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PubMed · 2063199

Reading a neural code.

W Bialek·F Rieke·R R de Ruyter van Steveninck·D Warland
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Abstract

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.

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AlgorithmsAnimalsDipteraMathematicsModels, NeurologicalNeuronsNeurons, AfferentPhotoreceptor CellsVisual PerceptionJournal ArticleResearch Support, Non-U.S. Gov'tResearch Support, U.S. Gov't, Non-P.H.S.Research Support, U.S. Gov't, P.H.S.

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W Bialek, F Rieke, R R de Ruyter van Steveninck, D Warland. 1991-06-28. Reading a neural code.. https://doi.org/10.1126/science.2063199

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