Complexity in neuronal networks.
Yves Frégnac, Michelle Rudolph, Andrew P. Davison and
In: Biological Networks, Edited by Kepes, F. World
Scientific, Singapore, pp. 291-340 (2007).
The central nervous system, and cerebral cortex in particular, is a
highly complex system. Usually, this complexity is avoided, by
designing computational models or theories involving simple and
stereotyped neurons. Here, we argue that this complexity may be
important for understanding cortical computations. We review some
aspects of this complexity at multiple scales, cellular, synaptic and
network levels. We suggest that maximizing complexity may be a
characteristic of cerebral cortex, which may be fundamental for the
type of computations it performs. Progress in the study of complex
systems may provide the right tools to theoretical neuroscience for
understanding cortical computations.
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