Electroencephalographic and cognitive task analysis of working memory and attention in athletes: A systematic review
Bibliographic record
Abstract
This study aimed to systematically review the current research on the cognitive ability of athletes, specifically, in working memory, attention, problem-solving and decision-making tasks. The objective was to examine the differences in cognitive abilities between athletes and non-athletes, and between athletes from different sports. To this end, a search was conducted on PubMed and Scopus for original articles published before November 28th, 2023, that used electroencephalography (EEG) in sports or with athletes engaged in at least moderate-intensity activities, evaluated healthy adults or children through case-control studies, and analyzed at least one of four cognitive tasks (working memory, attention, problem-solving and decision-making). The risk of bias and quality assessment was performed using the Newcastle-Ottawa Scale. The following results were extracted from the included studies: population; publishing year; type of sport; type of controls (athletes or general population); cognitive task results; brain wave frequencies analyzed; and brain wave components analyzed. Following the review of 697 studies, 35 met the inclusion criteria. Most studies reported that athletes outperformed controls in cognitive tasks, both in terms of accuracy and reaction time. Individual sports showed better performances, and martial arts and boxing showed good reaction times but poor accuracies. Increased cortical activity was also observed in athletes when compared with controls. Despite some limitations - primarily the number of studies performing sport-specific tasks or comparing the athletes with less experienced counterparts - results indicate a clear over-performance in cognitive tasks by athletes compared to controls, as well as definitive cognitive differences between different sports.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.000 | 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".