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Computational Methods of Neuronal Network Decomposition

  • Robert J. Sclabassi
  • Bogdan R. Kosanović
  • German Barrionuevo
  • Theodore W. Berger

Abstract

The hippocampal formation is a widely studied neuronal network involved in learning and memory formation and is composed of multiple feedforward and feedback loops which lend themselves to study through the use of systems theory In this approach, the network properties are characterized as the composite of input/output functions measured for each subsystem in the network. The characterizing functions are thekernels of a functional power series, and as such capture both the linear and nonlinear characteristics of the transformational processes associated with this network. This paper reviews the development of the functional power series approach to studying the hippocampal formation, summarizes experimental data which demonstrates the nonlinear nature of the hippocampal formation for both in-vivo and in-vitro preChapautions, and utilizes this data to explore the decomposition problem. An example is presented which computes the transformational properties of the basket cells in the granule cell layer.

Keywords

Granule Cell Dentate Gyrus Hippocampal Formation Granule Cell Layer Population 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

© Springer Science+Business Media New York 1994

Authors and Affiliations

  • Robert J. Sclabassi
    • 1
  • Bogdan R. Kosanović
    • 2
  • German Barrionuevo
    • 3
  • Theodore W. Berger
    • 4
  1. 1.Departments of Neurological Surgery, Electrical Engineering, Behavioral Neuroscience and PsychiatryUniversity of PittsburghUSA
  2. 2.Department of Electrical EngineeringUniversity of PittsburghUSA
  3. 3.Departments of Behavioral Neuroscience and PsychiatryUniversity of PittsburghUSA
  4. 4.Departments of Biomedical Engineering and Biological SciencesUniversity of Southern CaliforniaUSA

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