-use imagery vs. free hand imagery on subsequent free-hand grasping movements. As movement imagery is sensitive to task difficulty we asked participants to conform their final grip to three opposition axes of varying difficulty. In line with our expectations, the opposition axes differently taxed imagined movement durations, thus confirming that participants successfully engaged in the imagery tasks. Our analysis then focused on the differences of free-hand imagery vs. tool-use imagery on subsequent movements. While free hand grasping imagery did not affect actual free-hand movements, the latter movements performed after tool-use imagery were characterized by significant decrease of both wrist velocity and deceleration peaks. Together with previous findings from our group, these results indicate that imagery of tool-use may be sufficient to update the representation of the arm length used to execute free-hand movements. We have indeed reported previously that using a tool to grasp an object modifies the kinematics of subsequent free-hand movements as if the participant performed object prehension with a longer arm (Cardinali et al.,

*MGA, maximum grip aperture. Significant p values (<0.05) are reported in bold.*

# **Table 2 | Main values ± 1 s.e.m. of each kinematic parameter according to the full factorial design.**

*MGA, maximum grip aperture.*

2009b), and we proposed that these kinematic modifications are the fingerprint of the tool incorporation in the body schema (Cardinali et al., 2011a,b, 2012). Here we investigated whether tool-use imagery could be sufficient to induce such modifications of the body schema. While imagery has been largely explored in psychology and cognitive sciences, tool-use imagery has become a field of investigation only recently. Rieger and Massen (2014) have examined how different tools translate in different tool imagery performances by requiring participants to color a rectangle using pens with different thicknesses. As it was the case for physically executed actions, imagined actions were influenced by the pen's thickness, the thinnest one giving rise to longer movement times

to fill-up the rectangle. In the same vein, Macuga et al. (2012) reported that despite some inaccuracy, the Fitt's law holds for movements imaginarily performed with tools.

To make a step forward, here we tested whether tool-use imagery effects, besides influencing ongoing performance *during* the tool-use imagery task, can last sufficiently to modify actual movements performed *afterwards*, without the tool. We first aimed to ensure that imagery was accurately performed. To this aim, we varied the difficulty of an object prehension task by requiring participants to grasp a cylinder putting their index and thumb or the tool's "fingers" in predetermined positions on the cylinder, thus creating different orientations of the opposition axis(OA) between the fingertips. Our findings confirm and extend those of Frak et al. (2001) as we show that the −22◦ orientation of the OA is the most difficult and hence time consuming one, irrespective of whether movements were imagined with the hand or the tool.

When considering the effects of tool imagery on subsequent movements, our results make a considerable step further by demonstrating that tool-use imagery is sufficient to warrant tool incorporation in the body schema (i.e., the representation the brain uses to plan and execute actions). When comparing free hand movements performed before and after tool-use imagery, movement kinematics presented wrist velocity and deceleration peaks of decreased amplitude. Previously, after physical tool-use, we reported such reductions in amplitude for the very same kinematic parameters, accompanied by protracted latencies and discussed these kinematics modifications as the hallmark of tool incorporation in the body schema (Cardinali et al., 2009b, 2012). Similar to previous work, here the direction of the changes triggered by tool-use imagery on the subsequent movement kinematics (i.e., the reduction of maximum velocity and deceleration peaks) is compatible with a change of the represented length of the arm in the direction of its elongation. Compared to short-arm people, long(er)-armed participants naturally tend to perform the same grasping action with reduced velocity and deceleration peaks. For such movements, they also tend to display longer latencies of these parameters (see supplemental data in Cardinali et al., 2009b). In the present study, a relatively brief tool-use imagery task appeared sufficient to reduce the maximal amplitude of transport component parameters, thus suggesting profound consequences for real movements, from imagined movement execution. In contrast to our previous work, the latencies of the same parameters were not significantly modified by tool-use imagining suggesting that although very similar, tool-use imagery is not in all respects identical to actual tool-use execution. Nevertheless the modifications in motor control did replicate those found after actual tool-use both in the direction (i.e., reduction) and specificity, affecting selectively the transport component parameters and leaving the grasping ones unaltered (Cardinali et al., 2009b, 2012).

Noteworthy, the modifications on real hand movements induced by tool-use imagery unambiguously points to a tool incorporation in the body schema (e.g., reduced wrist velocity) and as such differ from the learning effects typically reported after mental practice (increased performance due to increased velocity). This observation finds additional support in the results of free-hand imagery performed in day 1. Indeed, normal subjects are by essence experts in performing manual prehension and hence mental training with the very same effector was ineffective in triggering any significant kinematic modification of subsequent executed movements (Allami et al., 2007). Moreover, the pre imagery session of day 2 as compared to that of day 1 displayed increased velocity and deceleration peaks, an effect that is exactly opposite to the one observed after tool-use imagery.

Finally, potential limitations of our study need to be addressed. First, the lack of execution session with the tool, before motor imagery, prevented us from directly comparing execution and imagery movement duration with the tool. Our main aim was not to compare tool execution and tool imagery (see Rieger and Massen, 2014 and Macuga et al., 2012 for this comparison), rather our study focused on tool-use vs. free-hand imagery effects on subsequent free-hand movements. A second potential limitation arises from the fact that to avoid potential carry-over effects freehand imagery and tool-use imagery were not counterbalanced, tool-use imagery occurring always on day 2 after hand imagery. The post-test performed on day 2 is thus the fourth time subjects executed the free-hand grasping task. One could have expected a facilitation effect similar to that observed between the pre session of day 1 and 2; by contrast, velocity and deceleration peaks decreased after tool-use imagery, an effect that is thus compatible with our previous results obtained after physical tool-use. Third, it might have been of interest to directly compare the consequences of both tool-use execution and tool-use imagery. Since we used the very same paradigm and grabber as the one we used for evaluating the effects of tool use execution (Cardinali et al., 2009b, 2012), the results obtained here nevertheless point to some differential effect of imagined vs. real tool-use, as the velocity and deceleration peaks, but not the latencies of these parameters, were affected by tool-use imagery.

To conclude, tool-use imagery not only adheres to most of the physical rules of actual movement execution, but has protracted consequences on the real execution of movements performed afterwards without the tool that are readily understandable as the product of previous tool incorporation.

#### **ACKNOWLEDGMENTS**

This work was supported by FRC (Fondation pour le Recherche sur le Cerveau), the Labex/Idex (ANR-11-LABX-0042), the James S. McDonnell Foundation and the ANR Samenta ASD-BARN 01502. Matteo Baccarini was supported by the Fondazione Carlo Fornasini-PoggioRenatico.

#### **REFERENCES**

Holmes, N. P. (2012). Does tool use extend peripersonal space? A review and reanalysis. *Exp Brain Res*. 218, 273–282. doi: 10.1007/s00221-012-3042-7

**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.

*Received: 16 January 2014; accepted: 06 May 2014; published online: 30 May 2014. Citation: Baccarini M, Martel M, Cardinali L, Sillan O, Farnè A and Roy AC (2014) Tool use imagery triggers tool incorporation in the body schema. Front. Psychol. 5:492. doi: 10.3389/fpsyg.2014.00492*

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

*Copyright © 2014 Baccarini, Martel, Cardinali, Sillan, Farnè and Roy. 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) or licensor 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.*

# Differential mechanisms of action understanding in left and right-handed subjects: the role of perspective and handedness

# *Rachel L. Kelly and Lewis A.Wheaton\**

*Cognitive Motor Control Laboratory, School of Applied Physiology, Georgia Institute of Technology, Atlanta, GA, USA*

#### *Edited by:*

*Cristina Massen, Leibniz Research Centre for Working Environment and Human Factors, Germany*

#### *Reviewed by:*

*Thierry Chaminade, Centre national de la recherche scientifique, France Massimiliano Conson, Second University of Naples, Italy Aine Ni Choisdealbha, Lancaster University, UK*

