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Analysis of between-trial and within-trial neural spiking dynamics
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Czanner, Gabriela, Eden, Uri T., Wirth, Sylvia, Yanike, Marianna, Suzuki, Wendy A. and Brown, E. N. (Emery N.) (2008) Analysis of between-trial and within-trial neural spiking dynamics. Journal of Neurophysiology, Vol.99 (No.5). pp. 2672-2693. doi:10.1152/jn.00343.2007
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Official URL: http://dx.doi.org/10.1152/jn.00343.2007
Abstract
Recording single-neuron activity from a specific brain region across multiple trials in response to the same stimulus or execution of the same behavioral task is a common neurophysiology protocol. The raster plots of the spike trains often show strong between-trial and within-trial dynamics, yet the standard analysis of these data with the peristimulus time histogram (PSTH) and ANOVA do not consider between-trial dynamics. By itself, the PSTH does not provide a framework for statistical inference. We present a state-space generalized linear model (SS-GLM) to formulate a point process representation of between-trial and within-trial neural spiking dynamics. Our model has the PSTH as a special case. We provide a framework for model estimation, model selection, goodness-of-fit analysis, and inference. In an analysis of hippocampal neural activity recorded from a monkey performing a location-scene association task, we demonstrate how the SS-GLM may be used to answer frequently posed neurophysiological questions including, What is the nature of the between-trial and within-trial task-specific modulation of the neural spiking activity? How can we characterize learning-related neural dynamics? What are the timescales and characteristics of the neuron's biophysical properties? Our results demonstrate that the SS-GLM is a more informative tool than the PSTH and ANOVA for analysis of multiple trial neural responses and that it provides a quantitative characterization of the between-trial and within-trial neural dynamics readily visible in raster plots, as well as the less apparent fast (1-10 ms), intermediate (11-20 ms), and longer (>20 ms) timescale features of the neuron's biophysical properties.
| Item Type: | Journal Article | ||||
|---|---|---|---|---|---|
| Subjects: | R Medicine > RC Internal medicine > RC0321 Neuroscience. Biological psychiatry. Neuropsychiatry Q Science > QP Physiology |
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| Divisions: | Faculty of Science > Statistics | ||||
| Library of Congress Subject Headings (LCSH): | Neural networks (Neurobiology), Sensory neurons | ||||
| Journal or Publication Title: | Journal of Neurophysiology | ||||
| Publisher: | American Physiological Society | ||||
| ISSN: | 0022-3077 | ||||
| Official Date: | May 2008 | ||||
| Dates: |
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| Volume: | Vol.99 | ||||
| Number: | No.5 | ||||
| Number of Pages: | 22 | ||||
| Page Range: | pp. 2672-2693 | ||||
| DOI: | 10.1152/jn.00343.2007 | ||||
| Status: | Peer Reviewed | ||||
| Publication Status: | Published | ||||
| Access rights to Published version: | Restricted or Subscription Access | ||||
| Funder: | National Institutes of Health (U.S.) (NIH), McKnight Foundation, National Science Foundation (U.S.) (NSF), Fondation pour la recherche médicale | ||||
| Grant number: | DA- 015644 (NIH), MH-59733 (NIH), MH-58847 (NIH), IIS-0643995 (NSF) |
Data sourced from Thomson Reuters' Web of Knowledge
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