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Abstract:
The contrast response function (CRF) of many neurons in the
primary visual cortex saturates, and shifts towards higher contrast
values following prolonged presentation of high contrast visual
stimuli. Using a recurrent neural network of excitatory spiking
neurons with adapting synapses we show that both effects could be
explained by a fast and a slow component in the synaptic
adaptation. The fast component---a short term synaptic depression
component---leads to a saturation of the CRF and a phase advance in
the cortical cells' response to high contrast stimuli. The slow
component is derived from an adaptation of the probability of the
synaptic transmitter release, and changes such that the mutual
information between the input and the output of a cortical neuron
is maximal. This component---given by the infomax learning
rule---explains contrast adaptation of the averaged membrane
potential (DC component) as well as the surprising experimental
results, that the stimulus modulated component (F1 component) of a
cortical cell's membrane potential adapts only weakly. Based on our
results we propose a new experimental method to estimate the
strength of the effective excitatory feedback to a cortical neuron,
and we also suggest a relatively simple experimental test to
justify our hypothesized synaptic mechanism for contrast
adaptation.
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