Infinite Dimensional Stochastic Differential Equation Models for Spatially Distributed Neurons.

Abstract

The membrane potential of spatially distributed neurons is modelled as a random field driven by a generalized Poisson process. Approximation to an Ornstein-Uhlenbeck type process is established in the sense of weak convergence of the induced measures in Skorokhod space. (Author)

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Document Details

Document Type
Technical Report
Publication Date
May 01, 1983
Accession Number
ADA136507

Entities

People

  • G. Kallianpur
  • R. Wolpert

Organizations

  • University of North Carolina at Chapel Hill

Tags

DTIC Thesaurus Topics

  • Cell Membrane
  • Cells
  • Cellular Structures
  • Differential Equations
  • Eigenvalues
  • Electrical Properties
  • Equations
  • Fokker Planck Equations
  • Gaussian Processes
  • Hilbert Space
  • Membrane Potentials
  • Neurons
  • Partial Differential Equations
  • Probability
  • Random Variables
  • Stochastic Processes
  • Weak Convergence

Fields of Study

  • Biology
  • Mathematics

Readers

  • Mathematical Modeling and Probability Theory.
  • Neuroscience

Technology Areas

  • Space