Spatiotemporal profiling of functional network overlapping modules in Alzheimer's disease

Area of Science:

• Neuroscience
• Medical Imaging
• Network Science

Background:

• Alzheimer's disease (AD) involves progressive neural network degradation.
• Overlapping module structures in brain networks offer more accurate functional representations than nonoverlapping ones.
• Understanding dynamic functional changes in overlapping brain modules is crucial for insights into AD.
• The spatiotemporal dynamics of overlapping modular brain organization in AD are not fully understood.

Purpose of the Study:

• To explore the overlapping modular organization and dynamic multilayer modules in Alzheimer's disease (AD) using resting-state fMRI.
• To compare brain network organization between AD patients and healthy controls (HC).
• To investigate the relationship between overlapping nodal characteristics, amyloid deposition, and cognitive performance in AD.

Main Methods:

• Resting-state functional magnetic resonance imaging (fMRI) was used.
• Data were collected from 64 AD patients and 61 healthy controls (HC) from the Alzheimer's Disease Neuroimaging Initiative.
• Analysis focused on overlapping modular organization, dynamic multilayer modules, nodal overlapping probability, and modularity.
• Lasso regression was employed to correlate network characteristics with cognitive performance.

Main Results:

• Alzheimer's disease (AD) patients exhibited increased overlapping modules and decreased modularity compared to healthy controls (HC).
• Altered nodal overlapping probability was observed, particularly in the superior frontal cortex and hippocampus.
• Higher nodal overlapping probability correlated with increased functional flexibility and larger amyloid deposits.
• Overlapping nodal characteristics showed strong correlations with cognitive performance.

Conclusions:

• Overlapping nodes are critical components in Alzheimer's disease (AD) pathology.
• These nodes demonstrate high amyloid deposition, significant functional flexibility, and strong associations with cognitive behavior.
• Findings enhance understanding of AD pathology and may aid in developing diagnostic and therapeutic biomarkers.