Primary study on hand motor cortex mapping by using navigated transcranial magnetic stimulation
Bibliographic record
Abstract
Objective To investigate the feasibility and safety of using navigated transcranial magnetic stimulation (nTMS) to map hand motor cortex and further analyze its clinical application. Methods The first dorsal interosseous (FDI) was selected as target muscle. The location and area of bilateral FDI were mapped by using nTMS in 10 healthy right-handed volunteers. In order to identify the accuracy of nTMS, all individual MRI volumes and the coordinates of hotspots were normalized to Montreal Neurological Institute (MNI) space using SPM8. Positive sites and motor-evoked potential (MEP) were recorded. The areas of hand motor representations were calculated and compared between bilateral cerebral hemispheres. Results nTMS was capable of identifying hand motor cortex area in both hemispheres in all cases. It took 45 to 60 minutes to finish the whole nTMS procedures of each side of hand motor area. The motor cortex was found at the Ω area of bilateral precentral gyri. The right hand motor representation area was significantly larger than that of left area [(6.22 ± 0.76) cm2 vs (4.30 ± 0.40) cm2; t = 7.078, P = 0.000]. Four cases presented sleepiness, but no side effect such as headache or epilepsy was found. Conclusions nTMS is a reliable and safe technique to map hand motor cortex. It can be a very useful supplementary tool for preoperative motor cortex mapping and study on motor functional remodeling. DOI: 10.3969/j.issn.1672-6731.2016.08.011
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".