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Spatiotemporal multi-resolution approximation of the Amari type neural field model.

Identifieur interne : 001024 ( Ncbi/Curation ); précédent : 001023; suivant : 001025

Spatiotemporal multi-resolution approximation of the Amari type neural field model.

Auteurs : P. Aram [Royaume-Uni] ; D R Freestone [Australie] ; M. Dewar [États-Unis] ; K. Scerri [Malte] ; V. Jirsa [France] ; D B Grayden [Australie] ; V. Kadirkamanathan [Royaume-Uni]

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RBID : pubmed:23116813

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Abstract

Neural fields are spatially continuous state variables described by integro-differential equations, which are well suited to describe the spatiotemporal evolution of cortical activations on multiple scales. Here we develop a multi-resolution approximation (MRA) framework for the integro-difference equation (IDE) neural field model based on semi-orthogonal cardinal B-spline wavelets. In this way, a flexible framework is created, whereby both macroscopic and microscopic behavior of the system can be represented simultaneously. State and parameter estimation is performed using the expectation maximization (EM) algorithm. A synthetic example is provided to demonstrate the framework.

DOI: 10.1016/j.neuroimage.2012.10.039
PubMed: 23116813

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