#### *\*Correspondence:*

*Lewis A. Wheaton, Cognitive Motor Control Laboratory, School of Applied Physiology, Georgia Institute of Technology, 555 14th Street, Atlanta, GA 30332-0356, USA e-mail<EMAIL_ADDRESS>The ability to comprehend outcomes of skilled action is important for understanding the world around us. Prior studies have evaluated the perspective an action is performed in, but few have evaluated how handedness of the actor and the observer interact with action perspective. Understanding handedness affords the opportunity to identify the role of mirroring and matched limb action encoding, which may display unique strategies of action understanding. Right and left-handed subjects were presented with images of tools from egocentric or allocentric perspectives performing movements by either a left or right hand. Subjects had to judge the outcome of the task, and accuracy and latency were evaluated. Our hypothesis was that both left and right-handed subjects would predict action best from an egocentric perspective. In allocentric perspectives, identification of action outcomes would occur best in the mirror-matched dominant limb for all subjects. Results showed there was a significant effect on accuracy and latency with respect to perspective for both right and left-handed subjects. The highest accuracies and fastest latencies were found in the egocentric perspective. Handedness of subject also showed an effect on accuracy, where right-handed subjects were significantly more accurate in the task than left-handed subjects. An interaction effect revealed that left-handed subjects were less accurate at judging images from an allocentric viewpoint compared to all other conditions. These findings suggest that action outcomes are best facilitated in an internal perspective, regardless of the hand being used. The decreased accuracy for left-handed subjects on allocentric images could be due to asymmetrical lateralization of encoding action and motoric dominance, which may interfere with translating allocentric limb action outcomes. Further neurophysiological studies will help us understand the specific processes of how left and right-handed subjects may encode actions.

**Keywords: perspective, handedness, action understanding, limb-matched, mirror-matched, tool use**

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# **INTRODUCTION**

Understanding skilled action is a basic aspect of our daily living. Skilled action in humans frequently involves the use of tools in order to complete action goals. In order to understand skilled tool-use actions, we must understand at least two elements: how to identify the tool needed for a specific task (contextual knowledge) and understand how the tool is used to complete the action goal (physical knowledge; Mizelle andWheaton, 2010). Our knowledge of a tool comes from the fact that we learn tool and action associations in our cognitive-motor system and from this knowledge we are able to use it to understand not only how to accomplish skilled actions ourselves, but also how to predict the ultimate goal of actions executed by others.

Previous research suggests how action understanding occurs through observation (Fadiga et al., 1995; Iacoboni et al., 1999; Bekkering et al., 2000; Rizzolatti et al., 2004). Action understanding likely requires an imitative capability that allows a persons' motor system to precisely organize body motion in order to achieve an observed movement. The ideomotor theory describes that action and the perception of action are related by common neural systems (Massen and Prinz, 2009). Thus perceiving another's actions or action outcomes elicits the same action in the observer's motor system. It has been proposed that when viewing a tool or object, not only are the physical elements of the scene being processed, but also an additional higher level of processing occurs which can prompt "functional affordance" representations (Mizelle et al., 2013). In this work, functional affordances are the possible object-based tool actions that best "afford" a desired action goal. When subjects looked at static correct tool and object images, sensorimotor activation was observed which indicated that action was being understood and the motor system was being driven. Type of tool or object also affects the ability to understand the ultimate action goal. New tools might not be able to simulate a motor plan as would a known tool; however, our previous work (Mizelle et al., 2011) has shown that after directly training with a novel tool one time, it activates the same neural tool network that known tools activate.

Seeing an action and being able to recognize the possible outcomes are vital for not only the potential of motor simulation of action, but also for understanding the tool-action outcomes themselves. What remains unclear is what particular variables impact the perception of action and the understanding of action goals.

One variable that has been studied is the perspective of observed actions. It has been suggested that perspective encompasses not only visual objects in a scene, but also how concentration is focused in order to determine specific judgments about the environment (Lindgren, 2012). In this work, first and third person perspectives in a virtual world simulation were analyzed. Results indicated that there was a significant advantage in subject's memory for tasks and task related elements when watching first person perspective simulations. Subjects also achieved higher accuracy during recall. How this applies to interpreting action based on other people's movements that are typically in the third person perspective is still unclear. Mentally simulated actions from an egocentric perspective are considered visually and motorically familiar (Ni Choisdealbha et al., 2011; Conson et al., 2012) as this affords optimization of motor imagery and action encoding. Alternatively, the allocentric perspective may not be motorically familiar to oneself, and in order to process allocentric action, motor imagery may necessitate visual transformations. In Ni Choisdealbha et al. (2011), they showed that right and left-handed subjects were faster at judging hand stimuli in an egocentric orientation that corresponded to their own dominant hand. It was proposed that this effect was due to better utilization of visual and sensorimotor information to facilitate judgments in the dominant limb. In allocentric orientations, behavioral strategies shifted to "visual only" so that subjects could reorient the stimuli to align with "self" as a method for interpretation. This in turn suggests that subjects use a self-centered motor strategy to interpret action.

However, it is unclear how a subject's handedness and the hand involved in seen actions may affect these results. In previous work, it has been shown that the left cerebral hemisphere is specialized for tool-use action (Raymer et al., 1999; Frey et al., 2005). Neuroimaging studies have shown left lateralization in right-handed participants for both left and right hand tool pantomime movements (Moll et al., 2000; Choi et al., 2001; Johnson-Frey et al., 2005; Bohlhalter et al., 2009; Cabinio et al., 2010). Further, left parietofrontal lateralization for performance of tool-use action was observed in left and right-handed subjects using their dominant hand (Vingerhoets et al., 2012). This evidence leads to the indication that damage to the left cerebral hemisphere resulting in ideomotor apraxia (which causes the inability to correctly perform tool-use and communicative gesture on command) should be a bilateral deficit (Wheaton and Hallett, 2007). Apraxia can be seen in both hands after left hemispheric damage, which suggests that the left hemisphere network controls skillful tool-use knowledge for both left and right hand movements (Heath et al., 2003).

It is worth considering that in left-handed subjects, there is a unique hemispheric dissociation which exists for motor planning of tool use (left parietofrontal) and primary motor cortices (right motor cortex). Whether this dissociation is disadvantageous to understanding action outcomes is a key goal in this work. It has been argued that encoding seen action utilizes a principle of motor resonance, where seen actions may be encoded in

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the observer's motor system, perhaps using motor representations from the contralateral hemisphere of the seen arm (Gallivan et al., 2013). For actions seen in an egocentric (first person) perspective, limb-specific resonance is achievable. Under these circumstances, right-handed subjects watching a right-handed action would have no dissociation of motor planning and primary motor cortex. However, due to the diminished left lateralization of motor activation of left-handed action in right-handed subjects (Cabinio et al., 2010), there is the potential for some dissociation for right-handed subjects watching left-handed action. This assumes that action is encoded in the subject's limb that matches the seen action. It is unclear what would happen in left-handed subjects, where seeing a right-handed action may bring tool-use activation and motor activation into the same hemisphere. Further, we frequently have to understand actions in daily living, and we commonly view them from an allocentric (third person) perspective. There are two possible ways an action can be encoded in the allocentric perspective in order to understand that action: limb-matched and mirroredmatched (**Figure 1**). Limb-matched is a biological-limb match to the subject. For example, for a dominant right-handed person it would be a right-handed allocentric action. Mirror-matched would occur when watching a matched dominant limb perform an action as if you were looking in a mirror (for a dominant right hand person it would be a left-handed allocentric action). According to prior studies, mirror-matched movements are less challenging to imitate because they are spatially compatible and do not require a shift of reference (Chiavarino et al., 2007). Other studies show that both right and left-handed subjects were faster in egocentric perspectives when looking at their dominant hands and faster in allocentric perspectives when looking at other's nondominant hands (Conson et al., 2010). Thus, mirror-matched may be advantageous in this paradigm.

