Mild head injury and sympathetic arousal: Investigating relationships with decision-making and neuropsychological performance in university students
Bibliographic record
Abstract
SUMMARY: The purpose of this study was to examine the relationships between neuropsychological performance, physiological arousal and decision-making in university students who have or have not reported a history of mild head injury (MHI). METHODS: Forty-four students, 18 (41%) reporting a history of MHI, performed a design fluency task and the Iowa Gambling Task (IGT) while electrodermal activity (EDA) was recorded. RESULTS: General cognitive ability and overall choice outcomes did not differ between groups. However, self-reported MHI severity predicted decision-making performance such that the greater the neural indices of trauma, the more disadvantageous the choices made by participants. As expected, both groups exhibited similar base levels of autonomic arousal and physiological responses to reward and punishment outcomes; however, those reporting MHI produced significantly lower levels of EDA during the anticipatory stages of decision-making. CONCLUSIONS: Overall, these findings encourage the acceptance of head injury as being on a continuum of brain injury severity, as MHI can emulate neurophysiological and neuropsychological features of more traumatic cases and may be impacting mechanisms which sustain adaptive social decision-making.
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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 | 0.000 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".