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Journal of Neuroscience, Vol 13, 334-350, Copyright © 1993 by Society for Neuroscience


ARTICLE

The highly irregular firing of cortical cells is inconsistent with temporal integration of random EPSPs

WR Softky and C Koch
Division of Physics, Mathematics, and Astronomy, California Institute of Technology, Pasadena 91125.

How random is the discharge pattern of cortical neurons? We examined recordings from primary visual cortex (V1; Knierim and Van Essen, 1992) and extrastriate cortex (MT; Newsome et al., 1989a) of awake, behaving macaque monkey and compared them to analytical predictions. For nonbursting cells firing at sustained rates up to 300 Hz, we evaluated two indices of firing variability: the ratio of the variance to the mean for the number of action potentials evoked by a constant stimulus, and the rate-normalized coefficient of variation (Cv) of the interspike interval distribution. Firing in virtually all V1 and MT neurons was nearly consistent with a completely random process (e.g., Cv approximately 1). We tried to model this high variability by small, independent, and random EPSPs converging onto a leaky integrate-and- fire neuron (Knight, 1972). Both this and related models predicted very low firing variability (Cv << 1) for realistic EPSP depolarizations and membrane time constants. We also simulated a biophysically very detailed compartmental model of an anatomically reconstructed and physiologically characterized layer V cat pyramidal cell (Douglas et al., 1991) with passive dendrites and active soma. If independent, excitatory synaptic input fired the model cell at the high rates observed in monkey, the Cv and the variability in the number of spikes were both very low, in agreement with the integrate-and-fire models but in strong disagreement with the majority of our monkey data. The simulated cell only produced highly variable firing when Hodgkin-Huxley- like currents (INa and very strong IDR) were placed on distal dendrites. Now the simulated neuron acted more as a millisecond- resolution detector of dendritic spike coincidences than as a temporal integrator. We argue that neurons that act as temporal integrators over many synaptic inputs must fire very regularly. Only in the presence of either fast and strong dendritic nonlinearities or strong synchronization among individual synaptic events will the degree of predicted variability approach that of real cortical neurons.


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J. Neurosci., May 1, 2003; 23(9): 3761 - 3770.
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T. Uka and G. C. DeAngelis
Contribution of Middle Temporal Area to Coarse Depth Discrimination: Comparison of Neuronal and Psychophysical Sensitivity
J. Neurosci., April 15, 2003; 23(8): 3515 - 3530.
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A. F. Teich and N. Qian
Learning and Adaptation in a Recurrent Model of V1 Orientation Selectivity
J Neurophysiol, April 1, 2003; 89(4): 2086 - 2100.
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V. Litvak, H. Sompolinsky, I. Segev, and M. Abeles
On the Transmission of Rate Code in Long Feedforward Networks with Excitatory-Inhibitory Balance
J. Neurosci., April 1, 2003; 23(7): 3006 - 3015.
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S. A. Prescott and Y. De Koninck
Gain control of firing rate by shunting inhibition: Roles of synaptic noise and dendritic saturation
PNAS, February 18, 2003; 100(4): 2076 - 2081.
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T. R. Tucker and L. C. Katz
Spatiotemporal Patterns of Excitation and Inhibition Evoked by the Horizontal Network in Layer 2/3 of Ferret Visual Cortex
J Neurophysiol, January 1, 2003; 89(1): 488 - 500.
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G. Svirskis, V. Kotak, D. H. Sanes, and J. Rinzel
Enhancement of Signal-to-Noise Ratio and Phase Locking for Small Inputs by a Low-Threshold Outward Current in Auditory Neurons
J. Neurosci., December 15, 2002; 22(24): 11019 - 11025.
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M. C. Tresch and O. Kiehn
Synchronization of Motor Neurons during Locomotion in the Neonatal Rat: Predictors and Mechanisms
J. Neurosci., November 15, 2002; 22(22): 9997 - 10008.
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J. D. Roitman and M. N. Shadlen
Response of Neurons in the Lateral Intraparietal Area during a Combined Visual Discrimination Reaction Time Task
J. Neurosci., November 1, 2002; 22(21): 9475 - 9489.
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G. Fuhrmann, H. Markram, and M. Tsodyks
Spike Frequency Adaptation and Neocortical Rhythms
J Neurophysiol, August 1, 2002; 88(2): 761 - 770.
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D. G. Albrecht, W. S. Geisler, R. A. Frazor, and A. M. Crane
Visual Cortex Neurons of Monkeys and Cats: Temporal Dynamics of the Contrast Response Function
J Neurophysiol, August 1, 2002; 88(2): 888 - 913.
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M. C. W. van Rossum, G. G. Turrigiano, and S. B. Nelson
Fast Propagation of Firing Rates through Layered Networks of Noisy Neurons
J. Neurosci., March 1, 2002; 22(5): 1956 - 1966.
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P. R. Roelfsema, R. P. Hasegawa, A. M. Blitz, N. L. Geller, and M. E. Goldberg
Do Neurons Predict the Future?
Science, January 11, 2002; 295(5553): 227a - 227a.
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G. Fuhrmann, I. Segev, H. Markram, and M. Tsodyks
Coding of Temporal Information by Activity-Dependent Synapses
J Neurophysiol, January 1, 2002; 87(1): 140 - 148.
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ScienceHome page
F. Pouille and M. Scanziani
Enforcement of Temporal Fidelity in Pyramidal Cells by Somatic Feed-Forward Inhibition
Science, August 10, 2001; 293(5532): 1159 - 1163.
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M. J. Chacron, A. Longtin, and L. Maler
Negative Interspike Interval Correlations Increase the Neuronal Capacity for Encoding Time-Dependent Stimuli
J. Neurosci., July 15, 2001; 21(14): 5328 - 5343.
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S. P. Perrett, S. M. Dudek, D. Eagleman, P. R. Montague, and M. J. Friedlander
LTD Induction in Adult Visual Cortex: Role of Stimulus Timing and Inhibition
J. Neurosci., April 1, 2001; 21(7): 2308 - 2319.
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S. A. Roy and K. D. Alloway
Coincidence Detection or Temporal Integration? What the Neurons in Somatosensory Cortex Are Doing
J. Neurosci., April 1, 2001; 21(7): 2462 - 2473.
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P. Faure, D. Kaplan, and H. Korn
Synaptic Efficacy and the Transmission of Complex Firing Patterns Between Neurons
J Neurophysiol, December 1, 2000; 84(6): 3010 - 3025.
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S. R. Williams and G. J. Stuart
Backpropagation of Physiological Spike Trains in Neocortical Pyramidal Neurons: Implications for Temporal Coding in Dendrites
J. Neurosci., November 15, 2000; 20(22): 8238 - 8246.
[Abstract] [Full Text] [PDF]



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