The motivation of this study is to evaluate how perspective and handedness interact to understand and identify tool-action

outcomes. Our hypothesis was that both left and right-handed subjects would identify action outcomes best from an egocentric perspective. When looking at stimuli from an allocentric perspective, identification of action outcomes would best occur in mirror-matched dominant limb for right and left-handed subjects. This study will help us better understand how we translate handedness and motor representations from different perspectives.

# **MATERIALS AND METHODS**

#### **SUBJECTS**

Twenty right-handed subjects (7 males; average age, 22.8, SD, 3.0) and 19 left-handed subjects (11 males; average age: 21.6, SD, 2.2) participated in the study. All subjects were neurologically normal and had normal or corrected-to-normal vision. Handedness was evaluated by the Edinburg Handedness Inventory (Oldfield, 1971) with right-handed subjects having an average score of 82.54 (SD: 15.87) and left-handed subjects averaging −57.65 (SD: 26.81). If the handedness score was > + 40 then the subject was right-handed and if the score was <−40 then the subject was considered left-handed. If the subject was between +40 and −40 inclusive, the subject was considered ambidextrous and was excluded from the study. The maximum score is +/−100. The experimental procedure was approved by the Georgia Institute of Technology Institutional Review Board and consent was obtained from all participants prior to experiment.

#### **TRAINING**

Subjects were first trained on inserting and extracting tools on an upright stationary wooden board with screws protruding facing the subject. The subject had to use three different tools to perform the task, two were unfamiliar and one was familiar. Familiarity of the tools was confirmed verbally by subjects when prompted if they knew what each tool was. If they were familiar with an "unfamiliar" tool or unfamiliar with a "familiar" tool they were excluded from the study. The familiar tool was a twist screwdriver, while the unfamiliar tools were a push style "Yankee" screwdriver and a rotating (plumber's) screwdriver being used by an actor (**Figure 2**). The use of multiple screwdrivers allowed us to maintain task and instruction consistency. These screwdrivers were particularly chosen because to use them, very different actions are required, but the action outcome is the same (insert or extract). The twist screwdriver uses a simple clockwise/counter-clockwise forearm rotation to insert or extract the screw. The push style screwdriver operates by pushing the driver handle that rotates the bit clockwise or counterclockwise based on the position of a toggle switch. The plumber's screwdriver is similar to the twist, except that it demands circular rotation at the elbow to insert or extract the screw. The twist is the most familiar with push and rotational being the least familiar. Of these three, the push only has one action to insert or extract the screw (the other two require clockwise or counterclockwise rotation) and it is treated as a control image. A training board was placed in front of the subject's visual field and was reachable at arm's length. Participants used each of the three screwdrivers to insert five screws all the way into the

board and then screw the same screws all the way back out to their initial starting position to obtain the motoric actions required to use each tool. Subjects were instructed to choose any five screws that were at a comfortable height for them to manipulate.

### **STIMULI AND TASK**

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After all training was completed, subjects performed an action understanding task based on the trained tools. Subjects were seated comfortably in a chair and shown randomized action images of the three different tools on a 106.7 cm (42 inch) visual monitor (visual angle = 18.7◦). Images were high-resolution grayscale images of either a right or left-handed instructor holding one of the previously mentioned tools in either an allocentric or egocentric perspective.

While seated with a response pad comfortably in their hands, subjects were presented first with a circle (4–6 s), then a fixation cross which alerted subjects that the trial was about to start (500 ms), followed by the instructor-tool image (4 s). While the image (**Figure 3**) was on the screen, the subject was told the following: "The images on the screen will show you any of the tools you have just trained with, being used by either a left or right hand instructor, and can be shown either in an egocentric (as if you yourself are using the tool) or allocentric (as if you were watching me use the tool) perspective. On the image there will be a red arrow located on the wrist of the actor. Based on the direction of the arrow, you will need to simulate in your mind which way the hand is rotating, and answer if the hand is driving the screw into the board, or is it pulling the screw out of the board." If they thought the actor was inserting the screw into the board, they were instructed to indicate by pushing the left button with their left hand on the response pad. If they thought the actor was extracting the screw, they were instructed to indicate by pushing the right button with their right hand on the response pad. Based on the stimuli presented, this afforded an equal number of responses with the left and right hands without bias to the response hand matching the stimulus hand (i.e., a correct response would equally occur for the same number of left or right hand image actions). The subject was instructed to answer as quickly and accurately as possible from the onset of the image. If the subject did not respond before the 4 s time period, the circle reappeared and no response was counted. There were 12 different image types. Each type was displayed twice in each of the two blocks that lasted approximately 13 min each (**Figure 4**). All images were presented in a pseudorandom order and correctness and latency of responses were recorded.

#### **ANALYSIS**

Behavioral responses were recorded over two blocks of trials. All responses were recorded with Stim2 version 4.0 (Neuroscan 2003, El Paso, TX). Data sets were imported into Excel spreadsheets and organized by type into blocks. For each block, the response and latency average were calculated for each subject and every image type excluding any trials that the subject missed. Overall, there was no significant difference in missed trials for any image type (*p* = 0.685). All block averages were compiled into a grand average for each image type. Averages were then entered into IBM SPSS Statistics 19. A 4-way multivariate ANOVA (MANOVA) was computed with factors perspective (egocentric and allocentric) x hand of actor (left and right hand) x tool (traditional and rotational screwdrivers) x hand of subject (left and right-handed). Where appropriate, *t*-tests were used to identify interaction effects between the different image types. For *t*-tests, significance was assessed at *p* < 0.05 with Bonferroni correction for all comparisons.

# **RESULTS**

#### **LATENCY**

For latency of response time, there was a main effect of perspective (*F*(1,304) = 33.66, *p* < 0.05) and of tool (*F*(1,304) = 9.23, *p* < 0.05). In **Figure 5A** it is shown that when subjects look at egocentric images, they respond significantly faster than if they were looking at an allocentric image. Looking at novel tool images, subjects respond slower when compared to familiar tools.

There were no other main or interaction effects regarding latency.

### **ACCURACY**

Accuracy (percent correct) was also evaluated for each image type. There was a significant main effect in percent correct due to perspective (*F*(1,304) = 37.44, *p* < 0.05), with the egocentric perspective having lower error rates (**Figure 5B**). There was a second main effect with respect to percent correct for hand of subject (*F*(1,304) = 8.31, *p* < 0.05), with right-handed subjects having lower error rates than left-handed subjects.

An interaction effect was seen for perspective x hand of subject (*F*(1,304) = 4.06, *p* < 0.05). Right-handed subjects looking at images in the egocentric perspective had significantly lower error

**FIGURE 3 |The wooden board with screws that were mounted for subject training; (A) an exemplar image for right-handed egocentric rotating screwdriver driving a screw "in" and (B) an exemplar image for a left-handed allocentric rotating screwdriver pulling a screw "out".**

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rates compared to allocentric images (*p* = 0.019). Left-handed subjects looking at images in an allocentric perspective had the highest error rates overall compared to all the other conditions (**Figure 6**). An additional interaction effect was seenfor tool x hand (*F*(1,304) = 4.88, *p* < 0.05), however when explored, there were no significant individual effects.

# **DISCUSSION**

Right and left-handed subjects were recruited in order to judge tool-use action outcomes while hand of instructor, perspective, and tool type used in the images were manipulated. Specifically, we sought to evaluate how perspective and handedness interact on a learned tool in order to accurately determine an action goal using a discrete motor task. In conformation of our first hypothesis, we found that egocentric perspective images had higher accuracy and faster latencies when compared to allocentric images. Our second hypothesis was refuted, as there was no effect of handedness of subject and limb performing the action. We will further discuss our findings based on the hypotheses presented.

