P3‐331: FREQUENCY‐DEPENDENT RESTING‐STATE BRAIN ACTIVITY MAPPING: COMPARING HEALTHY ELDERLY TO MILD COGNITIVE IMPAIRMENT AND ALZHEIMER'S DISEASE
Bibliographic record
Abstract
Alzheimer's disease (AD) pathophysiology is gradual starting inconspicuously possibly years before manifestation of clinical symptoms (mild cognitive impairment (MCI)). Accordingly, early diagnosis of AD/MCI plays a crucial role in patient management and treatment development. PET and functional MRI (fMRI) may reveal subtle alterations in brain function associated with the early stages of the memory/cognitive decline in AD and MCI. A neuronal activity (NA) metric was recently introduced based on the fluctuations of the resting-state fMRI (rs-fMRI) signal which demonstrated decreased metabolism in mild AD as measured by FDG-PET. Here we introduced three novel more sophisticated frequency-dependent NA metrics and compared differences between healthy elderly and a group of people with MCI and AD. The rs-fMRI signal was pre-processed and decomposed into independent components (ICs) using IC analysis. The ICs were classified into neuronal and non-neuronal using a support vector machine (SVM) classifier. The rs-fMRI signal at each voxel and band-limited versions of the neuronal components (NCs) were used to define three NA metrics. The major difference between these NA metrics lies in the frequency-bands considered for NCs. In the first metric, fundamental frequency (FF) metric, the frequency-band was 0.01 to 0.08 Hz. In the second metric, medium frequency (MF) metric, the frequency-band was 0.05 to 0.1 Hz, and in the third metric, high frequency (HF) metric, it is 0.15 to 0.2 Hz. These metrics were compared to determine which produced greater differences in NA between a group of controls (N=14) from the Gait and Brain Study (aged 58-85, 71% female) and a group of AD/MCI subjects (N=14) from the Ontario Neurodegenerative Disease Research Initiative (aged 57-86, 50% female). Average NA maps are provided for the healthy elderly (Fig. 1a) and AD/MCI (Fig. 1b). The percentage difference maps between these two groups (Fig. 2) also demonstrates regional variability. The average percentage difference per voxel in NA between groups was also calculated as 25.85%, 28.67%, and 35.46% based on FF, MF, and HF metrics, respectively.
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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) | 0.000 | 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) | 0.002 | 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".