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The rodent lateral orbitofrontal cortex as an arbitrator selecting between model-based and model-free learning systems

Abstract : Our understanding of orbitofrontal cortex (OFC) function has progressed remarkably over the past decades in part due to theoretical advances in associative and reinforcement learning theories. These theoretical accounts of OFC function have implicated the region in progressively more psychologically refined processes from the value and sensory specific properties of expected outcomes to the representation and inference over latent state representations in cognitive maps of task space. While these accounts have been successful at modelling many of the effects of causal manipulation of OFC function in both rodents and primates, recent findings suggest that further refinement of our current models are still required. Here we briefly review how our understanding of OFC function has developed to understand two cardinal deficits following OFC dysfunction: reversal learning and outcome devaluation. We then consider recent findings that OFC dysfunction also significantly affects initial acquisition learning, often assumed to be intact. To account for these findings, we consider a possible role for the OFC in the arbitration and exploration between model-free and model-based learning systems, off-line updating of model-based representations. While the function of the OFC as a whole is still likely to be integral to the formation and use of a cognitive map of task space, these refinements suggest a way in which distinct orbital subregions, such as the rodent lateral OFC, might contribute to this overall function.
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https://hal.archives-ouvertes.fr/hal-03107588
Contributor : Mehdi Khamassi <>
Submitted on : Tuesday, January 12, 2021 - 4:50:49 PM
Last modification on : Friday, February 5, 2021 - 3:31:16 AM

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  • HAL Id : hal-03107588, version 1

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Marios Panayi, Mehdi Khamassi, Simon Killcross. The rodent lateral orbitofrontal cortex as an arbitrator selecting between model-based and model-free learning systems. Behavioral Neuroscience, American Psychological Association, inPress. ⟨hal-03107588v1⟩

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