Resting-State Functional Connectivity Difference in Alzheimer's Disease and Mild Cognitive Impairment Using...

Area of Science:

• Neuroscience
• Medical Imaging
• Network Science

Background:

• Functional connectivity disruption is an early hallmark of Alzheimer's disease (AD).
• Understanding brain network alterations is crucial for early AD detection and intervention.

Purpose of the Study:

• To investigate the clustering structure of functional connectivity in key brain networks.
• To identify potential imaging biomarkers for distinguishing Alzheimer's disease (AD) and mild cognitive impairment (MCI) from healthy controls (HC).

Main Methods:

• Utilized resting-state functional magnetic resonance imaging (rs-fMRI) data from 32 AD, 32 HC, and 31 MCI subjects.
• Employed the threshold-free cluster enhancement (TFCE) method for connectivity analysis.
• Modeled the brain as a graph-based network using pairwise Pearson's correlation.

Main Results:

• Severely affected connections were observed in the sensory motor network (SMN), dorsal attention network (DAN), salience network (SAN), default mode network (DMN), and cerebral network in AD and MCI patients.
• Disruptions in these networks showed potential as biomarkers for differentiating AD/MCI from HC.
• A negative correlation between the Clinical Dementia Rating (CDR) score and functional connectivity Z-scores was found in AD subjects.

Conclusions:

• Neurodegenerative disruption of fMRI connectivity is widespread across multiple brain networks in AD.
• Altered functional connectivity in specific networks may underlie cognitive deficits in AD and MCI.
• These findings highlight the potential of rs-fMRI connectivity patterns as biomarkers for early AD and MCI detection.