Planning a sequence of two motor elements is much more than concatenating two independent movements. However, very little is known about the cognitive strategies that are used to perform fluent sequences for intentional object manipulation. In this series of studies, the participants' task was to reach for and pick to place a wooden cylinder to set it on a place pad of three different diameters, which served to modify terminal accuracy constraints. Participants were required to perform the sequences (1) at their preferred speed or (2) as fast as possible. Action kinematics were recorded with the Qualisys motion-capture system in order to implement a real-time protocol to get participants to engage in a true interactive relation. Results revealed that with low internal constraints (at preferred speed), low coupling between the two elements of the motor sequence was observed, suggesting a step-by-step planning strategy. Under high constraints (at fastest speed), an important terminal accuracy effect back propagated to modify early kinematic parameters of the first element, suggesting strong coupling of the parameters in an encapsulated planning strategy. In Studies 2 and 3, we further manipulated instructions and timing constraints to confirm the importance of time and predictability of external information for coupled planning. These findings overall sustain the hypothesis that coupled planning can take place in a pick and place task when anticipatory strategies are possible. This mode of action planning may be the key reason why motor intention can be read through the observation of micro variations in body kinematics.

The understanding of concepts related to objects are developed over a long period of time in infancy. This paper investigates how physical constraints and changes in visual perception impact on both sensorimotor development for gaze control, as well as the perception of features of interesting regions in the scene. Through a progressive series of developmental stages, simulating ten months of infant development, this paper examines feature perception toward recognition of localized regions in the environment. Results of two experiments, conducted using the iCub humanoid robot, indicate that by following the proposed approach a cognitive agent is capable of scaffolding sensorimotor experiences to allow gradual exploration of the surroundings and local region recognition, in terms of low-level feature similarities. In addition, this paper reports the emergence of vision-related phenomena that match human behaviors found in the developmental psychology literature.

In humans, repeated exposure to the effects of events can lead to anticipation of these effects. This behaviour has been observed in infants from as young as 3months old. During infant experiments, the infants have been observed to predict either by pre-saccadic movements or reach actions according to the expected future outcome of the event. Event anticipation or prediction is necessary for such behaviours. In this paper we demonstrate prediction of object motion events using the adaptive learning tool Dev-PSchema. Results shows that the system is able to predict the linear motion outcome of the visual event using generalised schemas.

We present here a toolbox for the real-time motion capture of biological movements that runs in the cross-platform MATLAB environment (The MathWorks, Inc., Natick, MA). It provides instantaneous processing of the 3-D movement coordinates of up to 20 markers at a single instant. Available functions include (1) the setting of reference positions, areas, and trajectories of interest; (2) recording of the 3-D coordinates for each marker over the trial duration; and (3) the detection of events to use as triggers for external reinforcers (e.g., lights, sounds, or odors). Through fast online communication between the hardware controller and RTMocap, automatic trial selection is possible by means of either a preset or an adaptive criterion. Rapid preprocessing of signals is also provided, which includes artifact rejection, filtering, spline interpolation, and averaging. A key example is detailed, and three typical variations are developed (1) to provide a clear understanding of the importance of real-time control for 3-D motion in cognitive sciences and (2) to present users with simple lines of code that can be used as starting points for customizing experiments using the simple MATLAB syntax. RTMocap is freely available (http://sites.google.com/site/RTMocap/) under the GNU public license for noncommercial use and open-source development, together with sample data and extensive documentation.

During infancy, infants spend a lot of time visually exploring the scene around them. Over the first year of life, the level of detail that can be perceived visually increases significantly. In this study, the ability to perceive areas of interest w.r.t. human developmental change in vision, specifically acuity and field of view over the first year of life, is investigated. Two scenarios, namely learning through a series of developmental changes and learning without any constraints, shed light on how a humanoid robot scaffolds learning of interesting areas in the scene through different emergent exploratory behaviours. Divergence/convergence in features is reported, demonstrating a potential to be used at a higher level of understanding. Staged strategies with early sensory constraints and exploratory behaviour based on "similarity searches" improve the quality of acquired features and may be used as a mechanism for better on-line learning of objects knowledge.

