Network based analysis of cognitive related resting state networks in Alzheimer's disease
Bibliographic record
Abstract
Alzheimer's disease (AD) is accompanied by a widespread disruption of neural pathways. This in turn leads to alterations in functional brain networks and a progressive decline in cognitive functions. Despite the success of previous studies in detecting topological alterations in the AD brain, few studies have investigated networks that are related to decline of different cognitive functions in AD, with regard to disconnections and compensatory mechanisms. In this study, we adopted network based statistics (NBS) and resting state functional magnetic resonance imaging (rs-fMRI) in order to find alterations in the functional network and explore networks that are correlated to decline in four cognitive domains. To this end, NBS was applied to the rs-fMRI data and four Montreal cognitive assessment sub-scores of 30 AD patients and 34 healthy subjects. Our results suggest the loss of connections between regions of frontal lobe and two other lobes of temporal and parietal. Moreover, cognitive deficits are in line with changes in the resting state network such as thinning effect and disconnection.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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) | 0.001 | 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".