Relationship between chronic pain and brain reorganization after deafferentation: A systematic review of functional MRI findings
Bibliographic record
Abstract
BACKGROUND: Mechanisms underlying the development of phantom limb pain and neuropathic pain after limb amputation and spinal cord injury, respectively, are poorly understood. The goal of this systematic review was to assess the robustness of evidence in support of "maladaptive plasticity" emerging from applications of advanced functional magnetic resonance imaging (MRI). METHODS: Using MeSH heading search terms in PubMed and SCOPUS, a systematic review was performed querying published manuscripts. RESULTS: From 146 candidate publications, 10 were identified as meeting the inclusion criteria. Results from fMRI investigations provided some level of support for maladaptive cortical plasticity, including longitudinal studies that demonstrated a change in functional organization related to decreases in pain. However, a number of studies have reported no relationship between reorganization, pain and deafferentation, and emerging evidence has also suggested the opposite - that is, chronic pain is associated with preserved cortical function. CONCLUSION: Based solely on advanced functional neuroimaging results, there is only limited evidence for a relationship between chronic pain intensity and reorganization after deafferentation. The review demonstrates the need for additional neuroimaging studies to clarify the relationship between chronic pain and reorganization.
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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 | 0.006 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 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".