AIMS The aim of the study was to compare emotional information processing in patients with severe alcohol use disorder in short-term abstinence (<1 month) and long-term abstinence (at least 6 months to 9 years) with control participants. METHODS We studied the variation in pupil diameter during the presentation of pictures of human interactions associated with positive, negative or neutral valences. RESULTS Overall, the results of the short-term abstinent group revealed greater pupil dilation regardless of the valence of the pictures while the pupillary response of long-term abstainers did not differ from the control group. More specifically, according to each valence, the pupil response to neutral pictures was greater for both patient groups than for controls. For the long-term abstainers, a negative correlation was found between the length of abstinence and the pupillary response to emotional stimuli. CONCLUSION In long-term abstainers group, the high activation by neutral stimuli suggests however some difficulties in the processing of nonemotional stimuli, considered emotional ones and may constitute a potential relapse factor or the maintenance of addiction.

Psychologists report that infants rely on shape rather than colour for object recognition, differentiation and generalisation for both verbal and non-verbal tasks. In this paper we propose a mechanism for object generalisation, based on inductive inference and differentiation using visual along with non-visual information obtained through the manipulation of various objects. Experiments are conducted using a simple simulator to show the dependence of the generalisation on shape versus on colour. Results show that the mechanism creates complete generalisations for objects of different shapes and partial generalisation for objects of the same shape.

As social animals, it is crucial to understand others’ intention. But is it possible to detect social intention in two actions that have the exact same motor goal? In the present study, we presented participants with video clips of an individual reaching for and grasping an object to either use it (personal trial) or to give his partner the opportunity to use it (social trial). In Experiment 1, the ability of naïve participants to classify correctly social trials through simple observation of short video clips was tested. In addition, detection levels were analyzed as a function of individual scores in psychological questionnaires of motor imagery, visual imagery, and social cognition. Results revealed that the between-participant heterogeneity in the ability to distinguish social from personal actions was predicted by the social skill abilities. A second experiment was then conducted to assess what predictive mechanism could contribute to the detection of social intention. Video clips were sliced and normalized to control for either the reaction times (RTs) or/and the movement times (MTs) of the grasping action. Tested in a second group of participants, results showed that the detection of social intention relies on the variation of both RT and MT that are implicitly perceived in the grasping action. The ability to use implicitly these motor deviants for action-outcome understanding would be the key to intuitive social interaction.

In 1984, von Hofsten performed a longitudinal study of early reaching in infants between the ages of 1 week and 19 weeks. This paper proposes a possible model using excitation of various subsystems to reproduce the longitudinal study. The model is then implemented and tested on an iCub humanoid robot, and the results compared to the original study. The resulting model shares interesting similarities to the data presented by von Hofsten, in particular a slight dip in the quantity of reaching. However, the dip is shifted along by a few weeks, and the analysis of hand behaviour is inconclusive based on the data recorded.

Optimal control models of biological movements are used to account for those internal variables that constrain voluntary goal-directed actions. They, however, do not take into account external environmental constraints as those associated to social intention. We investigated here the effects of the social context on kinematic characteristics of sequential actions consisting in placing an object on an initial pad (preparatory action) before reaching and grasping as fast as possible the object to move it to another location (main action). Reach-to-grasp actions were performed either in an isolated condition or in the presence of a partner (audience effect), located in the near or far space (effect of shared reachable space), and who could intervene on the object in a systematic fashion (effect of social intention effect) or not (effect of social uncertainty). Results showed an absence of audience effect but nevertheless an influence of the social context both on the main and the preparatory actions. In particular, a "localized" effect of shared reachable space was observed on the main action, which was smoother when performed within the reachable space of the partner. Furthermore, a "global" effect of social uncertainty was observed on both actions with faster and jerkier movements. Finally, social intention affected the preparatory action with higher wrist displacements and slower movements when the object was placed for the partner rather than placed for self-use. Overall, these results demonstrate specific effects of action space, social uncertainty and social intention on the planning of reach-to-grasp actions, in particular on the preparatory action, which was performed with no specific execution constraint. These findings underline the importance of considering the social context in optimal models of action control for human-robot interactions, in particular when focusing on the implementation of motor parameters required to afford intuitive interactions.

