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A simple model of cortical dynamics explains variability and state dependence of sensory responses in urethane-anesthetized auditory cortex.


ABSTRACT: The responses of neocortical cells to sensory stimuli are variable and state dependent. It has been hypothesized that intrinsic cortical dynamics play an important role in trial-to-trial variability; the precise nature of this dependence, however, is poorly understood. We show here that in auditory cortex of urethane-anesthetized rats, population responses to click stimuli can be quantitatively predicted on a trial-by-trial basis by a simple dynamical system model estimated from spontaneous activity immediately preceding stimulus presentation. Changes in cortical state correspond consistently to changes in model dynamics, reflecting a nonlinear, self-exciting system in synchronized states and an approximately linear system in desynchronized states. We propose that the complex and state-dependent pattern of trial-to-trial variability can be explained by a simple principle: sensory responses are shaped by the same intrinsic dynamics that govern ongoing spontaneous activity.

SUBMITTER: Curto C 

PROVIDER: S-EPMC2861166 | biostudies-literature | 2009 Aug

REPOSITORIES: biostudies-literature

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A simple model of cortical dynamics explains variability and state dependence of sensory responses in urethane-anesthetized auditory cortex.

Curto Carina C   Sakata Shuzo S   Marguet Stephan S   Itskov Vladimir V   Harris Kenneth D KD  

The Journal of neuroscience : the official journal of the Society for Neuroscience 20090801 34


The responses of neocortical cells to sensory stimuli are variable and state dependent. It has been hypothesized that intrinsic cortical dynamics play an important role in trial-to-trial variability; the precise nature of this dependence, however, is poorly understood. We show here that in auditory cortex of urethane-anesthetized rats, population responses to click stimuli can be quantitatively predicted on a trial-by-trial basis by a simple dynamical system model estimated from spontaneous acti  ...[more]

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