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Neural Comput. 2017 Nov;29(11):2861-2886. doi: 10.1162/neco_a_01005. Epub 2017 Aug 4.

Rat Prefrontal Cortex Inactivations during Decision Making Are Explained by Bistable Attractor Dynamics.

Author information

1
Princeton Neuroscience Institute, Princeton University, Princeton, NJ 08544, U.S.A. alexpiet@gmail.com.
2
NYU-ECNU Institute of Brain and Cognitive Science, New York University Shanghai, Shanghai 200122, China jerlich@erlichlab.org.
3
Princeton Neuroscience Institute and Department of Molecular Biology, Princeton University, Princeton, NJ 08544, U.S.A. ckopec@princeton.edu.
4
Princeton Neuroscience Institute, Department of Molecular Biology, and Howard Hughes Medical Institute, Princeton University, Princeton, NJ 08544, U.S.A. brody@princeton.edu.

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 memory-duration-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.

PMID:
28777728
PMCID:
PMC6535097
DOI:
10.1162/neco_a_01005
[Indexed for MEDLINE]
Free PMC Article

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