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Self-Regulated Dynamical Criticality in Human ECoG.

Guillermo Solovey¹, Kai J Miller, Jeffrey G Ojemann

¹Department of Psychology, Columbia University New York, NY, USA.

Frontiers in Integrative Neuroscience

|July 27, 2012

Summary

Human brain activity, measured by electrocorticography (ECoG), shows self-regulated dynamical criticality. Brain states dynamically adjust near a critical threshold, balancing stability during rest and motor tasks.

Keywords:

criticality electrocorticography motor movement

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Area of Science:

Neuroscience
Dynamical Systems Theory
Computational Neuroscience

Background:

Neural systems are theoretically poised near critical states, but direct human evidence is limited.
Functional MRI (fMRI) offers indirect measures of neuronal activity with low temporal resolution.
Electrocorticography (ECoG) provides high-temporal-resolution recordings of local neuronal activity in humans.

Purpose of the Study:

To investigate dynamical criticality in the human brain using ECoG recordings.
To analyze the temporal dynamics of neural activation during rest and motor tasks.
To determine if human brain activity self-regulates near a critical state.

Main Methods:

Analysis of human electrocorticography (ECoG) data.
Characterization of dynamical modes of neural activation.
Comparison of brain dynamics during resting state versus a motor task.

Main Results:

ECoG recordings exhibit self-regulated dynamical criticality.
Neural activation modes dynamically drift around the critical stability threshold.
A fraction of dynamical modes showed increased stability during a motor task compared to rest.

Conclusions:

Human brain activity operates under principles of self-regulated dynamical criticality.
Fast time-scale equilibration of global dynamical states is achieved near criticality.
Task engagement modulates the stability of neural dynamics, suggesting adaptive criticality.