MRI receiver coil arrays and holders for concurrent TMS-MRI experiments
Bibliographic record
Abstract
Background: Transcranial direct current stimulation (tDCS) is a non-invasive neuromodulatory technique that modulates brain excitability through low-intensity electrical currents.While tDCS has shown some potentials in various stroke symptoms, its effect on ataxia in acute posterior circulation infarction (PCI) remains underexplored.This study examines the efficacy of tDCS in improving functional and neuropsychological outcomes in PCI patients with ataxia. Methods:We conducted a single-center, randomized, single-blind, sham-controlled trial.Acute ischemic stroke patients with ataxia, admitted within seven days of symptom onset, were enrolled if they had a Tinetti test score of 23, indicating moderate fall risk.Participants were randomized to receive either anodal tDCS (2mA, 20 min/session) targeting the cerebellum for 10 sessions over two weeks or sham stimulation.Outcome measures included the Tinetti test, Falls Efficacy Scale, Beck Depression Inventory-II (BDI-II), Beck Anxiety Inventory (BAI), and modified Rankin Scale (mRS), assessed at baseline, two weeks, and three months post-intervention.Statistical analyses included Scheirer-Ray-Hare, Mann-Whitney U, and Wilcoxon signed-rank tests.Results: twenty-seven patients completed the study (13 tDCS, 14 sham).tDCS significantly reduced BAI scores (P¼0.045,h 2 ¼0.052), with greater improvement at two weeks (Cliff's delta ¼ 0.42) compared to sham.Time effects were also significant for the Tinetti test (P¼0.024)and mRS (P<0.001).Post-hoc analysis revealed that the tDCS group experienced significant functional improvements over time, which were not observed in the sham group.Conclusions: Cerebellar anodal tDCS shows potential in enhancing anxiety, balance, and functional recovery in acute PCI patients with ataxia.These findings support the potential role of early neuromodulation in post-stroke rehabilitation.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.067 | 0.022 |
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".