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The Journal of Neuroscience, May 15, 1998, 18(10):3870-3896
The Variable Discharge of Cortical Neurons: Implications for
Connectivity, Computation, and Information Coding
Michael N.
Shadlen1 and
William T.
Newsome2
1 Department of Physiology and Biophysics and Regional
Primate Research Center, University of Washington, Seattle, Washington
98195-7290, and 2 Howard Hughes Medical Institute and
Department of Neurobiology, Stanford University School of Medicine,
Stanford, California 94305
Cortical neurons exhibit tremendous variability in the number and
temporal distribution of spikes in their discharge patterns. Furthermore, this variability appears to be conserved over large regions of the cerebral cortex, suggesting that it is neither reduced
nor expanded from stage to stage within a processing pathway. To
investigate the principles underlying such statistical homogeneity, we
have analyzed a model of synaptic integration incorporating a highly
simplified integrate and fire mechanism with decay. We analyzed a
"high-input regime" in which neurons receive hundreds of excitatory
synaptic inputs during each interspike interval. To produce a graded
response in this regime, the neuron must balance excitation with
inhibition. We find that a simple integrate and fire mechanism with
balanced excitation and inhibition produces a highly variable
interspike interval, consistent with experimental data. Detailed
information about the temporal pattern of synaptic inputs cannot be
recovered from the pattern of output spikes, and we infer that cortical
neurons are unlikely to transmit information in the temporal pattern of
spike discharge. Rather, we suggest that quantities are represented as
rate codes in ensembles of 50-100 neurons. These column-like ensembles
tolerate large fractions of common synaptic input and yet covary only
weakly in their spike discharge. We find that an ensemble of 100 neurons provides a reliable estimate of rate in just one interspike
interval (10-50 msec). Finally, we derived an expression for the
variance of the neural spike count that leads to a stable propagation
of signal and noise in networks of neurons that is, conditions that do
not impose an accumulation or diminution of noise. The solution implies that single neurons perform simple algebra resembling averaging, and
that more sophisticated computations arise by virtue of the anatomical
convergence of novel combinations of inputs to the cortical column from
external sources.
Key words:
noise; rate code; temporal coding; correlation; interspike interval; spike count variance; response variability; visual
cortex; synaptic integration; neural model
Copyright © 1998 Society for Neuroscience 0270-6474/98/18103870-27$05.00/0
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R. E. Kass, V. Ventura, and E. N. Brown
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E. S. Frechette, A. Sher, M. I. Grivich, D. Petrusca, A. M. Litke, and E. J. Chichilnisky
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J. A. Henrie and R. Shapley
LFP Power Spectra in V1 Cortex: The Graded Effect of Stimulus Contrast
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S. Shinomoto, Y. Miyazaki, H. Tamura, and I. Fujita
Regional and Laminar Differences in In Vivo Firing Patterns of Primate Cortical Neurons
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S. R. Williams
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R. Schaette, T. Gollisch, and A. V. M. Herz
Spike-Train Variability of Auditory Neurons In Vivo: Dynamic Responses Follow Predictions From Constant Stimuli
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M. Raffi and R. M. Siegel
Functional Architecture of Spatial Attention in the Parietal Cortex of the Behaving Monkey
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M. A. Lebedev, J. M. Carmena, J. E. O'Doherty, M. Zacksenhouse, C. S. Henriquez, J. C. Principe, and M. A. L. Nicolelis
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D. Cai, A. V. Rangan, and D. W. McLaughlin
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A. Kohn and M. A. Smith
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S. Hill and G. Tononi
Modeling Sleep and Wakefulness in the Thalamocortical System
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E. Hitt
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D. B. Katz
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J. Hegde and D. C. Van Essen
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J. B. Demb, P. Sterling, and M. A. Freed
How Retinal Ganglion Cells Prevent Synaptic Noise From Reaching the Spike Output
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October 1, 2004;
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S. Tanabe, K. Umeda, and I. Fujita
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E. Garcia-Perez, D. Zoccolan, G. Pinato, and V. Torre
Dynamics and Reproducibility of a Moderately Complex Sensory-Motor Response in the Medicinal Leech
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M. R. Deweese and A. M. Zador
Shared and Private Variability in the Auditory Cortex
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V. J. Uzzell and E. J. Chichilnisky
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M. Giugliano, P. Darbon, M. Arsiero, H.-R. Luscher, and J. Streit
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C. L. Passaglia and J. B. Troy
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C. C. Horn, Y. Zhurov, I. V. Orekhova, A. Proekt, I. Kupfermann, K. R. Weiss, and V. Brezina
Cycle-to-Cycle Variability of Neuromuscular Activity in Aplysia Feeding Behavior
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P. Petersson, M. Granmo, and J. Schouenborg
Properties of an Adult Spinal Sensorimotor Circuit Shaped Through Early Postnatal Experience
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J. Perez-Orive, M. Bazhenov, and G. Laurent
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W. J. Kargo and D. A. Nitz
Improvements in the Signal-to-Noise Ratio of Motor Cortex Cells Distinguish Early versus Late Phases of Motor Skill Learning
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