Dissecting the neurocomputational bases of patch-switching

G. Zacharopoulos*, G. Maio, D.E.J. Linden

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

The survival and well-being of humans require solving the patch-switching problem: we must decide when to stop collecting rewards in a current patch and travel somewhere else where gains may be higher. Previous studies suggested that frontal regions are underpinned by several processes in the context of foraging decisions such as tracking task difficulty, and/or the value of exploring the environment. To dissociate between these processes, participants completed an fMRI patch-switching learning task inspired by behavioral ecology. By analyzing >11,000 trials collected across 21 participants, we found that the activation in the cingulate cortex was closely related to several patch-switching-related variables including the decision to leave the current patch, the encounter of a new patch, the harvest value, and the relative forage value. Learning-induced changes in the patch-switching threshold were tracked by activity within frontoparietal regions including the superior frontal gyrus and angular gyrus. Our findings suggest that frontoparietal regions shape patch-switching learning apart from encoding classical non-learning foraging processes. These findings provide a novel neurobiological understanding of how learning emerges neurocomputationally shaping patch-switching behavior with implications in real-life choices such as job selection and pave the way for future studies to probe the causal role of these neurobiological mechanisms.
Original languageEnglish
Pages (from-to)7930-7940
Number of pages11
JournalCerebral Cortex
Volume33
Issue number12
Early online date1 Mar 2023
DOIs
Publication statusPublished - 15 Jun 2023

Keywords

  • patch-switching
  • fMRI
  • individual differences
  • learning
  • DORSAL ANTERIOR CINGULATE
  • PARIETAL CORTEX
  • IN-VIVO
  • MEMORY
  • RESOLUTION
  • FASCICLE
  • NUMBERS
  • HUMANS

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