The control costs of human brain dynamics.

Area of Science:

• Neuroscience
• Network Science
• Computational Biology

Background:

• The human brain's high energy demands necessitate efficient control mechanisms.
• Understanding whole-brain control costs and their bioenergetic basis is crucial but underexplored.

Purpose of the Study:

• To introduce and apply the concept of time-averaged control energy (TCE) to quantify brain control costs at rest.
• To investigate the relationship between TCE, brain metabolism, and functional brain dynamics.

Main Methods:

• Utilized network control theory to define and calculate TCE.
• Integrated functional MRI and diffusion MRI data for whole-brain analysis.
• Correlated TCE with positron emission tomography (PET) measures of oxygen metabolism.

Main Results:

• TCE spatially correlates with brain oxygen metabolism, indicating a bioenergetic cost of control.
• Brain state transitions are more efficient (lower TCE) and frequent within hierarchical groups than between them.
• An inverse correlation exists between temporal control costs and state visit frequency, suggesting energy-efficient functional diversity.

Conclusions:

• Introduced TCE as a novel metric for quantifying the energetic cost of brain control.
• Demonstrated a link between brain control costs, metabolism, and hierarchical organization.
• Proposed a mechanism where the brain balances functional diversity and energy expenditure through efficient control strategies.