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Computational approach to understanding Autism Spectrum Disorders

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
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.
Wydawca
Czasopismo
Rocznik
Strony
47--61
Opis fizyczny
Bibliogr. 28 poz., rys., wykr.
Twórcy
autor
  • Department of Informatics, Nicolaus Copernicus University, ul. Grudziądzka 5, 87-100, Toruń, Poland
autor
  • Institute of Physics, Nicolaus Copernicus University, ul. Grudziądzka 5, 87-100, Toruń, Poland
autor
  • Department of Informatics, Nicolaus Copernicus University, ul. Grudziądzka 5, 87-100, Toruń, Poland
autor
  • Department of Informatics, Nicolaus Copernicus University, ul. Grudziądzka 5, 87-100, Toruń, Poland
autor
  • Department of Informatics, Nicolaus Copernicus University, ul. Grudziądzka 5, 87-100, Toruń, Poland
  • Department of Informatics, Nicolaus Copernicus University, ul. Grudziądzka 5, 87-100, Toruń, Poland
  • Institute of Physics, Nicolaus Copernicus University, ul. Grudziądzka 5, 87-100, Toruń, Poland
Bibliografia
  • [1] Baron-Cohen S.: Autism: The empathizing-systemizing (e-s) theory. Annals of the New York Academy of Sciences, 1156:68–80, 2009.
  • [2] Baron-Cohen S., Scott F., Allison C., Williams J., Bolton P., Matthews F., Brayne C.: Prevalence of autism-spectrum conditions. UK school-based population study The British Journal of Psychiatry, 194(6):500–509, 2009.
  • [3] Bilder R. M., Sabb F. W., Cannon T. D., London E. D., Jentsch J. D., Parker D. S., Poldrack R. A., Evans C., Freimer N. B.: Phenomics: the systematic study of phenotypes on a genome-wide scale. Neuroscience, 164(1), 2009. 58 Włodzisław Duch, Wiesław Nowak, Jarosław Meller, et al.
  • [4] Bilder R. M., Sabb F. W., Parker D. S., Kalar D., Chu W. W., Fox J., Freimer N. B., Poldrack R. A.: Cognitive ontologies for neuropsychiatric phenomics research. Cognitive Neuropsychiatry, 14(4–5):419–450, 2009.
  • [5] Bower J., Beeman D.: The Book of Genesis – Exploring Realistic Neural Models with GEneral NEural SImulation System. Springer, 1998.
  • [6] Broyd S. J., Demanuele C., Debener S., Helps S. K., James C. J., Sonuga-Barke E. J.: Default-mode brain dysfunction in mental disorders: A systematic review. Neuroscience & biobehavioral reviews, 33:279–296, 2008.
  • [7] Casanova M. F.: The neuropathology of autism. Brain Pathology, 17:422–433, 2007.
  • [8] Clusterix.: Krajowy klaster linuksowy. http://www.clusterix.pcz.pl/, grudzien 2010.
  • [9] Dobosz K., Duch W.: Understanding neurodynamical systems via fuzzy symbolic dynamics. Neural Networks, 23(4):487–496, 2010.
  • [10] Duch W., Dobosz K.: Visualization for understanding of neurodynamical systems. Cognitive Neurodynamics, 5(2):145–160, 2011.
  • [11] Gepner B., Feron F.: Autism: A world changing too fast for a mis-wired brain? Neuroscience and Biobehavioral Reviews, 33(8):1227–1242, 2009.
  • [12] Geshwind D. H.: Autism: Many genes, common pathways? Cell, 135:391–395, 2008.
  • [13] Grossberg S., Seidman D.: Neural dynamics of autistic behaviors: cognitive, emotional, and timing substrates. Psychological Review, 113(3):483–525, 2006.
  • [14] Hodgkin A. L., Huxley A. F.: A quantitative description of membrane current and its application to conduction and excitation in nerve. Journal of Physiology, 117:500–544, 1952.
  • [15] Iacoboni M., Mazziotta J. C.: Mirror neuron system: basic findings and clinical applications. Ann Neurol, 62:213–218, 2007.
  • [16] Kaminski W. A.: Theoretical Neurocybernetics by Ryszard Tadeusiewicz, chapter Modelling of Single Neural Cells, pp. 75–86. Warsaw University Publishers, Warsaw, 2009.
  • [17] Kawakubo Y., Kasai K., Okazaki S., Hosokawa-Kakurai M., Watanabe K., Kuwabara H., Ishijima M., Yamasue H., Iwanami A., Kato N., Maekawa H.: Electrophysiological abnormalities of spatial attention in adults with autism during the gap overlap task. Clinical neurophysiology, 118(7):1464–1471, 2007.
  • [18] Landry L., Bryson S.: Impaired disengagement of attention in young children with autism. Journal of Child Psychology and Psychiatry, 45(6):1115–1122, 2004. Computational approach to understanding Autism Spectrum Disorders 59
  • [19] Muller R. A.: The study of autism as a distributed disorder. Mental Retardation and Developmental Disabilities Research Reviews, 13:85–95, 2007.
  • [20] O’Reilly R. C., Munakata Y.: Computational Explorations in Cognitive Neuroscience: Understanding the Mind by Simulating the Brain. MIT Press, Cambridge, Massachusetts, 2000.
  • [21] Pinto D., Pagnamenta A. T., Klei L., Anney R., Merico D., et al.: Functional impact of global rare copy number variation in autism spectrum disorders. Nature, 466(7304):368–372, 2010.
  • [22] PL-GRID.: The homepage of pl-grid project. http://www.plgrid.pl, December 2011.
  • [23] Tadeusiewicz R.: Theoretical Neurocybernetics. Warsaw University Publishers, Warsaw, 2009.
  • [24] Wallis F., Russell H. F., Muenke M.: Review: Genetics of attention deficit/ hyperactivity disorder. Journal of Pediatric Psychology, 33(10):1085–1099, 2008.
  • [25] Wojcik G. M.: Large simulations of mammalian visual system. In Science and Supercomputing in Europe, pp. 290–295. HPC-Europa Annual Project Directory, 2005.
  • [26] Wojcik G. M., Kaminski W. A.: Large scalable simulations of mammalian visual cortex. In Parallel Processing and Applied Mathematics, volume 3911 of Lecture Notes in Computer Science, pp. 399–405. Springer, 2005.
  • [27] Wojcik G. M., Kaminski W. A.: Grid-based simulations of mammalian visual system. In Proceedings of Cracow Grid Workshop 2005, pp. 384–389, 2006.
  • [28] Zimmerman A. W.: Autism: Current theories and evidence. Humana Press, Totowa, NJ, 2000.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-AGH1-0028-0202
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