Network models of neurodegeneration: bridging neuronal dynamics and disease progression
Output Details
Preprint January 16, 2026
Description
Computational models are indispensable for understanding neurodegenerative disease. This review surveys computational modeling approaches relevant to Parkinson’s and related neurodegenerative diseases, focusing on two historically separate traditions: whole-brain models of neuronal dynamics and network-based models of protein pathology, including prion-like spread of α-synuclein. The manuscript highlights experimental evidence showing that neuronal activity influences protein release and clearance, while accumulating pathology feeds back to disrupt circuit and network function, motivating recent efforts to connect these modeling domains. By reviewing work across scales—from neural mass models to connectome-based propagation models—the paper clarifies how computational perspectives, can improve understanding of disease progression in Parkinson’s disease.
Identifier (DOI)
10.1109/RBME.2025.3643310
