A trade-off between cognitive and physical performance, with relative preservation of brain function
Bibliographic record
Abstract
Debate surrounds the issue of how the large, metabolically expensive brains of Homo sapiens can be energetically afforded. At the evolutionary level, decreased investment in muscularity, adiposity and the digestive tract allow for a larger brain. Developmentally, high neo-natal adiposity and preferential distribution of resources to the brain provide an energetic buffer during times of environmental stress. Through an experimental design, we investigated the hypothesis of a trade-off involving brain and muscle at the acute level in humans. Mental performance was measured by a free-recall test, and physical performance by power output on an indoor rowing ergometer. Sixty-two male student rowers performed the two tests in isolation, and then again simultaneously. Paired samples t-tests revealed that both power output and mental performance reduced when tested together compared to in isolation (t(61) = 9.699, p < 0.001 and t(61) = 8.975, p < 0.001). Furthermore, the decrease in physical performance was greater than the decrease in mental performance (t(61) = -2.069, p = 0.043). This is the first investigation to demonstrate an acute level trade-off between these two functions, and provides support for the selfish brain hypothesis due to the relative preservation of cognitive function over physical power output. The underlying mechanism is unclear, and requires further work.
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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 | 0.001 |
| 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 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".