Network Hyperexcitability in Early Alzheimer's Disease: Is Functional Connectivity a Potential Biomarker?

Area of Science:

• Neuroscience
• Computational Neuroscience
• Biomarkers

Background:

• Network hyperexcitability (NH) is implicated in Alzheimer's disease (AD) pathophysiology.
• Functional connectivity (FC) is a potential biomarker for NH.
• Understanding the relationship between brain network dynamics and FC is crucial for AD research.

Purpose of the Study:

• To investigate the relationship between brain hyperexcitability and functional connectivity (FC).
• To determine if FC measures can serve as surrogate markers for the excitation/inhibition (E/I) balance in the brain.
• To compare the sensitivity of different FC measures (AEC, PLI) and frequency bands (theta, alpha) in reflecting E/I balance.

Main Methods:

• Utilized a whole-brain computational model (Stuart Landau model) with 78 interconnected regions to simulate oscillatory brain activity.
• Quantified FC using amplitude envelope correlation (AEC) and phase coherence (PC) in the model.
• Recorded resting-state magnetoencephalography (MEG) in subjects with subjective cognitive decline (SCD) and mild cognitive impairment (MCI).
• Calculated corrected AEC (AECc) and phase lag index (PLI) in the theta (4-8 Hz) and alpha (8-13 Hz) bands from MEG data.

Main Results:

• The excitation/inhibition (E/I) balance in the computational model significantly affected both AEC and PC, with varying influence based on structural coupling and frequency band.
• Empirical FC matrices from SCD and MCI subjects showed good correlation with model-derived AEC, particularly in the hyperexcitable range, but less so for PC.
• Amplitude envelope correlation (AEC) was found to be more sensitive to E/I balance changes than the phase lag index (PLI).
• The theta band (4-8 Hz) yielded better results than the alpha band (8-13 Hz) for AEC in reflecting E/I balance.

Conclusions:

• Functional connectivity (FC) is sensitive to alterations in the brain's excitation/inhibition (E/I) balance.
• Amplitude envelope correlation (AEC) is a more effective measure than phase lag index (PLI) for detecting changes in E/I balance.
• These findings support the use of FC measures, especially AEC in the theta band, as surrogate markers for E/I balance in neurological conditions like Alzheimer's disease.