Computational Approach To Understanding Autism Spectrum Disorders

Every year the prevalence of Autism Spectrum of Disorders (ASD) is rising. Is there a unifying mechanism of various ASD cases at the genetic, molecular, cellular or systems level? The hypothesis advanced in this paper is focused on neural dysfunctions that lead to problems with attention in autistic...

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Bibliographic Details
Main Authors: Włodzisław Duch, Wiesław Nowak, Jaroslaw Meller, Grzegorz Osiński, Krzysztof Dobosz, Dariusz Mikołajewski, Grzegorz Marcin Wójcik
Format: Article
Language:English
Published: AGH University of Science and Technology Press 2012-01-01
Series:Computer Science
Subjects:
ASD
Online Access:http://journals.agh.edu.pl/csci/article/download/12/6
Description
Summary:Every year the prevalence of Autism Spectrum of Disorders (ASD) is rising. Is there a unifying mechanism of various ASD cases at the genetic, molecular, cellular or systems level? The hypothesis advanced in this paper is focused on neural dysfunctions that lead to problems with attention in autistic people. Simulations of attractor neural networks performing cognitive functions help to assess system long-term neurodynamics. The Fuzzy Symbolic Dynamics (FSD) technique is used for the visualization of attractors in the semantic layer of the neural model of reading. Large-scale simulations of brain structures characterized by a high order of complexity requires enormous computational power, especially if biologically motivated neuron models are used to investigate the influence of cellular structure dysfunctions on the network dynamics. Such simulations have to be implemented on computer clusters in a grid-based architectures
ISSN:1508-2806