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Noise and neuronal populations conspire to encode simple waveforms reliablySensory systems rely on populations of neurons to encode information transduced at the periphery into meaningful patterns of neuronal population activity. This transduction occurs in the presence of intrinsic neuronal noise. This is fortunate. The presence of noise allows more reliable encoding of the temporal structure present in the stimulus than would be possible in a noise-free environment. Simulations with a parallel model of signal processing at the auditory periphery have been used to explore the effects of noise and a neuronal population on the encoding of signal information. The results show that, for a given set of neuronal modeling parameters and stimulus amplitude, there is an optimal amount of noise for stimulus encoding with maximum fidelity.
Document ID
20040173263
Acquisition Source
Legacy CDMS
Document Type
Reprint (Version printed in journal)
External Source(s)
Authors
Parnas, B. R.
(NASA Ames Research Center Moffett Field, CA United States)
Date Acquired
August 22, 2013
Publication Date
March 1, 1996
Publication Information
Publication: IEEE transactions on bio-medical engineering
Volume: 43
Issue: 3
ISSN: 0018-9294
Subject Category
Life Sciences (General)
Distribution Limits
Public
Copyright
Other

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