Personalized brain models link cognitive decline progression to underlying synaptic and connectivity degeneration

Area of Science:

• Neuroscience
• Computational Biology
• Medical Imaging

Background:

• Cognitive decline affects a significant portion of the elderly population and is an early sign of Alzheimer's disease.
• Current understanding of the structural defects and neurodegeneration processes driving cognitive decline remains incomplete.
• Existing models lack the ability to fully replicate individual neural activity patterns across different stages of cognitive decline.

Purpose of the Study:

• To introduce a novel Brain Network Model (BNM) that simulates the impact of neurodegeneration on neural activity during cognitive tasks.
• To investigate the roles of synaptic degeneration and brain disconnection in the progression of cognitive decline.
• To establish a link between specific neurodegenerative mechanisms and the severity of cognitive impairment.

Main Methods:

• Developed a Brain Network Model (BNM) incorporating parameters for synaptic degeneration (leading to hyperexcitation) and brain disconnection.
• Optimized the BNM to replicate individual electroencephalography (EEG) responses from 145 participants (healthy controls, subjective cognitive decline, mild cognitive impairment).
• Performed model inversion using individual EEG data to generate personalized BNMs and analyze network configurations and neurodegeneration levels.

Main Results:

• Personalized BNMs accurately reflected individual cognitive status and showed neurodegeneration levels proportional to cognitive decline severity.
• Identified a neurodegeneration-driven phase transition in neural activity, creating distinct functional regimes during task execution.
• Linked synaptic degeneration and hyperexcitation to cognitive decline severity and pinpointed posterior cingulum fiber degeneration as the structural driver of the observed phase transition.

Conclusions:

• Brain Network Models (BNMs) can effectively simulate neural activity changes across cognitive decline stages.
• The study elucidates underlying neurodegenerative mechanisms, specifically the role of synaptic degeneration and posterior cingulum pathway integrity.
• This approach offers a new framework for understanding the interplay of structural and functional brain alterations in Alzheimer's disease progression.