Optimal Decisions: From Neural Spikes, through Stochastic Differential Equations, to Behavior

Philip HOLMES; Eric SHEA-BROWN; Jeff MOEHLIS; Rafal BOGACZ; Juan GAO; Gary ASTON-JONES; Ed CLAYTON; Janusz RAJKOWSKI; Jonathan D. COHEN

doi:10.1093/ietfec/e88-a.10.2496

Optimal Decisions: From Neural Spikes, through Stochastic Differential Equations, to Behavior

Philip HOLMES, Eric SHEA-BROWN, Jeff MOEHLIS, Rafal BOGACZ, Juan GAO, Gary ASTON-JONES, Ed CLAYTON, Janusz RAJKOWSKI, Jonathan D. COHEN

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There is increasing evidence from in vivo recordings in monkeys trained to respond to stimuli by making left- or rightward eye movements, that firing rates in certain groups of neurons in oculo-motor areas mimic drift-diffusion processes, rising to a (fixed) threshold prior to movement initiation. This supplements earlier observations of psychologists, that human reaction-time and error-rate data can be fitted by random walk and diffusion models, and has renewed interest in optimal decision-making ideas from information theory and statistical decision theory as a clue to neural mechanisms. We review results from decision theory and stochastic ordinary differential equations, and show how they may be extended and applied to derive explicit parameter dependencies in optimal performance that may be tested on human and animal subjects. We then briefly describe a biophysically-based model of a pool of neurons in locus coeruleus, a brainstem nucleus implicated in widespread norepinephrine release. This neurotransmitter can effect transient gain changes in cortical circuits of the type that the abstract drift-diffusion analysis requires. We also describe how optimal gain schedules can be computed in the presence of time-varying noisy signals. We argue that a rational account of how neural spikes give rise to simple behaviors is beginning to emerge.

Publication: IEICE TRANSACTIONS on Fundamentals Vol.E88-A No.10 pp.2496-2503

Publication Date: 2005/10/01

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DOI: 10.1093/ietfec/e88-a.10.2496

Type of Manuscript: Special Section INVITED PAPER (Special Section on Nonlinear Theory and its Applications)

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Philip HOLMES, Eric SHEA-BROWN, Jeff MOEHLIS, Rafal BOGACZ, Juan GAO, Gary ASTON-JONES, Ed CLAYTON, Janusz RAJKOWSKI, Jonathan D. COHEN, "Optimal Decisions: From Neural Spikes, through Stochastic Differential Equations, to Behavior" in IEICE TRANSACTIONS on Fundamentals, vol. E88-A, no. 10, pp. 2496-2503, October 2005, doi: 10.1093/ietfec/e88-a.10.2496.
Abstract: There is increasing evidence from in vivo recordings in monkeys trained to respond to stimuli by making left- or rightward eye movements, that firing rates in certain groups of neurons in oculo-motor areas mimic drift-diffusion processes, rising to a (fixed) threshold prior to movement initiation. This supplements earlier observations of psychologists, that human reaction-time and error-rate data can be fitted by random walk and diffusion models, and has renewed interest in optimal decision-making ideas from information theory and statistical decision theory as a clue to neural mechanisms. We review results from decision theory and stochastic ordinary differential equations, and show how they may be extended and applied to derive explicit parameter dependencies in optimal performance that may be tested on human and animal subjects. We then briefly describe a biophysically-based model of a pool of neurons in locus coeruleus, a brainstem nucleus implicated in widespread norepinephrine release. This neurotransmitter can effect transient gain changes in cortical circuits of the type that the abstract drift-diffusion analysis requires. We also describe how optimal gain schedules can be computed in the presence of time-varying noisy signals. We argue that a rational account of how neural spikes give rise to simple behaviors is beginning to emerge.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1093/ietfec/e88-a.10.2496/_p

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@ARTICLE{e88-a_10_2496,
author={Philip HOLMES, Eric SHEA-BROWN, Jeff MOEHLIS, Rafal BOGACZ, Juan GAO, Gary ASTON-JONES, Ed CLAYTON, Janusz RAJKOWSKI, Jonathan D. COHEN, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Optimal Decisions: From Neural Spikes, through Stochastic Differential Equations, to Behavior},
year={2005},
volume={E88-A},
number={10},
pages={2496-2503},
abstract={There is increasing evidence from in vivo recordings in monkeys trained to respond to stimuli by making left- or rightward eye movements, that firing rates in certain groups of neurons in oculo-motor areas mimic drift-diffusion processes, rising to a (fixed) threshold prior to movement initiation. This supplements earlier observations of psychologists, that human reaction-time and error-rate data can be fitted by random walk and diffusion models, and has renewed interest in optimal decision-making ideas from information theory and statistical decision theory as a clue to neural mechanisms. We review results from decision theory and stochastic ordinary differential equations, and show how they may be extended and applied to derive explicit parameter dependencies in optimal performance that may be tested on human and animal subjects. We then briefly describe a biophysically-based model of a pool of neurons in locus coeruleus, a brainstem nucleus implicated in widespread norepinephrine release. This neurotransmitter can effect transient gain changes in cortical circuits of the type that the abstract drift-diffusion analysis requires. We also describe how optimal gain schedules can be computed in the presence of time-varying noisy signals. We argue that a rational account of how neural spikes give rise to simple behaviors is beginning to emerge.},
keywords={},
doi={10.1093/ietfec/e88-a.10.2496},
ISSN={},
month={October},}

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TY - JOUR
TI - Optimal Decisions: From Neural Spikes, through Stochastic Differential Equations, to Behavior
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 2496
EP - 2503
AU - Philip HOLMES
AU - Eric SHEA-BROWN
AU - Jeff MOEHLIS
AU - Rafal BOGACZ
AU - Juan GAO
AU - Gary ASTON-JONES
AU - Ed CLAYTON
AU - Janusz RAJKOWSKI
AU - Jonathan D. COHEN
PY - 2005
DO - 10.1093/ietfec/e88-a.10.2496
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E88-A
IS - 10
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - October 2005
AB - There is increasing evidence from in vivo recordings in monkeys trained to respond to stimuli by making left- or rightward eye movements, that firing rates in certain groups of neurons in oculo-motor areas mimic drift-diffusion processes, rising to a (fixed) threshold prior to movement initiation. This supplements earlier observations of psychologists, that human reaction-time and error-rate data can be fitted by random walk and diffusion models, and has renewed interest in optimal decision-making ideas from information theory and statistical decision theory as a clue to neural mechanisms. We review results from decision theory and stochastic ordinary differential equations, and show how they may be extended and applied to derive explicit parameter dependencies in optimal performance that may be tested on human and animal subjects. We then briefly describe a biophysically-based model of a pool of neurons in locus coeruleus, a brainstem nucleus implicated in widespread norepinephrine release. This neurotransmitter can effect transient gain changes in cortical circuits of the type that the abstract drift-diffusion analysis requires. We also describe how optimal gain schedules can be computed in the presence of time-varying noisy signals. We argue that a rational account of how neural spikes give rise to simple behaviors is beginning to emerge.
ER -