F Rieke | PubMed Health

PubMed1992

Reliability and information transmission in spiking neurons.

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.

Action Potentials↗

PubMed1991

Reading a neural code.

Traditional approaches to neural coding characterize the encoding of known stimuli in average neural responses. Organisms face nearly the opposite task--extracting information about an unknown time-dependent stimulus from short segments of a spike train. Here the neural code was characterized from the point of view of the organism, culminating in algorithms for real-time stimulus estimation based on a single example of the spike train. These methods were applied to an identified movement-sensitive neuron in the fly visual system. Such decoding experiments determined the effective noise level and fault tolerance of neural computation, and the structure of the decoding algorithms suggested a simple model for real-time analog signal processing with spiking neurons.

Algorithms↗