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| Paper IPM / Cognitive / 14560 |
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The accurate prediction of how spiking of a pre-synaptic neuron affects spike timing of the post-synaptic neuron has significant importance in a variety of questions of neurosciences. It is crucial in understanding information transfer, timing dependent learning, reverse engineering of the network architecture and more. Such prediction, however, is lacking due to the nonlinear nature of neuron�??s spiking dynamics; the neuron exclusively fires if its membrane potential reaches the so-called threshold potential. The Fokker-Planck equation, which is used to find such accurate prediction, is hardly tractable in the presence of absorbing boundary condition, imposed by the very threshold criteria. However, there is a specific but ubiquitous situation for which we can solve the Fokker-Planck equation; it happens if the mean current which a neuron receives equals threshold potential*. We have been able to exactly solve the aforementioned problem of prediction for this threshold regime. Then we used our exact solution to reverse engineer the network architecture of monkey�??s cortex, in V1, using existing experimental data. It is notable that the architecture we have found contradicts with the intuitive structure which is widely accepted.
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