Rat Prefrontal Cortex Inactivations during Decision Making Are Explained by Bistable Attractor Dynamics. Author Alex Piet, Jeffrey Erlich, Charles Kopec, Carlos Brody Publication Year 2017 Type Journal Article 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. Keywords Animals, Time Factors, Decision Making, Models, Neurological, Rats, Functional Laterality, Muscimol, Prefrontal Cortex, Models, Psychological, Memory, Computer Simulation, Neural Networks, Computer, GABA-A Receptor Agonists, Psychometrics Journal Neural Comput Volume 29 Issue 11 Pages 2861-2886 Date Published 2017 Nov ISSN Number 1530-888X DOI 10.1162/neco_a_01005 Alternate Journal Neural Comput PMCID PMC6535097 PMID 28777728 PubMedPubMed CentralGoogle ScholarBibTeXEndNote X3 XML