Models of the temporal dynamics of visual processing

Single unit recordings of neurons in primary visual cortex have demonstrated complex temporal patterns in the interspike interval return maps when presented with periodic input. Two models are tested to account for these patterns. An integrate-and-fire model is only able to replicate thein vivo data if its synaptic input is a chaotic function of time (such as a time series derived from the sinusoidally driven Duffing equation). Simpler purely periodic inputs are insufficient to replicate the experimental data. A Hodgkin-Huxley ionic model with a periodic input can replicate some of the features of the neural data, however it seems to be lacking as a complete model. These results indicate that thein vivo dynamics are not a result of the intrinsic properties of the neuron, but arise from a chaotic input to the neuron.