Faculty Opinions recommendation of Neural basis of induced phantom limb pain relief.
Bibliographic record
Abstract
Objective: Phantom limb pain (PLP) is notoriously difficult to treat, partly due to an incomplete understanding of PLPrelated disease mechanisms.Noninvasive brain stimulation (NIBS) is used to modulate plasticity in various neuropathological diseases, including chronic pain.Although NIBS can alleviate neuropathic pain (including PLP), both disease and treatment mechanisms remain tenuous.Insight into the mechanisms underlying both PLP and NIBS-induced PLP relief is needed for future implementation of such treatment and generalization to related conditions.Methods: We used a within-participants, double-blind, and sham-controlled design to alleviate PLP via task-concurrent NIBS over the primary sensorimotor missing hand cortex (S1/M1).To specifically influence missing hand signal processing, amputees performed phantom hand movements during anodal transcranial direct current stimulation.Brain activity was monitored using neuroimaging during and after NIBS.PLP ratings were obtained throughout the week after stimulation.Results: A single session of intervention NIBS significantly relieved PLP, with effects lasting at least 1 week.PLP relief associated with reduced activity in the S1/M1 missing hand cortex after stimulation.Critically, PLP relief and reduced S1/M1 activity correlated with preceding activity changes during stimulation in the mid-and posterior insula and secondary somatosensory cortex (S2).Interpretation: The observed correlation between PLP relief and decreased S1/M1 activity confirms our previous findings linking PLP with increased S1/M1 activity.Our results further highlight the driving role of the mid-and posterior insula, as well as S2, in modulating PLP.Lastly, our novel PLP intervention using task-concurrent NIBS opens new avenues for developing treatment for PLP and related pain conditions.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.698 | 0.525 |
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".