Report of a patient undergoing chronic responsive deep brain stimulation for Tourette syndrome: proof of concept
Why this work is in the frame
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Bibliographic record
Abstract
Deep brain stimulation (DBS) has emerged as a promising intervention for the treatment of select movement and neuropsychiatric disorders. Current DBS therapies deliver electrical stimulation continuously and are not designed to adapt to a patient's symptoms. Continuous DBS can lead to rapid battery depletion, which necessitates frequent surgery for battery replacement. Next-generation neurostimulation devices can monitor neural signals from implanted DBS leads, where stimulation can be delivered responsively, moving the field of neuromodulation away from continuous paradigms. To this end, the authors designed and chronically implemented a responsive stimulation paradigm in a patient with medically refractory Tourette syndrome. The patient underwent implantation of a responsive neurostimulator, which is capable of responsive DBS, with bilateral leads in the centromedian-parafascicular (Cm-Pf) region of the thalamus. A spectral feature in the 5- to 15-Hz band was identified as the control signal. Clinical data collected prior to and after 12 months of responsive therapy revealed improvements from baseline scores in both Modified Rush Tic Rating Scale and Yale Global Tic Severity Scale scores (64% and 48% improvement, respectively). The effectiveness of responsive stimulation (p = 0.16) was statistically identical to that of scheduled duty cycle stimulation (p = 0.33; 2-sided Wilcoxon unpaired rank-sum t-test). Overall, responsive stimulation resulted in a 63.3% improvement in the neurostimulator's projected mean battery life. Herein, to their knowledge, the authors present the first proof of concept for responsive stimulation in a patient with Tourette syndrome.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 it