# **ALLOCENTRIC VERSUS EGOCENTRIC PERSPECTIVES**

Our first hypothesis was that both left and right-handed subjects would be able to judge action best from an egocentric perspective. Results revealed there was a significant effect of accuracy and latency with respect to perspective for both right and left-handed subjects. The highest accuracy and fastest latency was found in the egocentric perspective for both sets of subjects, which supports our first hypothesis. These findings are in line with previous studies which suggest that action outcomes are best facilitated in an internal (egocentric) perspective, regardless of the hand being used (Conson et al., 2010; Lindgren, 2012; Oosterhof et al., 2012). Looking at previous neural studies, the left parietal lobe has been shown to be active in coding representations of the body, and the right parietal lobe is active for visuospatial orienting (Iacoboni et al., 1999; Watanabe et al., 2011). Specifically, Watanabe et al. (2011) studied right-handed subjects who viewed and then imitated limb-matched ("anatomical") and mirrormatched ("specular") images performing a finger touch task. The findings in this work suggested that the more dissimilar the actors hand was from the position of the participants, the more difficulty they had in interpreting the imitation task, and there was a corresponding notable increase in right posterior parietal cortex (PPC) activation. They suggested that the increase in activation was due to the demands of aligning visuospatial representations with kinesthetic signals from self and therefore it was more challenging to imitate the images. These findings could explain why our behavioral results showed effects of latency and accuracy, particularly disadvantageously in the allocentric perspective. Together, these authors suggest that when an action is observed in the allocentric perspective, it is possible that action resonates to either of the observer's limbs as a technique to interpret action more readily. Although visual areas associated with mental rotation were not assessed, this could be a future direction to further explore the neural mechanisms driving the behavioral effect.

### **EFFECTS OF HANDEDNESS IN ALLOCENTRIC PERSPECTIVE**

Our second hypothesis was that in allocentric perspectives, optimal action prediction would align best in mirror-matched dominant limb for right-handed and left-handed subjects. Handedness of subject showed an effect on accuracy, where right-handed subjects were significantly more accurate in the task than left-handed subjects overall. However, neither right nor left-handed subjects showed behavioral effects to the allocentric actions performed with a mirrored or matched hand, which does not support the second portion of our hypothesis. We studied

action prediction by testing if the ability for resonance to occur may be impacted in a limb specific way. In action perception, according to the ideomotor theory, a subject's motor system and the associated action representations are activated when perceiving action from another person (Massen and Prinz, 2009). Perceiving body movements and corresponding remote goals influences how those actions are understood. Functional affordances include all possible tool-based goal directed actions that best "afford" a desired action goal (Mizelle et al., 2013). In this work, we proposed that functional affordances are proposed to be critical for the ability to simulate action and understand all possible action outcomes. Importantly both body movements and action goals have a bidirectional association in order for the perception of action to trigger action in the observer (Massen and Prinz, 2009; Paulus, 2012). If the perception of action in an observer comes from bidirectional understanding of movements and goals, then mapping all seen action to the dominant or non-dominant limb in an allocentric perspective could facilitate action understanding. Although allocentric actions showed no bias to either limb for our behavioral study, Conson et al. (2010) did in fact see a limb bias in the allocentric perspective. This could be due to different experimental demands between the paradigms where our study was focused on action outcome and Conson et al. (2010) was focused on hand laterality and mental rotation. Future neurophysiological studies will further evaluate specific neural mechanisms that may relate to activation of left or right sensorimotor areas in a similar task.

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**and hand of subject (\****p <* **0.05).** Right-handed subjects looking at images in the egocentric perspective were more accurate at the task when compared to allocentric images (\**p* = 0.019). Overall, left-handed subjects looking at images in an allocentric perspective were significantly worse compared to all other conditions (\**p* < 0.05).

When compared to right-handed subjects, left-handed subjects were significantly less accurate when judging the outcomes of allocentric images. The decreased accuracy for left-handed subjects on the allocentric images could be due to an asymmetrical lateralization of encoding action and motoric dominance in the brain, which may interfere with translating allocentric limb action outcomes within their own motor system. In prior work (Frey et al., 2005), left and right-handed callosotomy patients were studied in order to understand hemispheric specialization for tooluse. The left-handed patient performed worse at demonstrating tool-use actions with the dominant left hand compared to their right hand, but the right-handed patient performed best with the dominant right hand and worse with the left. These results indicate that the left hemisphere is specialized for tool-use information. This idea has been well validated in human neuroimaging experiments (Vingerhoets et al., 2012). For left-handed people (because the right hemisphere controls their dominant hand) a challenge is presented when trying to access tool representations from the opposite (left) hemisphere. However, performance of tool-use actions was not a disadvantage in their right-handed callosotomy patient. If tool-use information is stored in the left hemisphere for both right and left-handed people, then it is possible that because right-handed people have a dominant left motor hemisphere (creating a hemisphere match), they would have an advantage when interpreting action outcomes in our study. Extending these concepts, these results could suggest the reason left-handed subjects perform significantly worse in allocentric action outcome interpretation is because when they view the images they utilize an additional mechanism that is needed to facilitate coordination of information across the hemispheres. Specifically, we propose that when action is seen in the allocentric perspective, left-handed subjects have an additional demand of utilizing left hemisphere action encoding along with right hemispheric motor and visuospatial rotations to comprehend action

outcomes (Watanabe et al., 2011). Importantly, right hemispheric visuospatial rotation may relate to right-handed subjects performing worse on allocentric versus egocentric actions (**Figure 6**). Why this affects accuracy, but not latency is worth consideration in behavioral and neurophysiological studies to understand aspects of decision delay versus decision accuracy in similar tasks.

#### **EFFECTS OF LATENCY VERSUS ACCURACY**

The finding that latency was significantly increased for allocentric images contributes to previous research that states allocentric images are harder to interpret compared to egocentric images (Ni Choisdealbha et al., 2011; Zhou et al., 2012). However, latency effects did not persist through any other variable in this study. Given the difficulty of the task, there could possibly be no other latency differences because all images are moderately difficult, which would extend reaction time and ultimately interfere with accuracy due to the time constraints on response time. We removed the missed trials for each condition, which was 27.5% of trials in each condition (there was no significant difference in missed trials for any image type (*p* = 0.685), which suggests the task was equally difficult for all stimuli. Previous studies in our lab involving affordance have shown effects of action encoding in the latency domain but not in the accuracy domain (Borghi et al., 2012). Whether increasing the time constraint on response interval or reducing the difficulty of action images would alter latency effects is an issue to be investigated in future research.

#### **ALTERNATIVE EXPLANATIONS**

There is other existing evidence that would suggest it is possible that right and left-handed subjects have different strategies when it comes to interpreting action. Ni Choisdealbha et al. (2011) suggested that right-handed subjects rely primarily on sensorimotor mental rotation. On the other hand, left-handed subjects could depend initially on visual analysis and/or pictorial strategies followed by a mental rotation strategy.

Work has also been done to evaluate patients with frontal lesions on similar tasks (Chiavarino et al., 2007). The patients were asked to imitate mirror-matched or limb-matched stimulus. They discovered that patients had a selective deficit for imitating limbmatched responses which suggests that executive function of the frontal lobes drives the system to visually rotate the frame of reference in order for them to imitate the stimulus. They suggest that the imitation capacity was damaged for these particular patients. If this theory is true, then in our healthy population, left and righthanded subjects would have had a similar deficit when judging allocentric images. Although this is a valid explanation, we believe it is unlikely due to higher order executive function, but rather differences in the motor system. A limitation of their study was that they did not separate the patients into left and right sided brain lesion groups and they also had diverse locations where the lesions were located within the frontal lobe. Apraxia in left-handed patients with left or right hemisphere damage has been evaluated in a recent study by Goldenberg (2013). He found that in lefthanded patients, apraxia can occur as a result of damage to either the left or right hemisphere. Apraxia after left hemispheric damage (dissociating from manual dominance) may be explained as result of damage to the praxis relevant networks which remain in the left hemisphere. However, apraxia after right hemispheric damage could be explained as result of damage to a unique co-localization of praxis skills and spatial processing within the right hemisphere. Such findings could argue for a stronger bilateral organization of praxis control in left handed compared to right handed subjects.

