The neuron as a population of ion channels -
the emergence of stochastic and history dependent behavior.
The classic view of a neuron as a point element, combining a large number of small synaptic currents, and comparing the sum to a fixed threshold, is becoming more difficult to sustain given the plethora of non-linear regenerative processes known to take place in the soma, axon and even the dendritic tree. Since a common source for the complexity in the input, soma and output is the behavior of ionic channels, we propose a view of a neuron as a population of channels.
Analyzing the stochastic nature of ion channels using recently developed mathematical model, we provide a rather general characterization of the input output relation of the neuron, which admits a surprising level of analytic tractability.
The view developed provides a clear quantitative explanation to history-dependent effects in neurons and of the observed irregularity in firing. Interestingly, the present explanation of firing irregularity does not require a globally balanced state, but, rather, results from the intrinsic properties of a single neuron.