Probing the effects of mild traumatic brain injury with transcranial magnetic stimulation of the primary motor cortex
Bibliographic record
Abstract
PRIMARY OBJECTIVE: The present paper systematically reviews studies using transcranial magnetic stimulation (TMS) over the primary motor cortex (M1) to assess cortical excitability, intra-cortical inhibition/facilitation and synaptic plasticity following mild traumatic brain injury (mTBI). METHODS: Articles using TMS over M1 in patients with mTBI or sport-related concussion indexed in PubMed and published between 1998 and September 2014 were included in the present review. MAIN OUTCOMES AND RESULTS: From the 17 articles that matched search criteria, results from various TMS paradigms were summarized and divided in three main areas of interest: motor cortical excitability/facilitation, motor cortical inhibition and cortical plasticity. Although studies suggest a trend of abnormal intra-cortical inhibition following mTBI, no clear and specific pattern emerges from the surveyed data. CONCLUSIONS: At this time and with the possible exception of intra-cortical inhibitory measures, TMS cannot reliably detect changes in M1 excitability in individuals with mTBI or a concussion at both the acute and chronic stages of injury. This may be explained by the small number of studies and large variety of stimulation parameters. Additional longitudinal and multimodal studies are needed to better understand the nature of the excitability changes that may occur within M1 following mTBI.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".