Reading Motor Intentions Lewkowicz Daniel (daniel.lewkowicz@etu.univ-lille3.fr) URECA laboratory, Univ Lille Nord de France, F-59000 Lille, France Delevoye-Turrell Yvonne (yvonne.delevoye@univ-lille3.fr) URECA laboratory, Univ Lille Nord de France, F-59000 Lille, France MESHS, USR 3185, F-59000 Lille, France Abstract Some evidence in very recent psychological studies have demonstrated that motor simulation ability is crucial for the correct understanding of social intentions. The present study was conducted first to confirm that the nature of the motor intention leads to early modulations of movement kinematics. Then, we tested whether humans could read an agent’s intention when observing the very first element of a complex action sequence. Results revealed early variations in movement kinematics and further showed that human agents can use these deviants to distinguish above chance level between three different social actions. Similar performance levels were found using an artificial classifier (Neural Network) and this procedure demonstrated furthermore that decisions could be taken on the basis of information contained in the first 500ms of movement kinematics. Taken together these results confirm the importance of motor simulation for adapted social interaction, and suggest how robotic adaptive controllers may use as input low-level motor information (e.g. kinematics) to afford biologically inspired social behaviors. Keywords: Classifier; kinematics; sequences; motor control; intentionality: social interaction; internal models; prediction; motor planning; biological movement. Introduction In everyday activities, the grasping of an object might be performed with different prior intentions: e.g. touch, move, throw or pass. Ansuini et al. (2008) have measured the prior-to-contact grasping kinematics for reach-to-grasp movements performed toward a bottle filled with water. By comparing hand shaping across tasks involving different subsequent actions - pour the water into a container; throw the bottle; move the bottle from one spatial location to another - the authors demonstrated how the prior intention in grasping the object strongly affected the positioning of the fingers during the reaching and the contact phase of the action (Ansuini, Giosa, Turella, Altoe, & Castiello, 2008). In another series of studies, Becchio and collaborators investigated the effects of social context on reach-to-grasp actions. They found initial adjustments reflecting specific planning strategies (Becchio, Sartori, Bulgheroni, & Castiello, 2008a) as well as online adjustments (Sartori, Becchio, Bulgheroni, & Castiello, 2009) when performing under social context (see : Becchio et al., 2010 for a review). More recently, researchers have gone one step further to suggest that not only end-point constraints and social contexts affect movement kinematics, but that these deviants may be used to read motor intention. For example, when observing actions performed under social context or not, Castiello and collaborators demonstrated that humans can successfully use kinematic cues of reach-to-grasp movements to predict the final goal of the action (Sartori, Becchio, & Castiello, 2011). Similar results were also found using point-light displays of simple reach to grasp movements (Manera, Becchio, Cavallo, Sartori, & Castiello, 2011). However, in these studies, the classification rates were obtained under a forced two-choice paradigm, and for the most subtle differences (cooperative vs individual preferred speed or competitive vs fast speed) the classification rates were very small (near 50%). In the present work, we wanted to study the capacity of humans to read motor intention in a sequence of 2 motor elements. One novelty of this study is that the sequences were performed entirely during an interactive situation with a con-specific, without any interruption or verbal instruction between the sequences. As such, we recorded sequential actions during an ecologically inspired task (Jungle Speed), a simple face-to-face game using a unique manipulated object. Our main focus was to compare human and artificial categorization performances for three different sequential actions that took part during the game. To test the hypothesis that kinematics alone is sufficient to read social intention, we fed the artificial classifier with movement kinematics only. Confronting Jacob & Jeannerod’s (2005) reading motor intention hypothesis, we hypothesized that human agents are able to read motor intention through the simple observation of arm kinematics of the first element of a 2-sequence action. This is possible due to the fact that arm kinematics of the reach to grasp movements reveal specific deviants in function of goal intention from an ideal optimized trajectory. Finally, if motor simulation is sufficient, then an artificial neural network should be able to learn from the deviants and predict as well as humans, the motor intention of an observed agent. In the following section, we first describe the methods we used to make the observation videos (Part A), which were then played to human agents (Part B) and used as input parameters to an artificial neural network (Part C). Creating Stimuli Two adults participated in the study, one experimenter and the other as subject. Both participants were right handed

Some evidence in very recent psychological studies have demonstrated that motor simulation ability is crucial for the correct understanding of social intentions. The present study was conducted first to confirm that the nature of the motor intention leads to early modulations of movement kinematics. Then, we tested whether humans could read an agent’s intention when observing the very first element of a complex action sequence. Results revealed early variations in movement kinematics and further showed that human agents can use these deviants to distinguish above chance level between three different social actions. Similar performance levels were found using an artificial classifier (Neural Network) and this procedure demonstrated furthermore that decisions could be taken on the basis of information contained in the first 500ms of movement kinematics. Taken together these results confirm the importance of motor simulation for adapted social interaction, and suggest how robotic adaptive controllers may use as input low-level motor information (e.g. kinematics) to afford biologically inspired social behaviors.

