Different relationship of cross‐regional correlations of progression of local cortical thickness and local SUVR <sup>18</sup>F‐flortaucipir PET values to strength of connectivity
Bibliographic record
Abstract
Abstract Background We have demonstrated in vivo in humans that spatial progression of tau distribution and atrophy in Alzheimer’s is largely driven by connectivity (Soucy et al, HAI2020). Nevertheless, local tau accumulation and atrophy should not progress in parallel during disease evolution. Atrophy keeps worsening, while local tau density (SUVRs estimated with PET) initially increases but could then decline because of tissue loss. Therefore, despite the impact of connectivity on progression of both local atrophy and SUVRs, it likely will not remain the same for both over time. This is what we tested in this work. Method We studied 35 AD subjects from ADNI with 2 PET studies (18F‐florbetapir) at times Ta/Tb (mean elapsed time = 438 days, median = 454), and a T1 MRI at Ta. Eighteen subjects were non‐progressors (NP) and 17 were progressors (P) based on change between Ta/b hippocampal SUVRs values. This criterion was considered to represent how far advanced patients were in their disease. Moran I statistic was used to measure autocorrelations between connectivity and T1 MRI‐defined cortical thickness at Ta or tau PET SUVR values at both times Ta and Tb in NP and P subjects in regions separately analyzed based the “intensity” of their connectivity as defined by a standard connectivity map (Human Connectome Project). We defined 3 groups of regions from thresholds separating poorly connected from moderately connected (0.01) and moderately connected from highly connected ones (0.021). Result In both NPs and Ps, regions with high connectivity showed higher Z‐score (4.06) of the Moran I value for correlations between regions’ cortical thickness than those with low (2.64)/moderate (2.17) connectivity. For SUVR values however, in both NPs and Ps and at both time points, Z‐scores were always lower for the highly connected regions than for those with moderate/low connectivity. Conclusion The way connectivity influences correlations of atrophy across regions is indeed different from the way it affects correlations of tau deposition, likely for the reasons we hypothesized above to guide the progression of each parameter. Models of tau propagation across the brain will need to factor in ongoing atrophy but reversible accumulation of tau.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".