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Prefrontal Goal Codes Emerge as Latent States in Probabilistic Value Learning

Abstract : 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.
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Contributor : Jean-Baptiste Melmi Connect in order to contact the contributor
Submitted on : Wednesday, January 11, 2017 - 4:33:24 PM
Last modification on : Wednesday, November 3, 2021 - 6:44:25 AM

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Ivilin Stoianov, Aldo Genovesio, Giovanni Pezzulo. Prefrontal Goal Codes Emerge as Latent States in Probabilistic Value Learning. Journal of Cognitive Neuroscience, Massachusetts Institute of Technology Press (MIT Press), 2016, 28 (1), pp.140-157. ⟨10.1162/jocn_a_00886⟩. ⟨hal-01432272⟩



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