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Variability and coding efficiency of noisy neural spike encoders

Steinmetz, Peter N. and Manwani, Amit and Koch, Christof (2001) Variability and coding efficiency of noisy neural spike encoders. Biosystems, 62 (1-3). pp. 87-97. ISSN 0303-2647. doi:10.1016/S0303-2647(01)00139-3.

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Encoding synaptic inputs as a train of action potentials is a fundamental function of nerve cells. Although spike trains recorded in vivo have been shown to be highly variable, it is unclear whether variability in spike timing represents faithful encoding of temporally varying synaptic inputs or noise inherent in the spike encoding mechanism. It has been reported that spike timing variability is more pronounced for constant, unvarying inputs than for inputs with rich temporal structure. This could have significant implications for the nature of neural coding, particularly if precise timing of spikes and temporal synchrony between neurons is used to represent information in the nervous system. To study the potential functional role of spike timing variability, we estimate the fraction of spike timing variability which conveys information about the input for two types of noisy spike encoders — an integrate and fire model with randomly chosen thresholds and a model of a patch of neuronal membrane containing stochastic Na+ and K+ channels obeying Hodgkin–Huxley kinetics. The quality of signal encoding is assessed by reconstructing the input stimuli from the output spike trains using optimal linear mean square estimation. A comparison of the estimation performance of noisy neuronal models of spike generation enables us to assess the impact of neuronal noise on the efficacy of neural coding. The results for both models suggest that spike timing variability reduces the ability of spike trains to encode rapid time-varying stimuli. Moreover, contrary to expectations based on earlier studies, we find that the noisy spike encoding models encode slowly varying stimuli more effectively than rapidly varying ones.

Item Type:Article
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URLURL TypeDescription
Koch, Christof0000-0001-6482-8067
Additional Information:© 2001 Elsevier Science. This work was funded by NSF, NIMH and the Sloan Center for Theoretical Neuroscience at Caltech. We would like to thank our collaborators Michael London, Elad Schneidman and Idan Segev for their invaluable suggestions.
Group:Koch Laboratory (KLAB)
Funding AgencyGrant Number
Sloan Center for Theoretical NeuroscienceUNSPECIFIED
Subject Keywords:Integrate-and-fire models; Hodgkin–Huxley model; Stochastic ion channels; Neuronal variability; Signal estimation
Issue or Number:1-3
Record Number:CaltechAUTHORS:20130816-103229923
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Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:40521
Deposited By: KLAB Import
Deposited On:11 Jan 2008 20:04
Last Modified:09 Nov 2021 23:49

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