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Contrast Adaptation in Simple Cells by Changing the Transmitter Release Probability

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. (i) Fast synaptic depression leads to saturation of the CRF and phase advance in the cortical response to high contrast stimuli. (ii) Slow adaptation of the synaptic transmitter release probability is derived such that the mutual information between the input and the output of a cortical neuron is maximal. This component--given by infomax learning rule--explains contrast adaptation of the averaged membrane potential (DC component) as well as the surprising experimental result, 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 experiment 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.