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Journal of Neuroscience, Vol 13, 334-350, Copyright © 1993 by Society for Neuroscience
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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[Abstract]
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[Abstract]
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[PDF]
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