Functional Near-Infrared Spectroscopy Reveals Reduced Interhemispheric Cortical Communication after Pediatric Concussion
Bibliographic record
Abstract
Concussion, or mild traumatic brain injury (mTBI), is a growing concern, especially among the pediatric population. By age 25, as many as 30% of the population are likely to have had a concussion. Many result in long-term disability, with some evolving to postconcussion syndrome. Treatments are being developed, but are difficult to assess given the lack of measures to quantitatively monitor concussion. There is no accepted quantitative imaging metric for monitoring concussion. We hypothesized that because cognitive function and fiber tracks are often impacted in concussion, interhemispheric brain communication may be impaired. We used functional near-infrared spectroscopy (fNIRS) to quantify functional coherence between the left and right motor cortex as a marker of interhemispheric communication. Studies were undertaken during the resting state and with a finger-tapping task to activate the motor cortex. Pediatric patients (ages 12-18) had symptoms for 31-473 days, compared to controls, who have not had reported a previous concussion. We detected differences between patients and controls in coherence between the contralateral motor cortices using measurements of total hemoglobin and oxy-hemoglobin with a p<0.01 (n=8, control; n=12 mTBI). Given the critical need for a quantitative biomarker for recovery after a concussion, we present these data to highlight the potential of fNIRS coupled with interhemispheric coherence analysis as a biomarker of concussion injury.
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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 | 0.000 | 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".