Visual signals suppress Alpha Power Increases & Frequency Decreases before and after a Mindfulness Meditation Intervention for Problem Gambling
Bibliographic record
Abstract
Abstract The use of mindfulness meditation (MM) in the treatment of problem gambling (PG), has been used effectively for over five years. However, the neural mechanisms responsible for the improvements are unknown. The literature describes healthy individuals with an increase in alpha power and a decrease in alpha frequency after eight weeks of mindfulness meditation, but it is unknown if changes are similar amongst individuals with PG. Using resting-state electroencephalography (rsEEG), we measured the changes in alpha oscillations before and after an eight-week mindfulness meditation intervention (MMi) and a pre/ post-five-minute mindfulness meditation body scan (MMb). For people with PG, we observed an increase in alpha power and decreased alpha peak frequency after the MMi, while the inverse was true for the MMb. The most considerable alpha rhythm changes occurred in the frontal and temporal lobes, areas sensitive to reward and sensory processing in PG. Our observed changes may reflect theories that MMi for PG may improve attentional control as hypothesized by previous research in alpha oscillations and cue-reward processing.
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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 | 0.000 | 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".