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Chaotic itinerancy and its roles in cognitive neurodynamics
1Research Institute for Electronic Science, Hokkaido University, Kita-12, Nishi-7, Kita-ku, Sapporo, Hokkaido 060-0012, Japan.
Current Opinion in Neurobiology
|September 15, 2014
Summary
Chaotic itinerancy describes brain activity trajectories that generate sequences of quasi-attractors, representing thoughts and memories. This model explains intelligent search and cognitive processes like thinking and speaking.
Area of Science:
- Computational Neuroscience
- Cognitive Dynamics
- Complex Systems
Background:
- Cortical neural activity exhibits complex, high-dimensional dynamics.
- Understanding the mechanisms underlying cognitive processes like perception and memory is crucial.
- Existing models may not fully capture the sequential and exploratory nature of cognition.
Purpose of the Study:
- To introduce and define chaotic itinerancy as a model for cortical neural activity.
- To elucidate the role of quasi-attractors in representing cognitive states.
- To explain how chaotic trajectories facilitate intelligent search and cognitive sequencing.
Main Methods:
- Theoretical modeling of high-dimensional state space dynamics.
- Analysis of autonomous trajectories and quasi-attractor formation.
- Conceptual framework linking neurodynamics to cognitive functions.
Main Results:
- Chaotic itinerancy generates temporal sequences of quasi-attractors.
- Quasi-attractors represent ordered cognitive states (perceptions, thoughts, memories).
- Chaotic trajectories between quasi-attractors model intelligent, history-dependent search and exploration.
Conclusions:
- Chaotic itinerancy provides a neurodynamic framework for understanding cognitive sequencing.
- This model explains the interplay between ordered (quasi-attractor) and disordered (chaotic) neural activity.
- Itinerancy offers insights into the mechanisms of thinking, speaking, and writing.
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