Dynamics of Noisy Neural Nets with Chemical Markers and Gaussian-distributed Connectivities

Abstract

We have previously investigated the dynamics of probabilistic neural nets with chemical markers and Gaussian distribution of connectivities of the constituent neurons. These investigations have shown that the change from a Poisson to a Gaussian distribution may cause a net to change class. We have now generalized these studies by considering the intrinsic noise of the systems, caused by the spontaneous release of synaptic transmitter substance. A simple mathematical model is developed, the dynamics of which is compared with the Poisson model.

Keywords:

• Keywords: Neural Models
• Chemical Markers
• Gaussian-Poisson Distributions