Computational modeling of neuronal map development: insights into disease

Simpson, Hugh D., Giacomantonio, Clare and Goodhill, Geoffrey J. (2011) Computational modeling of neuronal map development: insights into disease. Future Neurology, 6 3: 339-349. doi:10.2217/fnl.11.10

Author Simpson, Hugh D.
Giacomantonio, Clare
Goodhill, Geoffrey J.
Title Computational modeling of neuronal map development: insights into disease
Journal name Future Neurology   Check publisher's open access policy
ISSN 1479-6708
Publication date 2011-05
Sub-type Article (original research)
DOI 10.2217/fnl.11.10
Volume 6
Issue 3
Start page 339
End page 349
Total pages 11
Place of publication London, United Kingdom
Publisher Future Medicine
Collection year 2012
Language eng
Abstract The study of the formation of neuronal maps in the brain has greatly increased our understanding of how the brain develops and, in some cases, regenerates. Computational modeling of neuronal map development has been invaluable in integrating complex biological phenomena and synthesizing them into quantitative and predictive frameworks. These models allow us to investigate how neuronal map development is perturbed under conditions of altered development, disease and regeneration. In this article, we use examples of activity-dependent and activity-independent models of retinotopic map formation to illustrate how they can aid our understanding of developmental and acquired disease processes. We note that fully extending these models to specific clinically relevant problems is a largely unexplored domain and suggest future work in this direction. We argue that this type of modeling will be necessary in furthering our understanding of the pathophysiology of neurological diseases and in developing treatments for them. Furthermore, we discuss how the nature of computational and theoretical approaches uniquely places them to bridge the gap between the bench and the clinic.
Keyword Computational modeling
Developmental neuroscience
Neural map
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: School of Mathematics and Physics
Queensland Brain Institute Publications
Official 2012 Collection
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Created: Fri, 04 Nov 2011, 11:15:33 EST by Debra McMurtrie on behalf of Queensland Brain Institute