A Complex Systems Approach to an Interpretation of Dynamic Brain Activity Ⅰ: Chaotic Itinerancy Can Provide a Mathematical Basis for Information Processing in Cortical Transitory and Nonstationary Dynamics

摘要

The transitory activity of neuron assemblies has been observed in various areas of animal and human brains. We here highlight some typical transitory dynamics observed in laboratory experiments and provide a dynamical systems interpretation of such behaviors. Using the information theory of chaos, it is shown that a certain type of chaos is capable of dynamically maintaining the input information rather than destroying it. Taking account of the fact that the brain works in a noisy environment, the hypothesis can be proposed that chaos exhibiting noise-induced order is appropriate for the representation of the dynamics concerned. The transitory dynamics typically observed in the brain seems to appear in high-dimensional systems. A new dynamical systems interpretation for the cortical dynamics is reviewed, cast in terms of high-dimensional transitory dynamics. This interpretation differs from the conventional one, which is usually cast in terms of low-dimensional attractors. We focus our attention on, in particular, chaotic itinerancy, a dynamic concept describing transitory dynamics among "exotic attractors" , or "attractor ruins". We also emphasize the functional significance of chaotic itinerancy.