Temporal chunking as a mechanism for unsupervised learning of task-sets

Author:

Bouchacourt Flora12ORCID,Palminteri Stefano123ORCID,Koechlin Etienne12,Ostojic Srdjan123ORCID

Affiliation:

1. Laboratoire de Neurosciences Cognitives et Computationnelles, Institut National de la Sante et de la Recherche Medicale, Paris, France

2. Departement d’Etudes Cognitives, Ecole Normale Superieure, Paris, France

3. Institut d’Etudes de la Cognition, Universite de Recherche Paris Sciences et Lettres, Paris, France

Abstract

Depending on environmental demands, humans can learn and exploit multiple concurrent sets of stimulus-response associations. Mechanisms underlying the learning of such task-sets remain unknown. Here we investigate the hypothesis that task-set learning relies on unsupervised chunking of stimulus-response associations that occur in temporal proximity. We examine behavioral and neural data from a task-set learning experiment using a network model. We first show that task-set learning can be achieved provided the timescale of chunking is slower than the timescale of stimulus-response learning. Fitting the model to behavioral data on a subject-by-subject basis confirmed this expectation and led to specific predictions linking chunking and task-set retrieval that were borne out by behavioral performance and reaction times. Comparing the model activity with BOLD signal allowed us to identify neural correlates of task-set retrieval in a functional network involving ventral and dorsal prefrontal cortex, with the dorsal system preferentially engaged when retrievals are used to improve performance.

Funder

Ecole des Neurosciences de Paris Ile-de-France

Agence Nationale de la Recherche

Inserm

Fondation Fyssen

Schlumberger Foundation

Region Ile de France

Publisher

eLife Sciences Publications, Ltd

Subject

General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,General Medicine,General Neuroscience

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