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TY  - BOOK
ID  - 4794688
TI  - Computational Neuroscience
AU  - Chaovalitwongse, Wanpracha
AU  - Pardalos, Panos M
AU  - Xanthopoulos, Petros
AU  - SpringerLink (Online service)
PY  - 2010
SN  - 9780387886305 9780387886299
PB  - New York NY  Springer New York Imprint Springer
DB  - UniCat
KW  - Mathematics.
KW  - Computational Mathematics and Numerical Analysis.
KW  - Neurosciences.
KW  - Biomedical Engineering.
KW  - Mathematical Modeling and Industrial Mathematics.
KW  - Computer science
KW  - Biomedical engineering.
KW  - Mathématiques
KW  - Neurosciences
KW  - Informatique
KW  - Génie biomédical
KW  - Computational neuroscience.
KW  - Computersimulation.
KW  - Neurowissenschaften.
KW  - Computational Biology.
KW  - Models, Neurological.
KW  - methods.
KW  - Methods.
UR  - https://www.unicat.be/uniCat?func=search&query=sysid:4794688
AB  - The human brain is among the most complex systems known to mankind. Neuroscientists seek to understand brain function through detailed analysis of neuronal excitability and synaptic transmission. Only in the last few years has it become feasible to capture simultaneous responses from a large enough number of neurons to empirically test the theories of human brain function computationally. This book is comprised of state-of-the-art experiments and computational techniques that provide new insights and improve our understanding of the human brain. This volume includes contributions from diverse disciplines including electrical engineering, biomedical engineering, industrial engineering, and medicine, bridging a vital gap between the mathematical sciences and neuroscience research. Covering a wide range of research topics, this volume demonstrates how various methods from data mining, signal processing, optimization and cutting-edge medical techniques can be used to tackle the most challenging problems in modern neuroscience. The results presented in this book are of great interest and value to scientists, graduate students, researchers and medical practitioners interested in the most recent developments in computational neuroscience.
ER  -