#### **LIMITATIONS**

A limitation of the current study is that it is difficult to recruit left-handed subjects that are extremely left hand dominant. Most tools are designed for right-handed people, thus left-handers acclimate and become slightly more ambidextrous for some skilled unimanual tasks. This effect could confound the interpretation of potential hemispheric dissociations, as strength of left-handedness has been shown to augment the strength of right hemispheric laterality (Cabinio et al., 2010). Ambidextrous subjects were excluded from the present study, but left-handed subjects had a lower overall hand dominance score when compared to the right-handed subjects on the Edinburg Handedness Inventory scale. Each individual subjects score was, according to the Edinburg Handedness Scale, beyond the ambidextrous range.

Another limitation is although we were not seeking to understand the learning of new tools, a new tool was incorporated into the study in order to obtain selection of tools that had the same action of "screwing." Our study utilized direct training for all tools presented and there was no effect of accuracy for novel versus familiar tool observed. There was an effect on latency, with novel tools overall having an increased latency compared to that of familiar tools. We did not expect to see a difference behaviorally between tool types due to previous work indicating neural networks were the same; however, the addition of a neural study would be able to confirm this.

#### **CONCLUSION**

The current findings provide insight into how action-goals are encoded and interpreted by left and right-handed subjects. We have demonstrated that encoding of action of left and right-handed actors is not necessarily differentially encoded in left or right-handed subjects in a way that would demonstrate behavioral differences. We have shown there is a benefit in representation of actions encoded in the egocentric perspective. While the ideomotor theory can explain much of why this occurs, it is still unclear as to why left-handed subjects viewing allocentric action showed the pronounced deficit from other combinations of handedness and perspective. Future research may determine the specific neural mechanisms that drive these results by collecting neurophysiological data focusing on motor lateralization effects, which is currently underway.

### **REFERENCES**

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Bekkering, H., Wohlschlager, A., and Gattis, M. (2000). Imitation of gestures in children is goal-directed. *Q. J. Exp. Psychol. A* 53, 153–164.

Bohlhalter, S., Hattori, N., Wheaton, L., Fridman, E., Shamim, E. A., Garraux, G., et al. (2009). Gesture subtype-dependent left lateralization of praxis planning: an event-related fMRI study. *Cereb. Cortex* 19, 1256–1262. doi: 10.1093/cercor/bhn168

**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.

*Received: 03 October 2013; accepted: 05 December 2013; published online: 19 December 2013.*

*Citation: Kelly RL and Wheaton LA (2013) Differential mechanisms of action understanding in left and right-handed subjects: the role of perspective and handedness. Front. Psychol. 4:957. doi: 10.3389/fpsyg.2013.00957*

*This article was submitted to Cognition, a section of the journal Frontiers in Psychology. Copyright © 2013 Kelly and Wheaton. 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) or licensor 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.*

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# The embodied mind extended: using words as social tools

# *Anna M. Borghi 1,2\*, Claudia Scorolli 1, Daniele Caligiore2, Gianluca Baldassarre2 and Luca Tummolini 2*

*1 EMbodied COgnition Lab, Department of Psychology, University of Bologna, Bologna, Italy*

*2 Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy*

#### *Edited by:*

*François Osiurak, Laboratoire d'Etude des Mécanismes Cognitifs (EMC EA 3082), France*

#### *Reviewed by:*

*Martin H. Fischer, University of Potsdam, Germany Frank Garcea, University of Rochester, USA*

#### *\*Correspondence:*

*Anna M. Borghi, EMbodied COgnition Lab, Department of Psychology, University of Bologna, Viale Berti Pichat, 5, 40127 Bologna, Italy. e-mail<EMAIL_ADDRESS>
The extended mind view and the embodied-grounded view of cognition and language are typically considered as rather independent perspectives. In this paper we propose a possible integration of the two views and support it proposing the idea of "Words As social Tools" (WAT). In this respect, we will propose that words, also due to their social and public character, can be conceived as quasi-external devices that extend our cognition. Moreover, words function like tools in that they enlarge the bodily space of action thus modifying our sense of body. To support our proposal, we review the relevant literature on tool-use and on words as tools and report recent evidence indicating that word use leads to an extension of space close to the body. In addition, we outline a model of the neural processes that may underpin bodily space extension via word use and may reflect possible effects on cognition of the use of words as external means. We also discuss how reconciling the two perspectives can help to overcome the limitations they encounter if considered independently.

**Keywords: embodied cognition, extended cognition, tool-use, words as tools, language comprehension, social cognition, body schema, incorporation**

# **INTRODUCTION**

The embodied-grounded (EG) view and the extended mind (EM) view of cognition and language are typically considered as rather independent perspectives. Aim of this paper is to show how the two views can be integrated considering the case of words in their relationship with the bodily space. Specifically, we will propose that words are a very peculiar kind of tool.

According to embodied views of cognition, cognitive processes are constrained by our body, that is, human-like cognition cannot occur independently of a human-like body. In the embodied view, cognition is not for knowing; rather, "cognition is for action" (Wilson, 2002). Proponents of grounded views make a similar argument but posit that the involvement of the body is not exhaustive of cognition, which is grounded in many ways (Barsalou, 2008). In fact, while initially the label "embodied" was used in a more comprehensive way, in the recent literature a slight distinction between embodied and grounded approaches, and between the terms "embodied" and "grounded," is emerging (see Pezzulo et al., 2011; Fischer, 2012; Myachykov et al., in press). According to this view cognition can be grounded in multiple ways. These include not only bodily states, but also situations, actions, etc. (Barsalou, 2008; Pezzulo et al., 2011). In the following, we will use the term embodied and grounded cognition (EG) to refer to both approaches, since the distinction is not relevant for the proposal we will advance.

When it comes to language processing, EG views argue that language is grounded in perception and action systems (for reviews: Willems and Hagoort, 2007; Fischer and Zwaan, 2008; Gallese, 2008; Toni et al., 2008; Jirak et al., 2010; Borghi and Pecher, 2011, 2012; Glenberg and Gallese, 2012). Comprehending language would imply activating a simulation, consisting in a re-enactment of the previous interaction with objects, situations, etc., to which linguistic expressions refer.

In the last years another perspective on cognition, the EM view, is gaining credit, in particular in philosophy. The underlying idea, initially promoted by Clark and Chalmers (1998), is that the human mind is not wholly in our head/brain, but it is rather distributed in our brain, body, and external devices. These external devices (e.g., computers) have the power to complement and augment our internal cognitive processes (see Wilson, 2010).

In this paper, we will first discuss some general limitations of EG and EM views, then address some more specific limits of these views in understanding the role of language. We will then suggest that words can be understood as social tools, and explain why, in our opinion, this approach helps to reconcile EG and EM views of cognition and to overcome their limitations. Finally, we will discuss experimental evidence to support the Words as social Tools (WAT) proposal and we will outline a computational model to specify the neural mechanisms that might underlie the aforementioned processes.

