Inhibitory Theta Burst Stimulation Highlights the Role of Left aIPS and Right TPJ during Complementary and Imitative Human–Avatar Interactions in Cooperative and Competitive Scenarios

Competitive and cooperative interactions are based on anticipation or synchronization with the partner’s actions. Both forms of interaction may either require performing imitative or complementary movements with respect to those performed by our partner. We explored how parietal regions involved in the control of imitative behavior (temporo-parietal junction, TPJ), goal coding and visuo-motor integration (anterior intraparietal sulcus, aIPS) contribute to the execution of imitative and complementary movements during cooperative and competitive interactions. To this aim, we delivered off-line non-invasive inhibitory brain stimulation to healthy individuals’ left aIPS and right TPJ before they were asked to reach and grasp an object together with a virtual partner by either performing imitative or complementary interactions. In different blocks, participants were asked to compete or cooperate with the virtual partner that varied its behavior according to cooperative or competitive contexts. Left aIPS and right TPJ inhibition impaired individuals’ performance (i.e., synchrony in cooperative task and anticipation in competition) during complementary and imitative interactions, respectively, in both cooperative and competitive contexts, indicating that aIPS and TPJ inhibition affects own-other action integration and action imitation (that are different in complementary vs imitative interactions) more than action synchronization or anticipation (that are different in cooperative vs competitive contexts).

Prefrontal Goal Codes Emerge as Latent States in Probabilistic Value Learning

The prefrontal cortex (PFC) supports goal-directed actions and exerts cognitive control over behavior, but the underlying coding and mechanism are heavily debated. We present evidence for the role of goal coding in PFC from two converging perspectives: computational modeling and neuronal-level analysis of monkey data. We show that neural representations of prospective goals emerge by combining a categorization process that extracts relevant behavioral abstractions from the input data and a reward-driven process that selects candidate categories depending on their adaptive value; both forms of learning have a plausible neural implementation in PFC. Our analyses demonstrate a fundamental principle: goal coding represents an efficient solution to cognitive control problems, analogous to efficient coding principles in other (e.g., visual) brain areas. The novel analytical–computational approach is of general interest because it applies to a variety of neurophysiological studies.

Is Automatic Imitation Based on Goal Coding or Movement Coding?

A key issue for research on automatic imitation is whether it occurs primarily at the level of movements, that is, by automatically activating a representation of the movement/effector involved in the execution of the observed action, or at the level of goals, that is, by triggering a representation of the action goal, irrespective of how the motor act is physically instantiated. The present study presents two experiments aimed at investigating the contribution of movement coding and goal coding to automatic imitation, by assessing participants’ performance in a spatial compatibility task where the observed stimuli were goal-directed and goal-less actions, which have been demonstrated to elicit, respectively, goal and movement coding. We found a significant automatic imitation effect both when the stimuli were goal-less actions and when they were actions directed toward a goal. However, the effect was stronger for the goal-less actions, even after controlling for saliency effects. These results suggest that goal coding contributes to automatic imitation, but to a lesser degree compared to movement coding. The implications of these results for theory and research on automatic imitation are discussed.