• J. Neurosci. · Apr 2014

    Does the processing of sensory and reward-prediction errors involve common neural resources? Evidence from a frontocentral negative potential modulated by movement execution errors.

    • Flavie Torrecillos, Philippe Albouy, Thomas Brochier, and Nicole Malfait.
    • Institut de Neurosciences de la Timone, UMR7289, Aix Marseille Université, CNRS, 13385 Marseille, France, and Centre de Recherche en Neurosciences de Lyon, U1028, INSERM, UMR5292, CNRS/Université Lyon 1, 69000, France.
    • J. Neurosci. 2014 Apr 2; 34 (14): 4845-56.

    AbstractIn humans, electrophysiological correlates of error processing have been extensively investigated in relation to decision-making theories. In particular, error-related ERPs have been most often studied using response selection tasks. In these tasks, involving very simple motor responses (e.g., button press), errors concern inappropriate action-selection only. However, EEG activity in relation to inaccurate movement-execution in more complex motor tasks has been much less examined. In the present study, we recorded EEG while volunteers performed reaching movements in a force-field created by a robotic device. Hand-path deviations were induced by interspersing catch trials in which the force condition was unpredictably altered. Our goal was twofold. First, we wanted to determine whether a frontocentral ERP was elicited by sensory-prediction errors, whose amplitude reflected the size of kinematic errors. Then, we explored whether common neural processes could be involved in the generation of this ERP and the feedback-related negativity (FRN), often assumed to reflect reward-prediction errors. We identified a frontocentral negativity whose amplitude was modulated by the size of the hand-path deviations induced by the unpredictable mechanical perturbations. This kinematic error-related ERP presented great similarities in terms of time course, topography, and potential source-location with the FRN recorded in the same experiment. These findings suggest that the processing of sensory-prediction errors and the processing of reward-prediction errors could involve a shared neural network.

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