Reliability and information transmission in spiking neurons

Abstract

Spiking neurons encode continuous, time-varying signals in sequences of identical action potentials. Relatively simple algorithms allow one to 'decode' this neural representation of sensory data to estimate the input signals. Decoding experiments provide a quantitative characterization of information transmission and computational reliability under real-time conditions. The results of these studies show that neural coding and computation in several systems approach fundamental physical and informational theoretic limits to performance.