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Point process models of single-neuron discharges

Point process models of single-neuron discharges In most neural systems, neurons communicate via sequences of action potentials. Contemporary models assume that the action potentials' times of occurrence rather than their waveforms convey information. The mathematical tool for describing sequences of events occurring in time and/or space is the theory of point processes. Using this theory, we show that neural discharge patterns convey time-varying information intermingled with the neuron's response characteristics. We review the basic techniques for analyzing single-neuron discharge patterns and describe what they reveal about the underlying point process model. By applying information theory and estimation theory to point processes, we describe the fundamental limits on how well information can be represented by and extracted from neural discharges. We illustrate applying these results by considering recordings from the lower auditory pathway. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Computational Neuroscience Springer Journals

Point process models of single-neuron discharges

Johnson, Don
Journal of Computational Neuroscience , Volume 3 (4) – Jun 26, 2004
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References (50)

Publisher
Springer Journals
Copyright
Copyright
Subject
Biomedicine; Neurosciences; Neurology; Human Genetics; Theory of Computation
ISSN
0929-5313
eISSN
1573-6873
DOI
10.1007/BF00161089
Publisher site
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Abstract

In most neural systems, neurons communicate via sequences of action potentials. Contemporary models assume that the action potentials' times of occurrence rather than their waveforms convey information. The mathematical tool for describing sequences of events occurring in time and/or space is the theory of point processes. Using this theory, we show that neural discharge patterns convey time-varying information intermingled with the neuron's response characteristics. We review the basic techniques for analyzing single-neuron discharge patterns and describe what they reveal about the underlying point process model. By applying information theory and estimation theory to point processes, we describe the fundamental limits on how well information can be represented by and extracted from neural discharges. We illustrate applying these results by considering recordings from the lower auditory pathway.

Journal

Journal of Computational Neuroscience – Springer Journals

Published: Jun 26, 2004

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