Complexity in neuronal networks.

Yves Frégnac, Michelle Rudolph, Andrew P. Davison and Alain Destexhe

In: Biological Networks, Edited by Kepes, F. World Scientific, Singapore, pp. 291-340 (2007).

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Abstract

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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