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25 mai 2021: 1 événement

Séminaires

  • Séminaires LPNC

    Mardi 25 mai 13:00-14:00 - Gabriel Weindel - Laboratoire de Neurosciences Cognitives, Aix-Marseille et Laboratoire de Psychologie Cognitive, Aix-Marseille

    On the measurement and estimation of cognitive processes with electrophysiological recordings and reaction time modeling

    Résumé : Mathematical models of decision making aim at decomposing reaction times into processing units by formalizing an assumed generative model. Unfortunately, a given generative model may explain the behavioral data while not necessarily reflecting the underlying cognitive processes. Obtaining measurements between the stimulus and the responses could provide additional information that fruitfully constrains the processing assumptions. In this spirit, we used electrophysiological recordings (electromyography and electroencephalography) to decompose each reaction time into different intervals, presumed to contain the different processing units assumed in a model. Simultaneously, we manipulated time-honored experimental factors to compare the cognitive locus of experimental effects inferred from either electrophysiological recordings or model fitting procedures.
    We show that the inferences drawn from cognitive mathematical models conflict with the electrophysiological decomposition when : 1) the model’s core assumption of independence between decision and non-decision processes is proven to be false ; 2) standard modeling strategies are inadequate to capture the locus of an experimental effect revealed by the electrophysiological decomposition ; and 3) opposite experimental effects are revealed across processing units. These results constitute a thorough examination of the validity of a popular decision making model. They offer new insights on the information processes that allow humans to decide between alternatives.

    Lieu : Salle virtuelle Zoom du laboratoire (mot de passe : cognition) - https://univ-grenoble-alpes-fr.zoom.us/j/94294861881?pwd=dkN2MzMvYXpZMnYwYjZPWS9GVUV4Zz09

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