Repeat traumatic brain injury exacerbates acute thalamic hyperconnectivity in humans
Bibliographic record
Abstract
Abstract Repeated mild traumatic brain injury is of growing interest regarding public and sporting safety and is thought to have greater adverse or cumulative neurological effects when compared with single injury. While epidemiological links between repeated traumatic brain injury and outcome have been investigated in humans, exploration of its mechanistic substrates has been largely undertaken in animal models. We compared acute neurological effects of repeat mild traumatic brain injury (n = 21) to that of single injury (n = 21) and healthy controls (n = 76) using resting-state functional MRI and quantified thalamic functional connectivity, given previous identification of its prognostic potential in human mild traumatic brain injury and rodent repeat mild traumatic brain injury. Acute thalamocortical functional connectivity showed a rank-based trend of increasing connectivity with number of injuries, at local and global scales of investigation. Thus, history of as few as two previous injuries can induce a vulnerable neural environment of exacerbated hyperconnectivity, in otherwise healthy individuals from non-specialist populations. These results further establish thalamocortical functional connectivity as a scalable marker of acute injury and long-term neural dysfunction following mild traumatic brain 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) | 0.003 | 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".