Standardized preprocessed derivatives for the Comprehensive Assessment of Neurodegeneration and Dementia (COMPASS‐ND) Study
Bibliographic record
Abstract
Abstract Background The Comprehensive Assessment of Neurodegeneration and Dementia (COMPASS‐ND) cohort of the pan‐Canadian Consortium on Neurodegeneration in Aging (CCNA) provides imaging on participants following a standardized protocol. This imaging contribution to deep phenotyping is done to study the full spectrum of age‐related dementias in more than 1,100 individuals (50‐90y) with subjective or mild cognitive impairment, Alzheimer’s disease, other dementias, or otherwise cognitively unimpaired. To accelerate discovery, we propose to release biomarkers extracted from these acquisitions. Here we present preliminary (N=385, AD=39) preprocessing methods, quality control, and available derivatives of the resting‐state functional (rsfMRI), diffusion weighted (DWI), and structural magnetic resonance images. Method fMRI data was preprocessed using fMRIprep v20.2.1. Sørensen–Dice similarity measure was computed between individual masks and group templates using our internal BIDS app. Functional connectome of 101 regions from Dictionary of Functional Modes (DiFuMo) 64 dimension atlas were calculated with confounds removed. Mean network connectivity for the Yeo7 networks was summarized from connectomes. DWI data underwent robust quality control and preprocessing using Tractoflow. Bundle extraction and mean metric computation was done using freewater_flow, rbx_flow and tractometry_flow. Structural scans were preprocessed and segmented using iterativeN3 and MAGeT‐brain to obtain subcortical and cerebellar volumes. As a validation, a subset of variables associated with aging in the literature was tested for association with participant age using simple correlation. Result The functional Dice score was 0.915 (SD=0.017, N=390) and structural was 0.988 (SD=0.004, N=381). Age was significantly associated with mean DMN connectivity (r=‐0.226, p<0.001), bilateral inferior fronto‐occipital fasciculus freewater (r=0.533, p<0.001), and bilateral thalamus volume (r=‐0.243, p<0.001). Conclusion Derivatives obtained include: functional connectomes using DiFuMo64, network connectivity from Yeo7, DWI measures for major fiber tracts, and segmented subcortical and cerebellar volumes. The results of the quality and validity checks indicate the derivatives would be useful for the study of age‐related dementias. Full quality control and release of the complete COMPASS‐ND preprocessed imaging dataset and derivatives should be completed in 2022. For information on access see ccna‐ccnv.ca.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".