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Statistical Analysis of Neuronal Spike Trains

  • Ronald J. MacGregor
  • Edwin R. Lewis

Abstract

Certain concepts from the information sciences have been particularly useful in helping describe nervous activity. One can picture the dynamical activity of a nervous network as consisting of a large number of ongoing simultaneous time series of events (spike trains) emerging from all the constituent cells. The output train of any particular cell reflects the ongoing input trains at each of some several hundred or even thousands of synapses. Various synapses are weighted in significance according to the strength of the metabolic transmitter apparatus and proximity to the soma. Whether or not one assumes that under some conditions certain components of the input or output patterns might be considered as “background noise” with respect to some other component which might comprise a “signal,” it is certainly clear that the methods and concepts of stochastic processes applied on an operational level can help to reveal many characteristics of neuroelectric events not readily apparent in other ways.

Keywords

Spike Train Firing Pattern Interspike Interval Neural Code Complex Spike 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Plenum Press, New York 1977

Authors and Affiliations

  • Ronald J. MacGregor
    • 1
  • Edwin R. Lewis
    • 2
  1. 1.University of ColoradoBoulderUSA
  2. 2.University of CaliforniaBerkeleyUSA

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