Assessing Nociception by Fmri of the Human Spinal Cord: A Systematic Review
Bibliographic record
Abstract
OBJECTIVE: To assess the use of fMRI of the spinal cord in measuring noxious stimulation. METHODS: The Scopus, Medline, EMBASE, and Web of Science databases were searched, along with the reference lists of included articles. Two independent reviewers screened abstracts, full-text articles, and extracted data. Original research was included if fMRI of the human spinal cord was used to measure responses to noxious stimulation. RESULTS: Of the 192 abstracts screened, 19 met the search criteria and were divided according to their focus: investigating pain responses (n = 6), methodology (n = 6), spinal cord injury (n = 2), or cognition-pain interactions (n = 5). All but one study appear to have observed activity in ipsilateral and dorsal gray matter regions in response to noxious stimuli, although contralateral or ventral activity was also widely observed. CONCLUSIONS: Although nociception can be investigated using spinal fMRI, establishing reliability, standardizing methodology, and reporting of results will greatly advance this field.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.027 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.005 |
| Bibliometrics | 0.012 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".