Many paths from state to state

Kaufman, M. T., Churchland, A. K. (November 2016) Many paths from state to state. Nat Neurosci, 19 (12). pp. 1541-1542. ISSN 1546-1726 (Electronic)1097-6256 (Linking)

URL: https://www.ncbi.nlm.nih.gov/pubmed/27898087
DOI: 10.1038/nn.4440

Abstract

Humans and animals can actively represent and maintain information that guides decisions, but how neural circuits achieve this is unknown. The dominant notion for many years has been that neurons encode information primarily using their spike rate, which is usually hypothesized to have a static relationship with stimuli or internal state. Yet more recently there has been a resurgence of interest in the old idea that the brain might use stereotyped sequences of discrete states, switching from one activity pattern to another to maintain activity1, 2. Each of these 'states' would be distinct enough from one another that even an imperfect realization of the activity pattern could still reliably drive the next state in the sequence. These sequences might be used explicitly as clocks3, 4, or they might be a convenient way for recurrent neural circuits to maintain information despite the short time constants of single cells5, 6. It is challenging to perfectly tune a circuit to maintain a precise, stable state along a continuum of possibilities7. The idea that sequences might avoid this challenge is thus appealing and would even permit sparse activity. In this issue of Nature Neuroscience, Morcos and Harvey8 present evidence that this is indeed the case, with a few wrinkles that may make the system more flexible.

Item Type: Paper
Subjects: organism description > animal behavior > decision making
organs, tissues, organelles, cell types and functions > cell types and functions > cell types > neurons > neuronal circuits
organs, tissues, organelles, cell types and functions > cell types and functions > cell types > neurons > neuronal circuits
organs, tissues, organelles, cell types and functions > cell types and functions > cell types > neurons > neuronal circuits
CSHL Authors:
Communities: CSHL labs > Churchland lab
Depositing User: Matt Covey
Date: 29 November 2016
Date Deposited: 01 Dec 2016 15:31
Last Modified: 01 Dec 2016 15:31
Related URLs:
URI: http://repository.cshl.edu/id/eprint/33917

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