Accession Number:

ADA159099

Title:

Stochastic Differential Equations for Neuronal Behavior.

Descriptive Note:

Technical rept.,

Corporate Author:

NORTH CAROLINA UNIV AT CHAPEL HILL CENTER FOR STOCHASTIC PROCESSES

Personal Author(s):

Report Date:

1985-06-01

Pagination or Media Count:

44.0

Abstract:

This article extends the recent work of Kallianpur and Wolpert modeling the behavior of neurons by means of stochastic partial differential equations on the dual of a nuclear space. The extensions will cover nuclear spaces of a more general structure and will apply to models described in terms of more general differential operators. A second objective of this article is to present a theoretical framework which will include the model recently proposed and heuristically investigated by Wan and Tuckwell. The authors illustrate their approach and its application by giving a rigorous treatment of the Wan and Tuckwell model. But first they briefly describe the neurophysiological context. Additional keywords Voltage potential Weak convergence Mathematical models Theorems. Author

Subject Categories:

  • Anatomy and Physiology

Distribution Statement:

APPROVED FOR PUBLIC RELEASE