Dissociable neural systems support the learning and transfer of hierarchical control structure

Humans can draw insight from previous experiences in order to quickly adapt to novel environments that share a common underlying structure. Here we combine functional imaging and computational modeling to identify the neural systems that support the discovery and transfer of hierarchical task struct...

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Bibliographic Details
Published inbioRxiv
Main Authors Eichenbaum, Adam, Scimeca, Jason, D'esposito, Mark
Format Paper
LanguageEnglish
Published Cold Spring Harbor Cold Spring Harbor Laboratory Press 17.01.2020
Subjects
Computer applications
Cortex (frontal)
Division of labor
Functional magnetic resonance imaging
Neuroimaging
Transfer learning
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Summary:Humans can draw insight from previous experiences in order to quickly adapt to novel environments that share a common underlying structure. Here we combine functional imaging and computational modeling to identify the neural systems that support the discovery and transfer of hierarchical task structure. Human subjects completed multiple blocks of a reinforcement learning task that contained a global hierarchical structure governing stimulus-response action mapping. First, behavioral and computational evidence showed that humans successfully discover and transfer the hierarchical rule structure embedded within the task. Next, analysis of fMRI BOLD data revealed activity across a frontal-parietal network that was specifically associated with the discovery of this embedded structure. Finally, activity throughout a cingulo-opercular network and in caudal frontal cortex supported the transfer and implementation of this discovered structure. Together, these results reveal a division of labor in which dissociable neural systems support the learning and transfer of abstract control structures.
DOI:10.1101/2020.01.16.909978