Exercise is good for the brain but getting outside is even better: Evidence from human brain wave data.
Bibliographic record
Abstract
Abstract It is well known that exercise increases cognitive function. However, the exercise environment may be just as important as the exercise itself. Indeed, time spent in natural outdoor environments has been found to lead to similar increases in cognition as those that come about as a result of exercise. The benefits of both exercise and outdoors suggest an additive impact on brain function when both factors are combined. This raises the question: Is exercise or environment more influential on cognitive function? We answered this question by using electroencephalography to probe cognitive function before and after brief indoor and outdoor walks. Our results demonstrate an increase in a neural response associated with attention and working memory following a 15-minute walk outside than was not seen following a 15-minute walk inside. Importantly, this finding indicates that the environment plays a more substantial role in increasing cognitive function than exercise, at least in acute exercise (i.e., a brief walk). Understanding the impact of time spent in nature on brain function is critical to supporting future infrastructure that aims to reduce the effect of a society spending more and more time indoors.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".