Effect of game-based EEG neurofeedback training on improvement of cognitive function
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Bibliographic record
Abstract
Objective: To observe the effect of game-based EEG neurofeedback system on improvement of cognitive function in the patients with cognitive impairment. Methods: Fifty-two patients with cognitive impairment, mainly memory decline, were included, and the Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment Scale (MoCA) and Alzheimer′s Disease Assessment Scale-Cognitive section(ADAS-cog) were conducted in the patients to evaluate cognitive impairment. Five days later, each patient was given 30-min EEG neural feedback training, once a day for 10 consecutive days. The EEG was detected before and after training, and MMSE, MoCA and ADAS-cog scores were also evaluated after training. Results: The scores of MMSE, MoCA and ADAS-cog scales after training were all higher(26.06±2.95, 21.88±3.94, 12.15±5.15) than those before training (23.10±2.82, 18.63±4.10, 14.76±5.30) (P<0.05). Before training, the scores of memory on MMSE, MoCA and ADAS-cog scales were 1.55±0.77, 1.33±1.28, 4.35±1.11, respectively, while the above scores increased to 2.16±0.80, 2.29±1.34, 3.93±1.30(P<0.001) after training. The EEG after training showed that the complexity of EEG was improved than that before training, mainly in the left frontal lobe. Conclusions: The game-based EEG neurofeedback system training can significantly improve cognitive function and EEG complexity in the left prefrontal lobe.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.042 | 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 it