Brain Networks Route Neurodegeneration Patterns in Patients with Progressive Supranuclear Palsy
Bibliographic record
Abstract
BACKGROUND: Progressive supranuclear palsy (PSP) is a neurodegenerative disease driven by 4-repeat τ pathology, which is thought to propagate across interconnected neurons. OBJECTIVES: We hypothesized that interconnected brain regions exhibit correlated atrophy, and that atrophy propagates network-like from fast-declining epicenters to connected regions in PSP. METHODS: = 114/90). MRI-based gray matter volumes were assessed for 246 regions of the Brainnetome atlas and converted to w-scores indicating local atrophy (ie, volumes adjusted for age, sex, and intracranial volume based on regression models determined in a sample of 377 healthy amyloid- and τ-negative controls from the Alzheimer's Disease Neuroimaging Initiative [ADNI]). Annual volume changes were determined for each Brainnetome region of interest using longitudinal structural MRI. Resting-state fMRI from 69 ADNI healthy controls was used to determine a connectivity template. RESULTS: We observed pronounced atrophy and volume decline in the frontal lobe and subcortical regions bilaterally. Correlated atrophy and volume changes were found among interconnected brain regions, with regions with severe atrophy or rapid decline being strongly connected to similarly affected areas, whereas minimally affected regions were connected to less affected areas. Connectivity patterns of atrophy epicenters predicted patient level atrophy and volume decline. CONCLUSIONS: Our findings show that key subcortical and frontal brain regions undergo atrophy in PSP-RS and that gray matter atrophy expands across interconnected brain regions, supporting the view that neurodegeneration patterns may follow the trans-neuronal τ propagation pattern in PSP-RS. © 2025 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".