Rat prefrontal cortex inactivations during decision making are explained by bistable attractor dynamics

Alex T. Piet, Jeffrey C. Erlich, Charles D. Kopec, Carlos D. Brody

Research output: Contribution to journalArticle

7 Scopus citations

Abstract

Two-node attractor networks are flexible models for neural activity during decision making. Depending on the network configuration, these networks can model distinct aspects of decisions including evidence integration, evidence categorization, and decision memory. Here, we use attractor networks to model recent causal perturbations of the frontal orienting fields (FOF) in rat cortex during a perceptual decision-making task (Erlich, Brunton, Duan, Hanks, & Brody, 2015). We focus on a striking feature of the perturbation results. Pharmacological silencing of the FOF resulted in a stimulus-independent bias. We fit several models to test whether integration, categorization, or decision memory could account for this bias and found that only the memory configuration successfully accounts for it. This memory model naturally accounts for optogenetic perturbations of FOF in the same task and correctly predicts a memoryduration- dependent deficit caused by silencing FOF in a different task. Our results provide mechanistic support for a "postcategorization" memory role of the FOF in upcoming choices.

Original languageEnglish (US)
Pages (from-to)2861-2886
Number of pages26
JournalNeural computation
Volume29
Issue number11
DOIs
StatePublished - Nov 1 2017

All Science Journal Classification (ASJC) codes

  • Arts and Humanities (miscellaneous)
  • Cognitive Neuroscience

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