Effects of transcranial direct current stimulation (tDCS) on posture, movement planning, and execution during standing voluntary reach following stroke
Bibliographic record
Abstract
BACKGROUND: Impaired movement preparation of both anticipatory postural adjustments and goal directed movement as shown by a marked reduction in the incidence of StartReact responses during a standing reaching task was reported in individuals with stroke. We tested how transcranial direct current stimulation (tDCS) applied over the region of premotor areas (PMAs) and primary motor area (M1) affect movement planning and preparation of a standing reaching task in individuals with stroke. METHODS: Each subject performed two sessions of tDCS over the lesioned hemisphere on two different days: cathodal tDCS over PMAs and anodal tDCS over M1. Movement planning and preparation of anticipatory postural adjustment-reach sequence was examined by startReact responses elicited by a loud acoustic stimulus of 123 dB. Kinetic, kinematic, and electromyography data were recorded to characterize anticipatory postural adjustment-reach movement response. RESULTS: Anodal tDCS over M1 led to significant increase of startReact responses incidence at loud acoustic stimulus time point - 500 ms. Increased trunk involvement during movement execution was found after anodal M1 stimulation compared to PMAs stimulation. CONCLUSIONS: The findings provide novel evidence that impairments in movement planning and preparation as measured by startReact responses for a standing reaching task can be mitigated in individuals with stroke by the application of anodal tDCS over lesioned M1 but not cathodal tDCS over PMAs. This is the first study to show that stroke-related deficits in movement planning and preparation can be improved by application of anodal tDCS over lesioned M1. Trial registration ClinicalTrial.gov, NCT04308629, Registered 16 March 2020-Retrospectively registered, https://www.clinicaltrials.gov/ct2/show/NCT04308629.
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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 | 0.000 | 0.000 |
| 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".