Sex-specific differences in resting-state functional brain activity in pediatric concussion
Bibliographic record
Abstract
Pediatric concussion has a rising incidence and can lead to long-term symptoms in nearly 30% of children. Resting state functional magnetic resonance imaging (rs-fMRI) disturbances are a common pathological feature of pediatric concussion, though no studies have explicitly examined sex-differences with respect to this outcome, precluding a sex-specific understanding of the functional neuropathology of pediatric concussion. Therefore, we performed a secondary data analysis of rs-fMRI data collected on children with concussion (n = 29) recruited from in a pediatric hospital setting, with greater than 12:1 matched control data accessed from the open-source ABIDE-II database. Seed-based and region of interest (ROI) analyses were used to examine sex-based rs-fMRI differences; threshold-free cluster enhancement (TFCE) and a family-wise error (FWE) corrected p-values were used to identify significantly different clusters. In comparing females with concussion to healthy females, groupwise differences were observed irrespective of seed selected. Notably, we observed (in order of largest effect) hypo-connectivity between the anterior cingulate cortex of the salience network and the thalamus and precuneus (TFCE = 1473.5, p-FWE < 0.001) and the cingulate gyrus (TFCE = 769.3, p-FWE = 0.009), and the seed (posterior cingulate cortex (PCC)) of the default mode network and the paracingulate gyrus (TFCE = 1275.7, p-FWE < 0.001), occipital pole right (TFCE = 1045.0, p-FWE = 0.001), and sub-callosal cortex (TFCE = 844.9, p-FWE = 0.005). Hyper-connectivity was observed between the salience network seed and the cerebellum (TFCE = 1719.3, p-FWE < 0.001) and the PCC and the thalamus (TFCE = 1198.3, p-FWE < 0.001), cuneal cortex (1070.9, p-FWE = 0.001), and lateral occipital cortex left (TFCE = 832.8, p-FWE = 0.006). ROI analyses showed 10 and 5 significant clusters of hypo- and hyper-connectivity in females, respectively. Only one cluster of difference was found between males with concussion and healthy males on seed-based analyses, and 3 clusters on ROI analyses. There are alterations in rs-fMRI in females with concussion at one-month post-injury that are minimally present in males, which provides further evidence that recovery timelines in pediatric concussion may differ by sex.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".