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.
Bialek
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Department of Physics, University of California, Berkeley 94720.
Rieke
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de Ruyter van Steveninck
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Warland
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D
D000465:Algorithms; D000818:Animals; D004175:Diptera; D008433:Mathematics; D008959:Models, Neurological; D009474:Neurons / Q000502:physiology*; D009475:Neurons, Afferent / Q000502:physiology*; D010786:Photoreceptor Cells / Q000502:physiology; D014796:Visual Perception