Event-Related Brain Potentials Depict Cognitive Disturbances in Children with Mild Traumatic Brain Injury
Bibliographic record
Abstract
Mild traumatic brain injury (MTBI) is a common cause of short-term cognitive disturbances in children that rarelyare related to objective neurophysiological markers. With the aim of correlating cognitive processing withevent-related brain potential variation, visual Continuous Performance Tests (CPT) were administered to 15children with MTBI and a matched control group. All the patients had suffered post-traumatic loss of consciousnesslasting less than 15 minutes, and they were evaluated within 5-to-15 days post-trauma. A few additionalneuropsychological tests were also administered to both groups. Behavioral results showed that the injured childrenachieved poorer scores for phonological and verbal fluency tasks and no interference effect in a computerizedversion of the Stroop test. They had fewer correct responses on CPT-AX, where a warning signal preceded targets.The N90, P240 and P390 ERP components varied significantly between groups while performing CPT-AX. Presentfindings could be interpreted as reflecting disturbances that impede injured children from using contextualinformation efficiently. The higher amplitude of the slow late positivity observed in the control group might reflectupdating memory preparatory processes that could increase subsequent cognitive operational competence. The ERPassessment could be helpful to demonstrate early neurophysiological disturbances subsequent to a MTBI inchildren.
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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".