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The brain as a dynamic physical system

T M McKenna1, T A McMullen, M F Shlesinger

  • 1Division of Cognitive and Neural Sciences, Office of Naval Research, Arlington, VA 22217.

Neuroscience
|June 1, 1994
PubMed
Summary
This summary is machine-generated.

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The brain

Area of Science:

  • Neuroscience
  • Complex Systems
  • Non-linear Dynamics

Background:

  • The brain operates as a dynamic, non-linear system across multiple analytical levels.
  • Understanding non-linear brain dynamics is crucial for comprehending brain function.
  • Attractor identification in phase space is a valuable method for analyzing non-linear systems.

Purpose of the Study:

  • To explore the utility of attractor identification in phase space for characterizing brain dynamics.
  • To investigate transitions between attractors as descriptors of neural state changes.
  • To leverage advancements in complex systems physics for analyzing neural population dynamics.

Main Methods:

  • Phase space analysis to identify families of attractors.
  • Observing population dynamics of neural ensembles using voltage-sensitive dyes and electrode arrays.

Related Experiment Videos

  • Applying concepts from the physics of complex systems, including chaotic system control and attractor switching.

    • Main Results:

    • Attractor families in phase space can describe diverse neural behaviors and activity, including sensory and motor repertoires.
    • Transitions between attractors offer insights into state changes in neurons and neural ensembles.
    • New analytical tools from complex systems physics can enhance the study of neural dynamics.

    Conclusions:

    • Characterizing non-linear brain dynamics through attractor analysis provides fundamental insights into brain function.
    • Emerging experimental capabilities and complex systems approaches offer powerful new methods for studying neural population dynamics.
    • Attractor dynamics and transitions are key to understanding the complex behavior of neural systems.