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A computational model of vertical signal propagation in the primary visual cortex


A computational model of the flow of activity in a vertically organized slab of cat primary visual cortex (area 17) has been developed. The membrane potential of each cell in the model, as a function of time, is given by the solution of a system of first order, coupled, non-linear differential equations. When firing threshold is exceeded, an action potential waveform is “pasted” in. The behavior of the model following a brief simulated stimulus to afferents from the dorsal lateral geniculate nucleus (dLGN) is explored. Excitatory and inhibitory post-synaptic potential (E and IPSP) latencies, as a function of cortical depth, were generated by the model. These data were compared with the experimental literature. In general, good agreement was found for EPSPs. Many disynaptic inhibitory inputs were found to be “masked” by the firing of action potentials in the model. To our knowledge this phenomenon has not been reported in the experimental literature. The model demonstrates that whether a cell exhibits disynaptic or polysynaptic PSP latencies is not a fixed consequence of anatomical connectivity, but rather, can be influenced by connection strengths, and may be influenced by the ongoing pattern of activity in the cortex.

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Correspondence to Robert E. Wyatt.

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Supported by a grant from Cray Research Inc.

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Patton, P., Thomas, E. & Wyatt, R.E. A computational model of vertical signal propagation in the primary visual cortex. Biol. Cybern. 68, 43–52 (1992).

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  • Membrane Potential
  • Computational Model
  • Signal Propagation
  • Lateral Geniculate Nucleus
  • Primary Visual Cortex