A large variety of everyday actions take place in a social context that needs to be shared by interacting agents. However, current neuroscientific models of interpersonal motor interactions mainly focus on individual motor performance. The goal of the present project is to model the exquisitely interactive nature of social communication based on non-verbal exchange of information via bodily movements. We will investigate motor interactions in real life contexts by recording simultaneously the action kinematics of participants engaged in cooperative tasks (either with a virtual avatar or between two individuals jointly grasping an object) and their brains' electrical activity with a Electroencephalography (EEG) system.
Our experimental choices to couple EEG and kinematics recordings offer a great opportunity to study the dynamics of social neuromarkers at the body and brain level.
This approach may pave the way to new studies on the cortical and cognitive basis of interactive motor behaviors and bidirectional social interaction. We aspire to better seize the social complexity and to give a greater overview of brain-behavior dynamics and generate a better understanding of social interaction in cooperative collaboration. Thus, the proposed research may have fundamental importance at both theoretical and empirical levels.
The capacity to reach and grasp is one the key behaviors that allows humans to change their environment, and it has been largely described both in terms of its kinematic features (Jeannerod, 1981, 1984) and in terms of its neural bases (see Castiello, 2005, for a review). Interestingly, when included in a social context, prehension kinematics could be modulated by the mere presence of a person observing us or more complex social factors (i.e. communication, Sartori et al., 2009; Ferri et al., 2011; cooperative intention, Georgiou et al., 2007; Becchio et al., 2008). Thus, grasping and reaching may be thoughtof a instrumental movements that also allow us communicating with others and suggest that reach-to-grasp joint actions are a good candidate to study non-verbal social interaction. These realistic face-to-face interactive tasks using objects allow the participants to reproduce social behaviors in a controlled experimental environment.
Historically, studies on social interaction have been using passive observer in action perception set-ups. These 'open' loops offer some information about the comprehension of others' behaviors (i.e. mirror neurons network, Rizzolatti and Craighero, 2004), but lack bidirectional and reciprocal adaptation that are inherent characteristics to our social life since birth. Our paradigm proposes an ecological closed-loop scenario, by virtually simulating (Exp 1) or ecologically generating (Exp 2) a shared goal during an on-line interaction. The crucial andmost innovative feature of the set-up is that is it based on rather complex individual movements (reaching and grasping) that need to be on-line adjusted to the movements of a partner who is synchronously reading and reacting to ones' behavior.
Our paradigm also offers a modulation on the 'degree' of social engagement, by asking subjects to either interact temporally or spatio-temporally with a virtual or a real partner. By its definition, joint actions require dynamic and efficient encoding of others' gesture and a spatio-temporal synchronization of the individuals involved (Sebanz et al., 2006) Therefore, we expect a greater modulation of social neuromarkers in the Free Condition compared to the Guided Condition (i.e. mu suppression over Rolandic areas, sensory-motor coherence linked to fronto-parietal visuo-motor transformations).
Furthermore, our experimental choices to couple electro-encephalogram and kinematics recordings offer a great opportunity to study the dynamics of social neuromarkers at the body and brain level. Social behavior is a complex integrative function that involves severa lbrains' features such as sensory perception, cognitive processing, emotional reactions and movement control. By using two simultaneous recording techniques, we seek to integrate multiple resources of data and cross information to better appreciate the interaction complexity. Our first experiment (Exp 1) will give us a better idea of what social neuromarkers are involved in our task and their modulation through different degree of social engagement. However, knowledge of the brain mechanisms involved in social behaviors needs to go further than knowledge of the individual brain. With our second experiment (Exp 2), by using dual-EEG recordings coupled with kinematics, we aspire to better seize the social complexity and to give a greater overviewof brain-behavior dynamics and generate a better understanding of social interaction in cooperative collaboration.
This approach has the potential to describe the neuro-behavioral markers of impaired motor interactive behavior in a number of clinical conditions such as neurological patients with motor impairments (apraxics, Parkinsonian) or individual characterized by reduced social skills (autistics).