Stability and Synchronization in Neural Fields - INRIA - Institut National de Recherche en Informatique et en Automatique Access content directly
Reports (Research Report) Year : 2007

Stability and Synchronization in Neural Fields

Olivier Faugeras
François Grimbert
  • Function : Author
  • PersonId : 840532

Abstract

Neural fields are an interesting option for modelling macroscopic parts of the cortex involving several populations of neurons, like cortical areas. Two classes of neural field equations are considered: voltage and activity based. The spatio-temporal behaviour of these fields is described by nonlinear integro-differential equations. The integral term, computed over a compact subset of $\mathbb{R}^q,\,q=1,2,3$, involves space and time varying, possibly non-symmetric, intra-cortical connectivity kernels. Contributions from white matter afferents are represented as external input. Sigmoidal nonlinearities arise from the relation between average membrane potentials and instantaneous firing rates. Using methods of functional analysis, we characterize the existence and uniqueness of a solution of these equations for general, homogeneous (i.e. independent of the spatial variable), and locally homogeneous inputs. In all cases we give sufficient conditions on the connectivity functions for the solutions to be absolutely stable, that is to say independent of the initial state of the field. These conditions bear on some compact operators defined from the connectivity kernels, the sigmoids, and the time constants used in describing the temporal shape of the post-synaptic potentials. Numerical experiments are presented to illustrate the theory. An important contribution of our work is the application of the theory of compact operators in a Hilbert space to the problem of neural fields with the effect of providing very simple mathematical answers to the questions asked by neuroscience modellers.
Fichier principal
Vignette du fichier
squelette-rr.pdf (844.54 Ko) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

inria-00153052 , version 1 (08-06-2007)
inria-00153052 , version 2 (11-06-2007)

Identifiers

  • HAL Id : inria-00153052 , version 1

Cite

Olivier Faugeras, François Grimbert, Jean-Jacques Slotine. Stability and Synchronization in Neural Fields. [Research Report] 2007. ⟨inria-00153052v1⟩
236 View
184 Download

Share

Gmail Facebook X LinkedIn More