# **EMBODIED-GROUNDED AND EXTENDED VIEWS**

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Even though we favor an EG approach to cognition, we hold that EG theories have some problems (for critiques to aspects of the embodied approach, see Borghi and Cimatti, 2009, 2010; Chatterjee, 2010; van Elk et al., 2010; Wilson and Golonka, 2013). We will consider first some problems characterizing the EG approach in general, and then we will focus on the limitations of the EG approach to language, in particular to language comprehension. We will focus on content issues and not on methodological problems, as for example the problem of the lack of precise and unidirectional predictions, which in our opinion can be solved with a more extensive use of computational models (see for discussions on this problem Borghi et al., 2010; Chersi et al., 2010; Willems and Franken, 2012). Notice that our critiques might not

necessarily concern all versions of EG views, which are sometimes rather different (see Goldman and de Vignemont, 2009, for an analysis of this). One major problem of EG views is the high risk of adopting the view that Clark (2008) has called "brainbound." In this view, human cognition directly depends on neural activity, with the mind being modeled as inner and neurally realized. This position does not accept the idea that cognition might be distributed and extended beyond bodily borders. The brainbound view is not convincing for a simple reason, as explained by Noe (2009): "the subject of experience is not a bit of your body.  The brain, rather, is part of what you are" (pp. 7). In our opinion many versions of the EG view are too brainbound: they emphasize too much the role of the brain with respect to the body. This might seem paradoxical for an embodied approach: obviously no embodied view does fully neglect the importance of the body, but many EG approaches ascribe a too relevant role to the brain compared to the whole body, at the same time neglecting the possible role of body extensions. Similar critiques are expressed by Wilson and Golonka (2013) who claim: "The major problem with this research is that it again assumes all the hard work is done in the head, with perception and action merely tweaking the result." (Wilson and Golonka, 2013, p. 11). van Elk et al. (2010) further deepen this point, arguing that in cognitive neuroscience embodied approaches are still cognitivist. We report their own words: "In cognitive neuroscience the notion that concepts are embodied primarily means that there is a correspondence between the brain activations associated with processing the referent of a concept and the processing of the concept itself. For instance, seeing a car and thinking or reading about a car involves the activation in comparable visual areas. Thus, the dispute between modal and amodal theories of language comprehension is basically a discussion about the representational vehicle of concepts (i.e., whether the representational vehicle of concepts is shared with neural resources used for perception and action). Both modal and amodal theories of language thus share a cognitivist notion of cognition in terms of discrete internal representations of the world" (van Elk et al., 2010, p. 3).

The second problem with many EG theories is that they do not sufficiently consider and emphasize the fact that the sense of body might be plastically rearranged. Body boundaries are treated as rather static while some studies have revealed that they are flexible and can be modified, for example through the use of tools, changing with our sense of body (see for example the special issue on the sense of body by Tessari et al., 2010). We will further address this problem in the rest of the paper.

When they deal with language, one major limit of EG views is that language is mainly conceived in its referential aspects. This way of conceiving language relies on the classical notion that knowing the meaning of a word is knowing what it refers to. Accordingly, the meaning of a word like "hammer" consists in the re-enactment of past multimodal experiences with the word referent, i.e. hammers. For example, according to the indexical theory (Glenberg and Robertson, 2000) words would index their referents in the world, which would be represented in terms of perceptual symbols (Barsalou, 1999). This referential view of language has a number of merits. First, it provided the instruments to contrast the propositional view, which was dominant in psychology and cognitive sciences (see Lakoff, 2012, for a description of the times before the idea of embodied cognition). In this view concepts and word meanings were seen as the product of a transduction process from sensorimotor to abstract knowledge. Knowledge would be represented in terms of amodal symbols only arbitrarily related to their referents, organized through syntactic combinatorial rules (e.g., Fodor, 1975; Pylyshyn, 1984). More recent non-embodied views posit that word meaning is a consequence of the statistical distribution of words in language (for an influential version, see Landauer and Dumais, 1997). However, today the necessity to contrast the statistical and the embodied view is not so critical, and conciliatory approaches have been proposed (see for example Andrews et al., in press).

Second, the influential research program based on these premises has inspired many studies, which have led to important and sophisticated experimental results (for reviews see Barsalou, 2008; Fischer and Zwaan, 2008; Gallese, 2008; Toni et al., 2008; Jirak et al., 2010; Borghi and Pecher, 2011, 2012). However, an embodied referential view is probably not sufficient to provide a thorough account of word meaning.

While in psychology and cognitive science the propositional view has dominated for a long time and the referential view was introduced by EG theorists as an alternative to it, in philosophy the referential view of language has been widely criticized since at least the seminal work of Wittgenstein (1953; see Noe, 2009 for a contemporary statement): the most widespread view in philosophy holds that, for example, we can speak about fawns even if we have never seen them since we can rely on the expertise of our community. Words are compositional and we can access the meaning of words of which we do not know or cannot see the referent thanks to the expertise of other members of our community. As Noe (2009) nicely argues, "meaning depends on the practice" (p. 90), and being able to use words corresponds to knowing what they mean.

Curiously, while philosophical examinations have gravitated toward treating the practical nature of meaning, the referential view is still the predominant one in EG cognition theories. This has probably been due to the desire, on the part of EG proponents, to contrast the traditional propositional view, according to which words are arbitrarily linked to their referents. EG proponents have assumed that it was necessary to demonstrate that words are grounded, as their referents activate perception and motor systems.

Beyond the limit of the focus on referentiality, in our view the EG view of language has two further limitations given that it has neglected two other important aspects of words. The first concerns the social and public nature of words, the second the fact that words can be instruments for action. Words are social and public because, since they are a heritage of our speakers' community, to be effective they require someone else's presence, implicit or not. Indeed, speaking implies performing complementary actions in coordination with someone else (Clark, 1996). Words can be instruments for action since their use allows humans to modify the current state of the world, as it happens during tool-use. This point will be further developed in the course of the paper.

If EG approaches often tacitly assume a brainbound view of cognition, the most vigorous attack to this view derives from the

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idea that cognition is not limited to the boundaries of body/skull but is extended. In other words, "minds like ours emerge from this colorful flux as surprisingly seamless wholes: adaptively potent mashups extruded from a dizzying motley of heterogeneous elements and processes" (Clark, 2008, p. 219). According to the EM view, tools complement our mental abilities: for example, a diary complements our memory. As a consequence of this relationship between brain-body system and external tools, our mind would be distributed (Hutchins, 1995) across a variety of bodily parts and non-bodily devices (Clark, 2003; Thompson and Stapleton, 2009). One potential limitation of EM views, and possibly one of the reasons why they have encountered resistance, is their appeal to functionalism (Kiverstein and Clark, 2009) which might conflict with the assumptions of an embodied view of cognition (but see Clark, 2008, for a different position, which does not put the two approaches in contrast).

The EM approach holds a peculiar view of the relation between words and cognition. Words themselves are considered as external devices and as cognitive tools capable of augmenting our computational abilities (Clark, 1998). This view (e.g., Clark, 1998) has its roots in the seminal work of Vygotsky (1962) who underlined the role played by inner language and its scaffolding function supporting actions. However, in our opinion, one of the most interesting aspects of Vygotsky's notion of inner language is that it involves the internalization of a phenomenon which is initially (and inherently) social and public and which augments our computational abilities. Such a social and public component is, however, underappreciated in the EM approach, which instead underlines the importance of language for developing thought and computational abilities.

Here we propose that EG and EM views can, and should, be integrated. Such integration will overcome their respective limitations when dealing with language: the limited focus of the EG view on the referential aspect of words and the neglect of the social dimension of words in the EM view.

# **THE INCORPORATION OF PHYSICAL TOOLS**

Even if it does not pertain to language, one line of research that may suggest how EG and EM views can be reconciled comes from recent work on the recoding of bodily space after tool-use. Below we will briefly review the behavioral, neural and computational literature on this topic and will then try to highlight why it is relevant for us.

Since Iriki's seminal work with monkeys (e.g., Iriki et al., 1996), neuroscientific studies with humans have revealed that active tooluse can change the representation of space, in particular inducing an extension of the near space (Berlucchi and Aglioti, 1997; Berti and Frassinetti, 2000; Maravita and Iriki, 2004; Farnè et al., 2005; Osiurak et al., 2012).

