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Updated: May 27, 2026
08:36
Dynamic Inter-subject Functional Connectivity Reveals Moment-to-Moment Brain Network Configurations Driven by Continuous or Communication Paradigms
Published on: March 21, 2019
Information flow dynamics in the brain.
Mikhail I Rabinovich1, Valentin S Afraimovich, Christian Bick
1BioCircuits Institute, University of California San Diego, 9500 Gilman Dr 0328, La Jolla, CA 92093-0328, United States. mrabinovich@ucsd.edu
Physics of Life Reviews
|November 29, 2011
Summary
This review explores brain information dynamics, focusing on temporal evolution for cognitive functions. Understanding information flow stability is key to cognitive health and disorders.
Area of Science:
- Neuroscience
- Cognitive Science
- Information Theory
Background:
- The temporal dynamics of brain information are crucial for understanding cognition in health and disease.
- Classical information theory is algebraic, while brain information dynamics considers flow stability, timing, and control.
Purpose of the Study:
- To review brain information dynamics concerning working memory, language, and goal-dependent behaviors.
- To explore the relationship between information flow instabilities and cognitive disorders.
- To highlight the role of information flow stability in cognitive robustness.
Main Methods:
- Discusses experimental and theoretical approaches to brain information dynamics.
- Analyzes information flow stability and its impact on cognitive functions.
- Utilizes dynamical models and phase space representations.
Main Results:
- Information flow instabilities in the brain correlate with specific cognitive disorders.
- Robust cognitive activity is linked to the control of information flow stability.
- Theoretical models aid in understanding experimental findings in brain information dynamics.
Conclusions:
- Brain activity is better understood through information flows within dynamical models.
- New theoretical formalisms inspired by recent findings can be experimentally tested.
- Information dynamics offers a framework for analyzing cognitive mechanisms and disorders.
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