The Role of Functional Brain Connectivity in Intervention Success: A Secondary Analysis from the SYNERGIC Trial
Bibliographic record
Abstract
PURPOSE: Functional (brain) connectivity, or brain regions that are anatomically separate but temporally synchronized, is crucial for executing complex functions and is sensitive for identifying covert but meaningful differences in clinical populations. We aimed to determine if preintervention functional connectivity and executive function differ between "responders" and "nonresponders" in a randomized controlled trial. METHODS: Participants diagnosed with mild cognitive impairment completed combined physical exercise (i.e., aerobic and resistance training) with or without cognitive training and/or vitamin D 3 supplementation three times per week for 20 wk. We assessed pre-intervention functional connectivity using a seed-to-voxel approach and executive function using the (normalized) Trail Making Test. We defined responders as those who achieved the minimal clinically important difference in tests of physical performance (i.e., cardiovascular fitness, muscle strength, and muscle power) by the end of the intervention. RESULTS: Our 67 participants were mostly male, with an average age of 74.51 ± 6.44 yr. For cardiovascular fitness, responders demonstrated stronger functional connectivity between the medial prefrontal cortex and right frontal pole (cluster: size = 352 P -FDR < 0.05). Similarly, for muscle strength, responders demonstrated stronger functional connectivity between the left amygdala and right cerebellum (cluster: size = 268 P -FDR < 0.05). There was no link between functional connectivity and executive functions. CONCLUSIONS: Responders to a physical exercise intervention possess stronger preintervention functional connectivity between regions implicated in higher-order cognitive and behavioral processing. Functional connectivity may delineate who is primed for intervention success and who may require alternative strategies before beginning. Future research should aim to determine if preintervention functional connectivity can help optimize intervention resources and enhance the precision of personalized exercise recommendations.
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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".