Reducing Chronic Visuo-Spatial Neglect Following Right Hemisphere Stroke Through Instrument Playing
Bibliographic record
Abstract
Unilateral visuo-spatial neglect is a neuropsychological syndrome commonly resulting from right hemisphere stroke at the temporo-parietal junction of the infero-posterior parietal cortex. Neglect is characterized by reduced awareness of stimuli presented on patients' contralesional side of space. Inspired by evidence of increased spatial exploration of patients' left side achieved during keyboard scale-playing, the current study employed a music intervention that involved making sequential goal-directed actions in the neglected part of space, in order to determine whether this would bring about clinically significant improvement in chronic neglect. Two left neglect patients completed an intervention comprising four weekly 30-min music intervention sessions involving playing scales and familiar melodies on chime bars from right to left. Two cancellation tests [Mesulam shape, Behavioral Inattention Test (BIT) star], the neglect subtest from the computerized TAP (Test of Attentional Performance) battery, and the line bisection test were administered three times during a preliminary baseline phase, before and after the four intervention sessions during the intervention phase to investigate short-term effects, and 1 week after the last intervention session to investigate whether any changes in performance would persist. Both patients demonstrated significant short-term and longer-lasting improvements on the Mesulam shape cancellation test. One patient also showed longer-lasting effects on the BIT star cancellation test and scored in the normal range 1 week after the intervention. These findings provide preliminary evidence that active music-making with a horizontally aligned instrument may help neglect patients attend more to their affected side.
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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".