The neural mechanisms underlying the extension of body representation caused by the use of a tool have not yet been identified (Magosso et al., 2010; Stout and Chaminade, 2012). Recently, some attempts mainly using computational modeling approaches have been proposed with the aim of identifying such mechanisms. Each proposed model sheds light on some important aspect underlying the phenomena. Ursino et al. (2007) and Magosso et al. (2010), for example, point out the involvement of visual-tactile cortical

regions serving the representation of action affordances and action outcomes (including the parietal cortex, PC, and the pre-motor cortex, PMC) and Hebbian associative mechanisms to shape the body representation after using a tool. In particular, Ursino et al. (2007) claim that the enlargement of the peripersonal space after tool-use depends on an expansion of the visual receptive field of parietal bimodal neurons due to a strengthening of visual synapses through Hebbian mechanisms. In the same line the model proposed by Magosso et al. (2010) shows how different tool-use tasks lead to different re-sizing effects of the peri-hand space. The model also predicts that, after tool-use, a far visual stimulus acts as a near one, independently of whether the tool is present or absent in the subject's hand. The authors validate this prediction by an *in-vivo* experiment. Other models focus on the role of sub-cortical areas (such as the cerebellum, see Arbib et al., 2009, and Imamizu and Kawato, 2012) in learning and storing internal models of body and environment after the use of a tool. Other ones suggest that memory processes are responsible for the dynamical aspects of tool-use during tool-body assimilation (Nabeshima et al., 2007; Nishide et al., 2009).

An open issue in the literature on bodily extension concerns whether the characteristic recoding of spatial perception also determines a change the body schema. We will briefly focus on this discussion since it is important for our view of language. One interesting distinction is between bodily extension determined by successful tool-use and incorporation following successful prosthesis-use. According to De Preester and Tsakiris (2009), tool-use does not determine changes in the sense of bodyownership, but only in motor and perceptual capacities (Botvinick, 2004). A crucial difference is the experience of completion: a noncorporeal object can be incorporated if it replaces something that originally was present, and now is missing. If the object cannot be assimilated to the pre-existing body-model (Tsakiris, 2010), true incorporation cannot occur. Beyond incorporation and use, there might be different degrees of relationship between ourselves and the objects. Some objects are perceived as external, while other objects provoke effects in our own sense of body. However, even objects perceived as completely external evoke motor responses (affordances), if they are close enough to our own body (Costantini et al., 2011b; Ambrosini et al., 2012; for a comprehensive review on affordances see Thill et al., 2013).

The same distinction between incorporation and use can also be applied to language. The question we will address in the following pages was initially proposed by Clark (2008, p. 39) in the following formulation: "Could anything like this notion of incorporation (rather than mere use)... get a grip in the more ethereal domain of mind and cognition?" We will show how the notion of incorporation can be applied to the"ethereal" domain of language. Here words, and in particular their public and social dimensions, come into play.

# **WORDS AS SOCIAL TOOLS: THE CASE OF SPACE**

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The idea that words can be conceived as tools is not completely new. Beyond Wittgenstein (1953), it has been proposed by a number of authors (Clark, 1998; Borghi and Cimatti, 2009, 2010, 2012; Mirolli and Parisi, 2009, 2011; Tylèn et al., 2010). However, different aspects of this idea have been stressed.

In *Philosophical Researches*,Wittgenstein (1953) highlighted the fact that words can have different and multiple functions, as tools in a toolbox. Clark (1998) spoke of the "magic" of words: words are external artefacts endowed with the power to augment and complement our computational abilities. According to him, while emphasis has been put on the communicative aspects of language, its computational role has been neglected, with the possible exception of Vygotsky who has underlined the role played by inner language and scaffolding to direct our actions.

The view we will present is slightly different. We agree that the computational role of inner language, intended as a guide for action, has not been considered enough. However, we intend to stress the role of other aspects of words that, despite the novel burst of interest for social neuroscience, have been neglected: the social and public role words possess. In order to be effective, words do not only need to refer correctly to objects or situations in the world. Language is also a powerful instrument for joint action. Words are tools, as they allow for the mental manipulation of information (Malt and Wolff, 2010). This in an individual and private use, as some authors have underlined. However, words have a peculiarity: to manipulate inner information we take advantage of a device that is social and public in its nature. For this reason we claim that words are "social tools." Specifically, in this paper we will consider a special case of similarity between words as social tools and physical tools, concerning the relationship between space and body.

Words and physical tools share an important feature: both can be used to accomplish goals via external means, respectively, other people and objects, resulting in a change of the current state of the world (Glenberg and Gallese, 2012) and in an extension of our capabilities. Consider the case of words as tools that can be used to reach for something. We can reach objects with a physical tool (e.g., a rake), but also by asking somebody to bring them to us. Thus, in certain contexts the same goal can be reached either through tools, or through words. In some cases, words are even more powerful than tools. For example, they might allow us to reach very distant objects.

However, words work as tools only under the condition that other people collaborate. Even if our proposal is in debt with the pragmatics literature (e.g., Levinson, 1983) and with Austin (1962)'s idea that we do things with words, here we intend to make a distinction between advancing a request for an object and performing an action with a tool. These two activities share many similarities, but are also clearly different. An action with an instrument can be planned but fail, for example due to problems of the instrument, etc. Similarly, a request can be disattended, either because of problems in its formulation, or due to disruptions in communication, or scarce compliance on the side of the addressee. But people can decide to use tools to reach a goal on their own, without the presence of other individuals. This is not possible with words. The referent of a word can be found, but if other individuals do not provide a support, i.e., if the social dimension implied in word use is absent, the request will not succeed. Thus words are a peculiar kind of instrument: they work effectively only if other people are available and respond positively to our implicit or explicit request. What counts is the dynamic interaction they are able to promote (see Cooke et al., 2013, on team cognition). When

performing activities which require coordination, such as lifting very heavy objects, we need to possess the sophisticated ability to understand others' action plans, others' willingness to collaborate, etc. (Marsh et al., 2009). Similarly, this ability should be present during language use as well, otherwise words, even if referentially correct, are not effective. In this respect, words constitute a bridge between ourselves, the environment and the others.

Here we propose that words and tools share a further similarity: we consider the possibility that when we use words to reach for something, word use expands the near space, modifying the representation of the relationship between our own body and the objects in space, similarly to what happens after tool use. The argument behind this hypothesis is the following: if words are similar to tools, then their use should lead to an extension of the bodily space, as it happens with real tools.

One could object that words and tools are substantially different, since tools are physical things in the world that we use with our bodies while words are not. We understand the objection, but the perspective we endorse is radically different: according to WAT (e.g., Borghi and Cimatti, 2009, 2012) not only tools but words as well can be considered as physical things. They are expressed through our bodies, be they spoken or written, and once pronounced or written they have a material and public existence, similarly to tools (Wittgenstein, 1953; Clark, 1998).

Now consider the relationship between words and body according to EG theories and the relationship between words and mind according to the EM view. EG theorists demonstrated that comprehending words activates the motor system. EM theorists propose that, as tools extend our body schema, "language extends our capacities for thought and therefore can be treated as extending our mind schema" (Noe, 2009). In fact, it has been shown that language modifies cognition, for example influencing perception and categorization (Wolff and Malt, 2010), in a flexible manner (Lupyan, 2012). But so far nobody has shown that word use might recode our bodily space with respect to objects, as it happens for physical tools. Notice that the parallel between words and tools is not only abstract and metaphorical; in contrast, we formulate the precise prediction, to be tested experimentally, that both words and physical tools have a specific effect on cognition, i.e., that their use determines an expansion of the bodily space representations. Demonstrating this would imply to apply the notion of incorporation to the "ethereal" domain of language. At the same time, it could help reconcile the EG and the EM view.

