Memory Function and Brain Functional Connectivity Adaptations Following Multiple-Modality Exercise and Mind–Motor Training in Older Adults at Risk of Dementia: An Exploratory Sub-Study
Bibliographic record
Abstract
Background: Multiple-modality exercise improves brain function. However, whether task-based brain functional connectivity (FC) following exercise suggests adaptations in preferential brain regions is unclear. The objective of this study was to explore task-related FC changes following multiple-modality exercise and mind-motor training in a subsample of older adults with subjective cognitive impairment. Methods: This was an exploratory sub-study involving a sample of participants (n = 9, mean age 67.8 [8.8] years, 8 women) who received 45 minutes of multiple-modality exercise with additional 15 minutes of mind-motor training and completed baseline and follow-up task-based fMRI assessment. Four computer-based memory tasks from the Cambridge Brain Sciences cognitive battery (i.e., Monkey Ladder, Spatial Span, Digit Span, Paired Associates) were employed and participants underwent 5 minutes of continuous fMRI data collection while completing the tasks. All fMRI data were analyzed using group-level independent component denoising and dual regression procedures, correcting for voxel-wise comparisons. All behavioural data were compared using paired samples t-tests. Results: Dual regression revealed significant decreased FC co-activation in the right precentral/postcentral gyri after the exercise program during the Spatial Span task (corrected p = 0.008), although there was no change in the behavioural task performance. Only trends for changes in FC were found for the other tasks (all corrected p < 0.09). In addition, for the Paired Associates task, there was a trend for improvements in the behavioural task performance, which was coupled with trends for increased co-activation in the right temporal lobe (Brodmann Area = 38, corrected p = 0.07), and left middle frontal temporal gyrus (corrected p = 0.06). Post-hoc analysis exploring voxel FC within each group-spatial map confirmed FC activation trends observed from dual regression. Conclusions: Our findings suggest that multiple modality, mind motor exercise resulted in divergent FC adaptations including significant decreased co-activation in the precentral/postcentral gyri during the Spatial Span task. Of particular interest, borderline significant changes during the Paired Associates tasks in FC and behavioural data provide insight into the potential of our intervention to promote improvements in visuospatial memory as well as impart FC adaptations in brain regions relevant to Alzheimer’s disease risk.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".