FUNCTIONAL MRI CORRELATES OF WORKING MEMORY IN CONCUSSED ATHLETES
Bibliographic record
Abstract
Postconcussive symptoms such as headaches, impaired memory and reduced information processing speed are commonly observed after closed head injury. Although these symptoms tend to improve, subtle cognitive difficulties characterised by deficits on tasks sensitive to frontal lobe function can persist, presumably due to the susceptibility of frontal regions following head injury. The present ongoing study aims to investigate alterations in the functional cerebral metabolic patterns of concussed athletes. Using functional MRI (fMRI), we compared the cerebral activation patterns as well as the performances of athletes who had suffered one or more concussions (N = 3) to a group of healthy control subjects (N = 4) on verbal and visual working memory tasks known to depend on the integrity of frontal areas. In each condition, subjects were inquired to ômonitor or keep trackö of 4 items and to decide whether a 5th item had been presented previously. Preliminary results showed the concussed athletes to be poorer than the control subjects on both verbal and visual working memory tasks. fMRI data revealed significant bilateral activations in areas 9 and 46 of the control group, consistent with the known role of these regions in working memory. In contrast, the activation patterns of the concussed athletes who were impaired on the working memory tasks were either absent or generally weaker and did not involve the same regions. The one athlete who performed as well as the control subjects on the working memory tasks also showed significant activations in areas 9 and 46. These results suggest that working memory tasks as well as fMRI imaging may be useful in identifying an underlying pathology following mild head trauma.
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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 | 0.001 |
| 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".