A Shift Toward Supercritical Brain Dynamics Predicts Alzheimer's Disease Progression

Area of Science:

• Neuroscience
• Cognitive Science
• Medical Research

Background:

• Alzheimer's disease (AD) is a progressive dementia, with transitions from subjective cognitive decline (SCD) to mild cognitive impairment (MCI) and AD linked to brain hypersynchronization.
• The precise mechanisms driving hypersynchronization and early AD progression remain unclear.
• Healthy brain function during aging is theorized to operate near a critical phase transition, balancing excitation and inhibition (E/I).

Purpose of the Study:

• To test the hypothesis that AD progression shifts brain dynamics toward supercriticality due to excessive excitation.
• To investigate changes in brain criticality, specifically long-range temporal correlations (LRTCs) and functional E/I (fE/I), in individuals with SCD and MCI.
• To determine the predictive value of these dynamic brain features for disease progression and their utility in classifying early AD stages.

Main Methods:

• Utilized source-reconstructed resting-state magnetoencephalography (MEG) data from cross-sectional (N=343) and longitudinal (N=45) cohorts encompassing healthy controls (HC), SCD, and MCI individuals.
• Quantified brain criticality by measuring LRTCs and fE/I of neuronal oscillations.
• Employed machine learning models trained on functional (LRTCs, fE/I) and structural (medial temporal lobe volumes) features for classification tasks.

Main Results:

• LRTCs were attenuated in SCD and progressively more widespread in MCI, indicating a breakdown in temporal correlations.
• Functional E/I (fE/I) was elevated in MCI but not SCD, suggesting an imbalance in neuronal excitation and inhibition.
• Both altered LRTCs and fE/I predicted disease progression in the longitudinal cohort.
• Machine learning models identified LRTCs and fE/I as key classifiers for SCD, while structural changes were more accurate for MCI classification.

Conclusions:

• A shift toward supercritical brain dynamics, characterized by altered LRTCs and fE/I, is an early indicator of Alzheimer's disease progression.
• These dynamic brain measures offer valuable insights into the mechanisms underlying cognitive decline in early AD.
• Functional brain dynamics, particularly LRTCs and fE/I, are crucial for early AD detection and classification, complementing structural assessments.