Abstract: Publisher SummaryThis chapter introduces a book that discusses several issues associated with computational neuroscience. Computational approaches have become an increasingly prominent and influential part of neuroscience research. From the cellular mechanisms of synaptic transmission and the generation of action potentials, to interactions among networks of neurons, and to the high-level processes of perception and memory, computational models provide new sources of insight into the complex machinery that underlies human behavior. These models are not merely mathematical surrogates for experimental data. More importantly, they help in clarifying a particular nervous system process or function, guide the design of experiments, and help in expressing hypotheses in a language of mathematical formalisms. A mathematical model is an explicit hypothesis in which one must incorporate all the beliefs and assumptions in a rigorous and coherent conceptual framework that is subject to falsification and modification. Furthermore, a successful computational model is a rich source of predictions for future experiments. Even a simplified computational model can offer insights that unify phenomena across different levels of analysis, linking cells to networks and networks to behavior.
Publication Year: 2007
Publication Date: 2007-01-01
Language: en
Type: book-chapter
Indexed In: ['crossref']
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