Closed-loop systems for deep brain stimulation to treat neuropsychiatric disorders
Bibliographic record
Abstract
INTRODUCTION: A closed-loop or feedback-control system is a process which considers the system's output in order to automatically adjust the input. Compared to a traditional open-loop system, a closed-loop system allows for a higher degree of accuracy with minimal human intervention. Novel methods of closed loop 'adaptive' deep brain stimulation DBS (aDBS) are being developed. AREAS COVERED: This review focuses on the current state of aDBS for various neuropsychiatric conditions: common movement disorders such as Parkinson's disease, dystonia, essential tremor, and Tourette syndrome, as well as psychiatric disorders of depression and obsessive-compulsive disorder. Finally, the future directions of closed-loop neuromodulation treatments are also discussed. EXPERT OPINION: Recently, aDBS has been shown to offer benefits compared to open-loop DBS. Understanding the biomarkers of pathological states across various disorders is, however, crucial to implementation of aDBS, and improved sensing-capable hardware and advances in machine learning are poised to allow its effective implementation.
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".