Frequency dependent whole-brain coactivation patterns analysis in Alzheimer's disease

Area of Science:

• Neuroscience
• Brain Imaging
• Alzheimer's Disease Research

Background:

• Resting-state brain activity exhibits complex, frequency-dependent dynamics.
• These dynamic characteristics have been overlooked in Alzheimer's disease (AD) research.

Purpose of the Study:

• To investigate the frequency-dependent dynamic characteristics of whole-brain coactivation patterns (CAPs) in Alzheimer's disease (AD).
• To explore the potential of CAP analysis in differentiating AD from healthy controls (NC).

Main Methods:

• Employed a multiband coactivation pattern (CAP) approach to model brain state space.
• Analyzed brain dynamics in both AD and normal control (NC) groups.
• Correlated dynamic CAP characteristics with clinical indices, including Mini-Mental State Examination scores.

Main Results:

• Identified similar spatial CAP patterns across different frequency bands, but with distinct occurrences.
• Found significant alterations in CAPs associated with the default mode network (DMN) and visual networks between AD and NC groups.
• Demonstrated a correlation between altered frequency-dependent CAP dynamics and cognitive impairment (MMSE scores) in AD patients.

Conclusions:

• While spatial CAP patterns are consistent across frequencies, their dynamic characteristics within subbands differ.
• Delineating frequency subbands of CAPs enhances the ability to distinguish between AD and NC.
• Frequency-dependent dynamic CAP analysis offers a promising avenue for understanding AD pathophysiology and aiding diagnosis.