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Identifying Temporal Codes in Spontaneously Active Sensory Neurons

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  • Alexander B Neiman
  • David F Russell
  • Michael H Rowe

Abstract

The manner in which information is encoded in neural signals is a major issue in Neuroscience. A common distinction is between rate codes, where information in neural responses is encoded as the number of spikes within a specified time frame (encoding window), and temporal codes, where the position of spikes within the encoding window carries some or all of the information about the stimulus. One test for the existence of a temporal code in neural responses is to add artificial time jitter to each spike in the response, and then assess whether or not information in the response has been degraded. If so, temporal encoding might be inferred, on the assumption that the jitter is small enough to alter the position, but not the number, of spikes within the encoding window. Here, the effects of artificial jitter on various spike train and information metrics were derived analytically, and this theory was validated using data from afferent neurons of the turtle vestibular and paddlefish electrosensory systems, and from model neurons. We demonstrate that the jitter procedure will degrade information content even when coding is known to be entirely by rate. For this and additional reasons, we conclude that the jitter procedure by itself is not sufficient to establish the presence of a temporal code.

Suggested Citation

  • Alexander B Neiman & David F Russell & Michael H Rowe, 2011. "Identifying Temporal Codes in Spontaneously Active Sensory Neurons," PLOS ONE, Public Library of Science, vol. 6(11), pages 1-13, November.
  • Handle: RePEc:plo:pone00:0027380
    DOI: 10.1371/journal.pone.0027380
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    References listed on IDEAS

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    1. Ilya Nemenman & Geoffrey D Lewen & William Bialek & Rob R de Ruyter van Steveninck, 2008. "Neural Coding of Natural Stimuli: Information at Sub-Millisecond Resolution," PLOS Computational Biology, Public Library of Science, vol. 4(3), pages 1-12, March.
    2. Zane N Aldworth & Alexander G Dimitrov & Graham I Cummins & Tomáš Gedeon & John P Miller, 2011. "Temporal Encoding in a Nervous System," PLOS Computational Biology, Public Library of Science, vol. 7(5), pages 1-19, May.
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    Cited by:

    1. Christoph Bauermeister & Tilo Schwalger & David F Russell & Alexander B Neiman & Benjamin Lindner, 2013. "Characteristic Effects of Stochastic Oscillatory Forcing on Neural Firing: Analytical Theory and Comparison to Paddlefish Electroreceptor Data," PLOS Computational Biology, Public Library of Science, vol. 9(8), pages 1-16, August.

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