Pain’s Adverse Impact on Training-Induced Performance and Neuroplasticity: A Systematic Review
Bibliographic record
Abstract
Motor training is a widely used therapy in many pain conditions. The brain's capacity to undergo functional and structural changes i.e., neuroplasticity is fundamental to training-induced motor improvement and can be assessed by transcranial magnetic stimulation (TMS). The aim was to investigate the impact of pain on training-induced motor performance and neuroplasticity assessed by TMS. The review was carried out in accordance with the PRISMA-guidelines and a Prospero protocol (CRD42020168487). An electronic search in PubMed, Web of Science and Cochrane until December 13, 2019, identified studies focused on training-induced neuroplasticity in the presence of experimentally-induced pain, 'acute pain' or in a chronic pain condition, 'chronic pain'. Included studies were assessed by two authors for methodological quality using the TMS Quality checklist, and for risk of bias using the Newcastle-Ottawa Scale. The literature search identified 231 studies. After removal of 71 duplicates, 160 abstracts were screened, and 24 articles were reviewed in full text. Of these, 17 studies on acute pain (n = 7) or chronic pain (n = 10), including a total of 258 patients with different pain conditions and 248 healthy participants met the inclusion criteria. The most common types of motor training were different finger tasks (n = 6). Motor training was associated with motor cortex functional neuroplasticity and six of seven acute pain studies and five of ten chronic pain studies showed that, compared to controls, pain can impede such trainings-induced neuroplasticity. These findings may have implications for motor learning and performance and with putative impact on rehabilitative procedures such as physiotherapy.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".