Abstract
Information from the senses must be compressed into the limited range of responses that spiking neurons can generate. For optimal compression, the neuron's response should match the statistics of stimuli encountered in nature. Given a maximum firing rate, a nerve cell should learn to use each available firing rate equally often. Given a set mean firing rate, it should self-organize to respond with high firing rates only to comparatively rare events. Here we derive an unsupervised learning rule that continuously adapts membrane conductances of a Hodgkin-Huxley model neuron to optimize the representation of sensory information in the firing rate. Maximizing information transfer between the stimulus and the cell's firing rate can be interpreted as a non-Hebbian developmental mechanism.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
