Brain metabolic-functional (de)coupling from health to glioma dysfunction.

Area of Science:

• Neuroscience
• Metabolic Imaging
• Brain Network Analysis

Background:

• Brain metabolism and function are crucial for cognitive processes.
• Previous research linked glucose metabolism to resting-state fMRI but ignored hemodynamic confounders and brain dynamics.
• Understanding the interplay between brain metabolism and functional connectivity is vital for cognitive neuroscience.

Purpose of the Study:

• To investigate the relationship between brain metabolism and functional dynamics at rest.
• To differentiate statistical dependencies from directional brain flow using novel methods.
• To examine how these interactions are altered in glioma patients.

Main Methods:

• Employed a novel effective connectivity decomposition separating partial covariance (statistical dependencies) from differential covariance (directional flow).
• Utilized resting-state fMRI and standardized uptake value ratio (SUVR) for glucose metabolism.
• Analyzed data from 42 healthy subjects and 43 glioma patients.

Main Results:

• Partial covariance correlated with metabolic connectivity across brain regions.
• Node directionality was associated with standardized uptake value ratio (local glucose consumption).
• Glioma patients showed disrupted local and network-level effective-metabolic interactions, varying by tumor location.

Conclusions:

• Established a link between brain's statistical dependencies and metabolic connectivity.
• Demonstrated that directional brain flow reflects local glucose consumption.
• Highlighted disruptions in brain metabolism-function coupling in glioma, offering insights into pathological brain states.