How voltage-dependent conductances can adapt to maximize the information encoded by neuronal firing rate

Information from the senses must be compressed into the limited range of re sponses that spiking neurons can generate. For optimal compression, the neu ron's response should match the statistics of stimuli encountered in nature . Given a maximum firing rate, a nerve cell should learn to use each availa ble firing rate equally often. Given a set mean firing rate, it should self -organize to respond with high firing rates only to comparatively rare even ts. Here we derive an unsupervised learning rule that continuously adapts m embrane conductances of a Hodgkin-Huxley model neuron to optimize the repre sentation of sensory information in the firing rate. Maximizing information transfer between the stimulus and the cell's firing rate can be interprete d as a non-Hebbian developmental mechanism.