Whole-brain modeling of the differential influences of Amyloid-Beta and Tau in Alzheimer’s Disease
Bibliographic record
Abstract
Abstract Background Alzheimer’s Disease is a neurodegenerative condition associated with the accumulation of two misfolded proteins, amyloid-beta (A β ) and tau. We study their effect on neuronal activity, with the aim of assessing their individual and combined impact. Methods We use a whole-brain dynamic model to find the optimal parameters that best describe the effects of A β and tau on the excitation-inhibition balance of the local nodes. Results We found a clear dominance of A β over tau in the early disease stages (MCI), while tau dominates over A β in the latest stages (AD). We identify crucial roles for A β and tau in complex neuronal dynamics and demonstrate the viability of using regional distributions to define models of large-scale brain function in AD. Conclusions Our study provides further insight into the dynamics and complex interplay between these two proteins, opening the path for further investigations on biomarkers and candidate therapeutic targets in-silico.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".