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Journal Article

Noise, not stimulus entropy, determines neural information rate

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Borst,  A.
Department: Systems and Computational Neurobiology / Borst, MPI of Neurobiology, Max Planck Society;

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Citation

Borst, A. (2003). Noise, not stimulus entropy, determines neural information rate. Journal of Computational Neuroscience, 14(1), 23-31. doi:10.1023/A:1021172200868.


Cite as: https://hdl.handle.net/11858/00-001M-0000-0012-2335-E
Abstract
In the quest for deciphering the neural code, theoretical advances were made which allow for the determination of the information rate inherent in the spike trains of nerve cells. However, up to now, the dependence of the information rate on stimulus parameters has not been studied in any neuron in a systematic way. Here, I investigate the information carried by the spike trains of H1, a motion- sensitive visual interneuron of the blowfly (Calliphora vicina) using a moving grating as a stimulus. Stimulus parameters fall in two classes: those that have only a minor effect on the information rate like increasing the frequency bandwidth or the maximum amplitude of the stimulus velocity, and those which dramatically affect the neural information rate, like varying the spatial size or the contrast of the visual pattern being moved. It appears that, for a broad range of complex stimuli, the neuron covers the stimulus with its whole response repertoire regardless of the stimulus entropy, with the information rate being limited by the noise of the stimulus and the neural hardware.