Brain functional connectivity in children with a mild traumatic brain injury: A scoping review
Bibliographic record
Abstract
INTRODUCTION: The occurrence of mild traumatic brain injury(mTBI) is estimated at 0,2-0,3% cases annually. Following a mTBI, some children experience persistent symptoms, and functional connectivity(FC) changes may be implicated. However, characteristics of FC have not been widely described in this population. This scoping review aimed to identify and understand the impacts of mTBI on EEG-measured FC in children, provide an overview of the available literature, detail analysis techniques, and describe gaps in the research. METHODS: PubMed, Web of Science, Medline, Embase, ProQuest and CINAHL were searched up to June 25, 2023, with the terms child, mTBI, EEG, FC, and their synonyms. Ten studies were identified. RESULTS: Five studies reported significant differences between the mTBI group and controls. In addition to group differences, six studies reported significant variation over time. Brain Network Analysis(BNA), utilized in seven studies, was the primary FC analysis recorded. Two of the five studies that reported significant differences following mTBI utilized the BNA. The other three applied alternative analysis methods. DISCUSSION: FC assessment based on EEG can identify some differences in children with mTBI. BNA was more useful in following changes over time. Further research is suggested, considering the limited age range and number of retrieved studies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".