🧫 Experiment Protocol
Validationproposed
SUMMARY
# Computational Modeling of Alpha-Synuclein Propagation in PD
## Background and Rationale
The progressive spread of alpha-synuclein pathology throughout the nervous system represents one of the most compelling yet incompletely understood aspects of Parkinson's disease pathogenesis. Alpha-synuclein, encoded by the SNCA gene, is a 140-amino acid presynaptic protein that normally functions in synaptic vesicle trafficking and neurotransmitter release regulation. Under pathological conditions, this i
METHODOLOGY NOTES
**Phase 1: Data Collection and Preprocessing (Weeks 1-4)**
• Acquire longitudinal neuroimaging datasets (DaTscan SPECT, structural MRI, DTI) from n=200 PD patients and n=100 controls across 3 timepoints (baseline, 12-month, 24-month follow-up)
• Collect postmortem brain tissue data with confirmed α-syn pathology staging from n=50 cases across Braak stages 1-6
• Extract regional connectivity matrices from DTI data using deterministic tractography with FA threshold >0.2 and streamline density >10 per voxel
• Quantify regional α-syn burden using standardized immunohistochemistry protocols with phospho-α-syn antibodies (pSer129)
• Generate brain parcellation using Desikan-Killiany atlas (68 cortical + 14 subcortical regions)
**Phase 2: Network-Based Propagation Model Development (Weeks 5-12)**
• Implement graph-theoretic propagation model using weighted adjacency matrices from structural connectivity
• Develop mathematical framework incorporating: (1) seeding probability per region, (2) t