A spatiotemporal complexity architecture of human brain activity.

Area of Science:

• Neuroscience
• Complex Systems Science
• Network Science

Background:

• The human brain functions via large-scale networks characterized by temporally correlated activity.
• The relationship between global network properties and individual region neural dynamics is not fully understood.

Purpose of the Study:

• To investigate the link between brain network architecture and neural dynamics.
• To identify the role of neural regularity episodes in brain function.

Main Methods:

• Analysis of functional magnetic resonance imaging (fMRI) signals.
• Identification and characterization of spontaneous "complexity drops" in neural activity.
• Examination of the relationship between complexity drops and functional connectivity, activity propagation, and interindividual differences.

Main Results:

• Brain network architecture is tightly associated with complexity drops in fMRI signals.
• Complexity drops explain functional connectivity strength and facilitate neural activity pattern propagation.
• These episodes reflect individual differences in age and behavior.
• Complexity drops define neural activity states that dynamically influence network connectivity, topology, and hierarchy, explaining structure-function relationships.

Conclusions:

• A principled complexity architecture, termed the human "complexome," underlies brain functional network organization.
• Complexity drops are critical events that dynamically shape brain network properties.
• This framework provides a new understanding of how neural dynamics relate to large-scale brain network function.