Bibliographic record
Abstract
Post-concussion syndrome (PCS) is a poorly understood sequela of mild traumatic brain injury (mTBI), more commonly referred to as concussion. While PCS is known to affect a subset of individuals following injury, it remains unclear how and why specific individuals incur chronic symptoms. Concussions disrupt normal neurophysiologic function within the brain, however the neurophysiologic underpinnings of PCS are unclear. Using transcranial magnetic stimulation (TMS), it is possible to non-invasively investigate neurotransmission in clinical populations such as those with PCS by stimulating the primary motor cortex (M1) and recording motor outputs in a contralateral hand muscle. A study was conducted using TMS to measure corticospinal excitability, intracortical facilitation and inhibition, and transcallosal inhibition in M1 of a group with PCS and a non-injured, healthy control group. Greater corticospinal excitability, and specific reductions in intracortical and transcallosal inhibition were observed in the PCS group, providing evidence of impaired neurotransmitter receptor activity. Importantly, these findings differed from previous observations in recovered concussion groups using similar stimulation techniques. Furthermore, it was observed that these neurophysiological differences may relate specifically to the presence of depression symptoms rather than general concussion symptoms. The physiologic and clinical implications of the findings of this thesis are discussed, and novel research avenues warranting investigation are identified.
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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 | 0.000 |
| 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".