Frontal cortex neuron types categorically encode single decision variables

Hirokawa, J., Vaughan, A., Masset, P., Ott, T., Kepecs, A. (December 2019) Frontal cortex neuron types categorically encode single decision variables. Nature, 576 (7787). pp. 446-451. ISSN 0028-0836 (Public Dataset)

URL: https://www.ncbi.nlm.nih.gov/pubmed/31801999
DOI: 10.1038/s41586-019-1816-9

Abstract

Individual neurons in many cortical regions have been found to encode specific, identifiable features of the environment or body that pertain to the function of the region(1-3). However, in frontal cortex, which is involved in cognition, neural responses display baffling complexity, carrying seemingly disordered mixtures of sensory, motor and other task-related variables(4-13). This complexity has led to the suggestion that representations in individual frontal neurons are randomly mixed and can only be understood at the neural population level(14,15). Here we show that neural activity in rat orbitofrontal cortex (OFC) is instead highly structured: single neuron activity co-varies with individual variables in computational models that explain choice behaviour. To characterize neural responses across a large behavioural space, we trained rats on a behavioural task that combines perceptual and value-guided decisions. An unbiased, model-free clustering analysis identified distinct groups of OFC neurons, each with a particular response profile in task-variable space. Applying a simple model of choice behaviour to these categorical response profiles revealed that each profile quantitatively corresponds to a specific decision variable, such as decision confidence. Additionally, we demonstrate that a connectivity-defined cell type, orbitofrontal neurons projecting to the striatum, carries a selective and temporally sustained representation of a single decision variable: integrated value. We propose that neurons in frontal cortex, as in other cortical regions, form a sparse and overcomplete representation of features relevant to the region's function, and that they distribute this information selectively to downstream regions to support behaviour.

Item Type: Paper
Subjects: organism description > animal behavior > decision making
organs, tissues, organelles, cell types and functions > cell types and functions > cell types > neurons
organs, tissues, organelles, cell types and functions > cell types and functions > cell types > neurons
organs, tissues, organelles, cell types and functions > cell types and functions > cell types > neurons
organs, tissues, organelles, cell types and functions > tissues types and functions > prefrontal cortex
organs, tissues, organelles, cell types and functions > tissues types and functions > striatum
CSHL Authors:
Communities: CSHL labs > Kepecs lab
Depositing User: Adrian Gomez
Date: 4 December 2019
Date Deposited: 11 Dec 2019 15:45
Last Modified: 09 Jan 2020 19:16
Related URLs:
Dataset ID:
  • Code: https://github.com/agvaughan/EllipticalClustering
URI: https://repository.cshl.edu/id/eprint/38734

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