# **WORDS AS SOCIAL TOOLS AND SPACE: EXPERIMENTAL EVIDENCE AND A MODEL EXPERIMENTAL EVIDENCE**

Recent experimental evidence supports the idea that words can be considered as tools that extend the bodily space.

Scorolli et al. (2011; submitted) and Scorolli and Borghi (2012) demonstrated with a kinematics study that word use modifies spatial perception. Participants, children and adults, observed objects located in the peripersonal, extrapersonal or far and "border" space. For operational reasons we defined"peripersonal," or"near," as the space reachable extending the arm (but see the discussion on the problems of this definition due to the plasticity of the near space made by Longo and Lourenco, 2006; Lourenco and

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Longo, 2009), "extrapersonal," or "far," as the non-reachable space, and "border" as the space reachable extending the arm and the back. Before and after training, subjects were asked to produce explicit verbal estimations on objects' distances, or to throw a toy-car toward objects' locations. During the training phase participants had to reach and grasp the "right" object and to put it in a box provided by different shaped holes. If the right object was too far, they could use a tool (a rake), press a button or use a linguistic label, pronouncing the object noun; all instruments were effective in reaching the goal. We introduced the button since we were interested in comparing the rake and the button, i.e., two instruments that, differently from words, do not imply a social context to be used. While participants hold the rake in their hands, the button has an arbitrary relation to the object, similarly to a word: once pressed, the object appears. In the last years, few studies have shown that even arbitrary relationships with a target can modify the perception of peripersonal space. Davoli et al. (2012) have shown that remote interactions with a target, for example illuminating the target object with a laser pointer, caused an extension of the perceived space. In the same vein, Bassolino et al. (2010) demonstrated that frequent use of a computer mouse determined a spatial extension. The difference between a button, i.e., a device that is arbitrary linked to the object to be reached, and a word is that the last one implies a social dimension.

The results of the study revealed that after training, even if the verbal estimations changed slightly, the car was thrown significantly closer than before the training. This indicated an extension of the reachable space, not modulated by the instrument kind.

As other studies on extended body, this work suggests that the distinction between near and far space is plastic and flexible. However, here the extension was brought about not only by physical tools but by immaterial ones as well, i.e. by words. The social dimension implicit in words made this possible: pronouncing an object name implies evoking somebody else performing a complementary action, helping us reach a distant object. Thus words, like tools, help us act in the world and influence our way of representing bodily space with respect to objects (Gianelli et al., 2013). However, with words, our operational space becomes larger because of the presence of others. Even if we propose that the social dimension is intrinsic in word use *per se*, we predict that the results will be stronger, i.e. the spatial extension with words will be more marked, in presence of another person. In particular, this extension should be particularly marked if the other person is close to the object, is looking directly at the participant and demonstrates through gestures and posture to be open to the interaction (see Innocenti et al., 2012; Scorolli et al., 2012). We predict, instead, that if the other person is not close to the object, and the body posture and the facial expression of the other are not expressing compliance, the effects of words will be reduced, given that the request is less likely to be attended. In sum, Scorolli et al. (2011; submitted) have shown that words alone are effective in modifying the bodily space. However, we predict that their effect will be more marked in a context in which the social dimension is emphasized, thanks to the real presence of another person.

These results are complementary with those obtained by Costantini et al. (2011b). Previous evidence demonstrated that objects afford actions only when presented in the peripersonal

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space e.g., Costantini et al. (2011a). The novelty of the study by Costantini et al. (2011b) consisted in showing that when the object was outside subject's reaching space but within an avatar's reaching space, it evoked affordances as well. According to the authors, this indicates that an interpersonal body representation is formed in which one's own arm reaching space is mapped with that of others'. Notice that an avatar might evoke the presence of another person, but the effects it produces might not be as strong as those elicited by the presence of a real other.

However, these findings together with those by Scorolli et al. (2011; submitted) and Scorolli and Borghi (2012), in which words refer only implicitly to the presence of another person, suggest that the subject's representation of reaching space is actually extended. Importantly, in the study by Scorolli et al. (2011; submitted) the other person plays a complementary role as he/she is implicitly evoked to perform an action one cannot perform alone (Newman-Norlund et al., 2007).

In sum: it has been suggested that active tool-use determines a progressive incorporation of the tool within the body schema (Iriki et al., 1996; Povinelli et al., 2010). The analogous extension of the operational space found after the rake, the button and the word use suggests that the reaching space extension is not due to the possibility of the tool to be integrated into the body schema, but to the goal-directed character of the action (Hommel et al., 2001; Massen and Prinz, 2009). However, some issues remain open.

The studies discussed so far indicate that words, similarly to real tools, determine a plastic modification of the reaching space, even if they cannot be integrated into the body schema as tools do. However, the evidence we reported concerns concrete words, and specifically words with specific referents endowed with a precise spatial location. One could ask whether the claim that words are tools can be generalized, i.e., whether other kinds of words can determine variations in the bodily space. Even if we are not aware of any evidence, we can speculate that even words like "the" or like "freedom," which do not have a specific concrete counterpart, can expand our near space (for work on mapping between demonstratives such as "this" and "that" and near and far space, see Coventry et al., 2008, 2012; Bonfiglioli et al., 2009). As we say something to somebody else through words we somehow create a novel, shared space. This should happen with each word, as each word is pronounced to be heard by somebody else. However, while we reported evidence showing that concrete words expand the peripersonal space, the possibility that this is true for other kinds of words is currently a speculation, and further research is needed in order to demonstrate it.

A further question one could raise is the following: do intransitive gestures as well induce an extension of the near space, similarly to tools? Indeed, for communicative gestures to succeed, we need that others are available and ready to collaborate, as it happens with words. Compared to gestures, however, words have a number of advantages: (a) they are typically more specific than gestures (e.g., I can point to an object I would like to receive, but the context might not help you to identify the precise object: this potential problem can be easily solved using the appropriate word); (b) they are arbitrarily related to their referents, and this allows more freedom of action; (c) also thanks to b, they are less tightly anchored

to a specific context and situation. Normally gestures coexist with words, even if they can have a separate meaning (McNeill, 2000; Kendon, 2004). Furthermore, it has been shown that gestures do not develop imitating others, but emerge in an autonomous way and are integrated in speech, probably because they facilitate thinking (Bates, 1976; Capirci et al., 1996; Iverson and Goldin-Meadow, 1998). On this basis we can advance the prediction that combinations of gestures and words would increase the effect with respect to words alone. As to the sign language, where gestures directly substitute words, we predict a similar effect as the one obtained with words. But consider the case in which gestures are not coupled with words but used as substitutes for them. In this case our predictions are not so straightforward, and further research is needed to investigate this important issue (for relevant work, see De Stefani et al., under review).

### **TOWARD A COMPUTATIONAL MODEL OF WORDS AS SOCIAL TOOLS**

Although the models reviewed in the Section "The incorporation of physical tools"give important insights on the brain mechanisms underlying the adaptation of body representation after using a tool, they do not deal with the question of the possible neural mechanisms underlying the processes of words as tools. To address this problem, it is crucial to consider three key aspects not yet considered by previous models: (a) the brain has a hierarchically (soft)modular organization (Meunier et al., 2010; Houk, 2011; b) such organization pivots on anticipatory/goal-based representations of actions at multiple levels (Hamilton and Grafton, 2008; c) words are grounded on the same (or contiguous) neural representations sub-serving action (for reviews, see Martin, 2007; Jirak et al., 2010).

A bio-inspired neural architecture based on these points is sketched in **Figure 1**. The overall model architecture is built on the model of Caligiore et al. (2010), capturing important aspects of hierarchical brain organization. Even if the model proposed here is not computationally implemented, the discussion of its design features allows us to unveil important aspects overlooked by current models on tool-body assimilation. These aspects could be important to investigate the neural mechanisms underlying the notion of words as social tools.