Brain Functional Flexibility and its Relationship to the Preclinical Stage of Alzheimer’s Disease
Bibliographic record
Abstract
Abstract Background Characterizing pathological and functional features of the preclinical stage of Alzheimer’s Disease (AD) is essential as Amyloid beta (Aβ) and tau, the pathological hallmarks of AD, start to accumulate years prior to the onset of clinical symptoms. Whether Aβ and/or tau are related to the brain’s ability to functionally reconfigure in time (functional flexibility) remains unclear despite its important role in behavior and cognition. Method We included 233 cognitively unimpaired individuals with family history of AD from the PREVENT‐AD cohort who underwent both Positron Emission Tomography (PET) and functional Magnetic Resonance Imaging (fMRI). We computed the element‐wise product of the BOLD fMRI timeseries of the 400 Schaefer atlas nodes as co‐fluctuation matrices for the scan duration (all TRs). We then calculated the variabilities of the obtained co‐fluctuations at the whole brain and network level (DMN and limbic as early susceptible networks in AD) and used these measures of variability as a proxy of functional flexibility. We also computed the average of the obtained co‐fluctuation matrices, which mathematically corresponds to the Pearson correlation of the nodal timeseries pairs and used this as our marker of static functional connectivity (sFC). We then assessed the relationship between functional flexibility and sFC with the level of Aβ (global index) and tau (temporal meta‐ROIs), using those, both as continuous and dichotomized variables (Figure 1). Two thresholds were used for Aβ, one associated with low Aβ accumulation (centiloid of 18) and the other with significant Aβ burden (centiloid of 40). Result No association was found between AD pathology and functional flexibility or sFC using AD pathology as continuous or dichotomized variables (Figure 2 and 3). However, the maximum range of functional flexibility values in individuals with significant Aβ burden and high tau was about half the one found in individuals with low or no pathology, a result that was particularly striking with tau. Conclusion The absence of group difference suggests that functional flexibility cannot be used as a proxy of AD. While individuals with AD pathology have a low range of functional flexibility values, low values are also frequent in individuals with no pathology.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".