Study of the effectiveness of training using the “NeuroChat” brain–computer interface at a later age
Bibliographic record
Abstract
BACKGROUND: This article examines the effectiveness of training using the increasingly popular braincomputer interface NeuroChat on a sample of older people. AIM: The purpose of this study is to determine the effectiveness and characteristics of training using the NeuroChat device. MATERIALS AND METHODS: The study involved 41 patients 6 men and 35 women aged 55 to 89 years with various comorbid conditions, undergoing planned treatment at the Russian Gerontology Research and Clinical Centre of the N.I. Pirogov Russian national research medical University. As research methods, a set of diagnostic tests was used: Montreal Cognitive Assessment (MoCA-test), Bourdons test (correction test), 10-word auditory-speech memory test, visual memory test, thinking test 4-th superfluous (4 subtests were used), The Hospital Anxiety and Depression Rating Scale (HADS), as well as the neurotraining using the NeuroChat braincomputer interface. RESULTS: By comparing the control test data with the test data conducted at the beginning of the study, the following results were obtained. Significant changes were found between groups in the 10-word memory test. It is also possible to note an improvement in the indicator of cognitive functioning in general (MoCA screening test), however, this indicator significantly improved in the control group. There was no correlation between the effectiveness of neurotraining with the use of the NeuroChat device and the number of sessions conducted. Changes in the psycho-emotional component of the life of the subjects were not found. CONCLUSION: The use of trainings using the NeuroChat device has a positive effect on the cognitive characteristics of older people without affecting the psycho-emotional sphere. The improvement in the characteristics of the cognitive sphere is confirmed by the results of diagnostic tests and occurs after the first use of the NeuroChat braincomputer interface. The authors consider it necessary to study the relationship between training using the NeuroChat device and improving the cognitive characteristics of people of different age groups, especially the improvement of auditory-speech memory.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".