: Competitive settings may be promising for neurorehabilitation as they may lead to stronger patient motivation. However, the mechanisms underlying the development of an interaction in competitive settings are not well understood. We use a dyadic haptic interface to investigate the dynamics of competitive interaction. Pairs of participants engaged in a ball game (a penalty kick challenge), with an attacker and a defender. To explore how the participants adapt to each other over game iterations, we manipulated the amount of information available to each one about the location of their opponent. We found that under the different experimental conditions, the participants adjusted their behavior in response to their opponents' strategy change. These observations are consistent with simulations with a computational model assuming that during interaction the participants use optimal (Bayesian) perception and action selection (based on game theory). Taken together, experiments and simulations suggest that the participants develop and update a flexible, adaptive predictor of their opponents next action, which helps them adjust their behavior to optimize performance. These findings provide a foundation for further research into the mechanisms that drive adaptive behavior in competitive scenarios, and provide new insights into how competitive environments can be used in rehabilitation.

Manipulation of Sensory Information in Competitive Scenarios Induces Adaptive Changes in Action Selection: Insights for Neurorehabilitation

Bandini, Laura;De Vicariis, Cecilia;Sanguineti, Vittorio
2025-01-01

Abstract

: Competitive settings may be promising for neurorehabilitation as they may lead to stronger patient motivation. However, the mechanisms underlying the development of an interaction in competitive settings are not well understood. We use a dyadic haptic interface to investigate the dynamics of competitive interaction. Pairs of participants engaged in a ball game (a penalty kick challenge), with an attacker and a defender. To explore how the participants adapt to each other over game iterations, we manipulated the amount of information available to each one about the location of their opponent. We found that under the different experimental conditions, the participants adjusted their behavior in response to their opponents' strategy change. These observations are consistent with simulations with a computational model assuming that during interaction the participants use optimal (Bayesian) perception and action selection (based on game theory). Taken together, experiments and simulations suggest that the participants develop and update a flexible, adaptive predictor of their opponents next action, which helps them adjust their behavior to optimize performance. These findings provide a foundation for further research into the mechanisms that drive adaptive behavior in competitive scenarios, and provide new insights into how competitive environments can be used in rehabilitation.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/1257319
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