Identifying aMCI with functional connectivity network characteristics based on subtle AAL atlas.

Area of Science:

• Neuroimaging
• Brain Connectivity
• Cognitive Impairment

Background:

• Mild cognitive impairment (MCI) can be a precursor to Alzheimer's disease.
• Subtle alterations in brain functional connectivity may indicate early-stage cognitive decline.
• The AAL_1024 atlas offers a more detailed parcellation of the brain than the AAL_90 atlas.

Purpose of the Study:

• To investigate subtle functional connectivity alterations in amnestic mild cognitive impairment (aMCI) using the high-resolution AAL_1024 atlas.
• To compare the diagnostic performance of the AAL_1024 atlas with the AAL_90 atlas for identifying aMCI.
• To identify key brain regions and network parameters associated with aMCI.

Main Methods:

• Functional MRI data from 32 aMCI patients and 35 healthy controls were analyzed.
• Functional connectivity networks were constructed using Pearson's Correlation with the AAL_1024 atlas.
• Local and global network parameters were calculated and analyzed using multiple-comparison tests and classification algorithms.

Main Results:

• The AAL_1024 atlas detected more subtle local brain functional alterations than the AAL_90 atlas.
• Key nodes such as the hippocampus and inferior temporal/parietal gyri were identified as significant in aMCI.
• Classification accuracy for aMCI identification significantly improved with the AAL_1024 atlas (98.51%) compared to the AAL_90 atlas (88.06%).

Conclusions:

• The AAL_1024 atlas provides a more sensitive tool for detecting functional connectivity alterations in aMCI.
• Utilizing the AAL_1024 atlas enhances the accuracy and reliability of aMCI diagnosis.
• This approach holds promise for early detection and intervention strategies for cognitive impairment.