Protocol for a randomized controlled trial: efficacy and mechanisms of dual-target anodal tDCS in post-stroke cognitive impairment
Bibliographic record
Abstract
Background: Post-stroke cognitive impairment (PSCI) significantly hinders functional recovery and quality of life in stroke survivors. Although transcranial direct current stimulation (tDCS) has emerged as a promising non-invasive neuromodulation technique to improve cognitive function, conventional single-target tDCS approaches often yield inconsistent outcomes across cognitive domains. Methods: This randomized controlled trial aims to investigate the efficacy and underlying neural mechanisms of dual-target anodal tDCS (a-tDCS) in individuals with PSCI. Sixty participants will be randomly assigned to either a dual-target stimulation group or a single-target stimulation group. Each group will receive 10 sessions of tDCS over two weeks. Cognitive performance will be assessed using the Montreal Cognitive Assessment (MoCA) as the primary outcome, while secondary outcomes include the digit span test, Trail Making Test, and modified Barthel Index. Functional near-infrared spectroscopy (fNIRS) will be used to assess cortical activation and functional connectivity before and after the intervention. Discussion: The findings are expected to provide evidence on the efficacy and underlying mechanisms of dual-target tDCS in PSCI rehabilitation, potentially offering a more effective neuromodulatory intervention strategy for cognitive recovery in stroke survivors. Clinical trial registration: http://www.chictr.org.cn, identifier ChiCTR2500096896.
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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 | 0.025 | 0.029 |
| Meta-epidemiology (narrow) | 0.008 | 0.002 |
| Meta-epidemiology (broad) | 0.013 | 0.005 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.009 | 0.008 |
| Insufficient payload (model declined to judge) | 0.088 | 0.013 |
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".