Youth-like brain activation linked with greater cognitive training gains in older adults: Insights from the ACTOP study
Bibliographic record
Abstract
This study investigates the relationship between inter-individual neurofunctional differences in older adults and cognitive training efficacy, with a specific focus on the association between youth-like task-related brain activation and improvements in working memory (WM) training. The data is part of the Attentional Control Training for Older People (ACTOP) study, 30 older adults completed 12 half-hour WM training sessions. The WM performance slope, assessed at the conclusion of sessions 1 through 6 and sessions 7 to 12, determined early- and late-stage training gains, respectively. Transfer measures were taken before (PRE), midway (MID), and after (POST) training, and the differences in MID-PRE and POST-MID on transfer tasks were used to determine early- and late-stage transfer effects, respectively. The Goodness of Fit (GOF) metric was used to quantify the similarity between each older adult's activation pattern, as measured with functional magnetic resonance imaging (fMRI), to that of a group of younger adults. GOF scores were calculated for activation during low-load (1-0back) and high-load (2-0back) N-back tasks. The results indicated that larger GOF scores in the low-load condition were associated with greater training gains in both the early and late learning stages, and that larger GOF scores in the high-load condition were associated with greater training gains during the late-stage. These findings suggest that a youth-like brain activation pattern in older adults is associated with greater cognitive training benefits, underscoring the role of inter-individual neurofunctional differences to account for variations in training outcomes among older adults. TRIAL REGISTRATION: ClinicalTrials.gov NCT03532113; https://clinicaltrials.gov/ct2/show/NCT03532113.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".