Association of a Brief Computerized Cognitive Assessment With Cholinergic Neurotransmission: Assessment Validation Study
Bibliographic record
Abstract
Background: Computerized cognitive assessments are most often validated against standard neuropsychological measures with limited validation against biological indices of brain health. Objective: This study aimed to evaluate whether a self-administered computerized cognitive assessment is associated with cholinergic neurotransmission using the vesicular acetylcholine transporter ligand [18F]fluoroethoxybenzovesamicol (FEOBV) and positron emission tomography (PET). Methods: In a retrospective analysis, we report baseline data from the Improving Neurological Health in Aging via Neuroplasticity-Based Computerized Exercise (INHANCE) trial. This study provides normative data for healthy older adults aged 65 years and above. We evaluate the validity of the Double Decision cognitive assessment (from the BrainHQ assessment platform) by examining its association with tracer binding in the anterior cingulate cortex, as measured by FEOBV-PET. We also assess concurrent validity with neuropsychological performance using standardized measures of executive function and global cognition. Results: The intent-to-treat population from the INHANCE trial analyzed in this study included 92 healthy adults with a mean age of 71.9 (SD 4.86, range 65-83) years, the majority of whom were female (61/92, 66%), with an average of 16.45 (SD 3.40, range 9-27) years of education. The Double Decision assessment is associated with FEOBV binding in the anterior cingulate cortex, explaining 8% of the variance, and was associated with neuropsychological performance measures. The assessment was sensitive to age and was not influenced by education level or gender. Psychometric properties supported its usability and the assessment showed an average completion time of 3 (SD 1.12) minutes. Conclusions: We present the first brief, self-administered computerized cognitive assessment associated with cholinergic network health. This tool is scalable and accessible to individuals with an internet-connected device, offering a practical and cost-efficient approach to cognitive screening. The findings provide valuable insights into brain health, particularly for early detection of cognitive decline, and hold significant potential for broad applications across both clinical and nonclinical contexts.
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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 | 0.008 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".