Non-Invasive Brain Stimulation Enhances the Effects of Melodic Intonation Therapy
Bibliographic record
Abstract
Research has suggested that a fronto-temporal network in the right hemisphere may be responsible for mediating melodic intonation therapy's (MIT) positive effects on speech recovery. We investigated the potential for a non-invasive brain stimulation technique, transcranial direct current stimulation (tDCS), to augment the benefits of MIT in patients with non-fluent aphasia by modulating neural activity in the brain during treatment with MIT. The polarity of the current applied to the scalp determines the effects of tDCS on the underlying tissue: anodal-tDCS increases excitability, whereas cathodal tDCS decreases excitability. We applied anodal-tDCS to the posterior inferior frontal gyrus of the right hemisphere, an area that has been shown both to contribute to singing through the mapping of sounds to articulatory actions and to serve as a key region in the process of recovery from aphasia, particularly in patients with large left hemisphere lesions. The stimulation was applied while patients were treated with MIT by a trained therapist. Six patients with moderate to severe non-fluent aphasia underwent three consecutive days of anodal-tDCS + MIT, and an equivalent series of sham-tDCS + MIT. The two treatment series were separated by 1 week, and the order in which the treatments were administered was randomized. Compared to the effects of sham-tDCS + MIT, anodal-tDCS + MIT led to significant improvements in fluency of speech. These results support the hypothesis that, as the brain seeks to reorganize and compensate for damage to left hemisphere language centers, combining anodal-tDCS with MIT may further recovery from post-stroke aphasia by enhancing activity in a right hemisphere sensorimotor network for articulation.
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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) | 0.002 | 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".