Default mode network functional connectivity after multiple concussions in children and adolescents
Bibliographic record
Abstract
Abstract The default mode network (DMN), a set of brain regions, has been shown to be affected post-concussion. Objective This cross-sectional study aims to elucidate if children and adolescents with multiple concussions demonstrate long-term alterations in DMN functional connectivity (FC). Method Participants (N = 57, 27 girls and 30 boys; 8-19 years old, M age = 14.7, SD = 2.8) were divided into three groups (orthopedic injury [OI] n = 20; one concussion n = 16; multiple concussions n = 21, M = 3.2 concussions, SD = 1.7) and seen on average 31.6 months post-injury (range 4.3-130.7 months; SD = 19.4). They underwent a resting-state functional magnetic resonance imaging scan. Parents completed the ADHD rating scale-5 for children and adolescents. Children and parents completed the post-concussion symptom inventory (PCSI). Results Anterior and posterior DMN components were extracted from the fMRI data for each participant using FSL’s MELODIC and dual regression. We tested for pairwise group differences within each DMN component in FSL’s Randomize (5000 permutations) using threshold-free cluster enhancement to estimate cluster activation, controlling for age, sex, and symptoms of inattention. FC of the anterior DMN was significantly reduced in the group with multiple concussions compared to the two other groups, whereas there were no significant group differences on FC of the posterior DMN. There were no significant associations between DMN FC and PCSI scores. Conclusions These results suggest reduced FC in the anterior DMN in youth with multiple concussions, but no linear association with post-concussive symptoms.
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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 | 0.000 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".