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Nat Neurosci. 2014 Jun;17(6):858-65. doi: 10.1038/nn.3711. Epub 2014 Apr 28.

Partitioning neuronal variability.

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Center for Neural Science, New York University, New York, New York, USA.
1] Center for Neural Science, New York University, New York, New York, USA. [2] Howard Hughes Medical Institute, New York University, New York, New York, USA.


Responses of sensory neurons differ across repeated measurements. This variability is usually treated as stochasticity arising within neurons or neural circuits. However, some portion of the variability arises from fluctuations in excitability due to factors that are not purely sensory, such as arousal, attention and adaptation. To isolate these fluctuations, we developed a model in which spikes are generated by a Poisson process whose rate is the product of a drive that is sensory in origin and a gain summarizing stimulus-independent modulatory influences on excitability. This model provides an accurate account of response distributions of visual neurons in macaque lateral geniculate nucleus and cortical areas V1, V2 and MT, revealing that variability originates in large part from excitability fluctuations that are correlated over time and between neurons, and that increase in strength along the visual pathway. The model provides a parsimonious explanation for observed systematic dependencies of response variability and covariability on firing rate.

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