Temporal encoding in a nervous system

Zane N Aldworth; Alexander G Dimitrov; Graham I Cummins; Tomáš Gedeon; John P Miller

doi:10.1371/journal.pcbi.1002041

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Temporal encoding in a nervous system

Zane N Aldworth, Alexander G Dimitrov, Graham I Cummins, Tomáš Gedeon and John P Miller

PLoS computational biology, Vol.7(5), pp.e1002041-e1002041

05/2011

DOI: https://doi.org/10.1371/journal.pcbi.1002041

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https://hdl.handle.net/2376/112982

PMCID: PMC3088658

PMID: 21573206

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Abstract

Computational Biology

Linear Models

Action Potentials - physiology

Animals

Gryllidae - physiology

Information Theory

Time Factors

Computer Simulation

Nervous System Physiological Phenomena

Neurons - physiology

Female

Models, Neurological

Nonlinear Dynamics

We examined the extent to which temporal encoding may be implemented by single neurons in the cercal sensory system of the house cricket Acheta domesticus. We found that these neurons exhibit a greater-than-expected coding capacity, due in part to an increased precision in brief patterns of action potentials. We developed linear and non-linear models for decoding the activity of these neurons. We found that the stimuli associated with short-interval patterns of spikes (ISIs of 8 ms or less) could be predicted better by second-order models as compared to linear models. Finally, we characterized the difference between these linear and second-order models in a low-dimensional subspace, and showed that modification of the linear models along only a few dimensions improved their predictive power to parity with the second order models. Together these results show that single neurons are capable of using temporal patterns of spikes as fundamental symbols in their neural code, and that they communicate specific stimulus distributions to subsequent neural structures.

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Details

Title: Temporal encoding in a nervous system
Creators: Zane N Aldworth - Center for Computational Biology, Montana State University, Bozeman, Montana, United States of America. zane.aldworth@nih.gov
Alexander G Dimitrov
Graham I Cummins
Tomáš Gedeon
John P Miller
Publication Details: PLoS computational biology, Vol.7(5), pp.e1002041-e1002041
Academic Unit: Mathematics and Statistics, Department of
Publisher: United States
Grant note: R01 MH064416 / NIMH NIH HHS 2R01 MH-064416 / NIMH NIH HHS
Identifiers: 99900547972801842
Language: English
Resource Type: Journal article