Motor imagery is defined as a dynamic state during which the representation of a given motor act is internally rehearsed without overt motor output. Some evidence in experimental psychology has suggested that imagery ability is crucial for the correct understanding of social intention. The present study was conducted first to confirm that the nature of the motor intention leads to early modulations of movement kinematics. Secondly, we tested whether humans use imagery to read an agent’s intention when observing the very first element of a complex action sequence. Results revealed early variations in movement kinematics between three different social actions and further showed that human agents can use these early deviants to anticipate above chance level the end-result before seeing the second half of the sequence. Response times in the observation task were similar in duration to those measured in the true production task, suggesting the use of motor imagery for trial categorization. Nevertheless, in a third study, the use of an artificial (neural network) classifier demonstrated that classification within the first 500 ms is possible without cognitive imagery processing. Hence, our results suggest that low-level motor indices afford intention reading without need for motor imagery but that human agents may use imaging beyond simulation to create an embodied sense of interactivity.

L'objectif de ma these est de participer a la construction d'un nouveau robot humanoide qui peut realiser des interactions intuitives avec l'humain a travers l'observation et l'imitation. Pour cela, j'ai conduit une serie d'etudes experimentales chez le jeune adulte pour caracteriser les proprietes cinematiques des mouvements du bras realises pendant des interactions motrices et sociales, autant d'elements qui seront les patterns de reference pour le futur robot. En se concentrant sur le comportement non-verbal, nous avons teste comment les contraintes externes et internes (difficulte, predictibilite, temporalite) faconne la cinematique des mouvements du bras et de la main dans une simple action sequentielle de prise et de pose d'un objet (etude 1 et 2). Les resultats revelent des modulations precoces dans la cinematique de la phase d'atteinte et de saisie, en fonction de la taille et de la stabilite du receptacle terminal sur lequel l'objet devait etre place. Ces modulations observees dans le premier element de la sequence sont en contradiction avec les modeles d'optimisation de trajectoire utilises en robotique pour les sequences d'action. Ils suggerent un couplage fort entre les parametres moteurs dans une strategie de planification encapsulee qui retro-propage les contraintes contextuelles sur les elements precoces de la sequence. Pour confirmer ces resultats, une seconde serie d'etude a ete conduite en utilisant des tâches cinematiques et videos pour montrer que les intentions motrices humaines pouvaient etre lues a travers la detection de ces modulations cinematiques precoces. En utilisant un systeme de classification artificiel, nous avons teste si les indices de bas niveau pouvaient permettre une categorisation des essais. Les resultats montrent qu'en absence de capacite cognitive particuliere, le reseau de neurone pouvait categoriser les intentions significativement au-dessus du niveau de la chance en observant les 500 premieres millisecondes de l'action (etude 3). La troisieme partie de mon travail de these s'est tournee vers les mesures en eye-tracking. Nous avons revele ici que la strategie proactive de fixations oculaires utilisee pendant l'observation de l'action etait similaire a celle utilisee pendant son execution (etude 4). De plus, les categorisations correctes d'intentions motrices etaient caracterisees par des saccades plus precises et des fixations plus longues sur l'objet. Les mouvements oculaires sont connus pour jouer un role important dans les interactions sociales. Ainsi, dans une derniere experience (etude 5), nous avons mis en place un jeu competitif en face a face revelant des effets specifiques du contexte social qui modifie la cinematique des mouvements d'atteinte selon le type de situations interactives. Dans le manuscrit de these je propose une discussion qui replace les resultats dans les modeles neuronaux et cognitifs de l'integration sensori-mmotrice. Lorsque c'est le cas, des directions futures sont suggerees a la fois pour les modeles cognitifs de controle moteur et pour le developpement e systemes artificiels neuro-inspires integrant des capacites d'interaction sociale intuitive.