Enhancement of pain inhibition by working memory with anodal transcranial direct current stimulation of the left dorsolateral prefrontal cortex
Bibliographic record
Abstract
The aim of this study was to examine whether transcranial direct current stimulation (tDCS) of the dorsolateral prefrontal cortex (DLPFC) enhances pain inhibition by improving working memory (WM). Forty healthy volunteers participated in two tDCS sessions. Pain was evoked by electrical stimulation at the ankle. Participants performed an n-back task (0-back and 2-back). The experimental protocol comprised five counterbalanced conditions (0-back, 2-back, pain, 0-back with pain and 2-back with pain) that were performed twice (pre-tDCS baseline and during tDCS). Compared with the pre-tDCS baseline values, anodal tDCS decreased response times for the 2-back condition (p < 0.01) but not for the 0-back condition (p > 0.5). Anodal tDCS also decreased pain ratings marginally in the 2-back with pain condition, but not the 0-back with pain condition (p = 0.052 and p > 0.2, respectively). No effect was produced by sham tDCS for any condition (p > 0.2). These results indicate that tDCS of the left DLPFC may enhance pain inhibition by improving WM.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".