Abstract
Summary:Responsive neurostimulation and deep brain stimulation have emerged as effective intracranial neuromodulation therapies for drug-resistant epilepsy when surgical resection is not an option. However, programming these devices presents unique challenges in epilepsy. Without immediate feedback and a vast programming space, clinicians are often tasked with fine-tuning device settings without clear, mechanistic guidance and limited clinical time. Recent efforts toward individualized programming have shown promise, including the use of nonstandard parameter sets, target-specific stimulation strategies, and patient-tailored adaptations while avoiding unintended interference with critical functions such as emotional regulation. Emerging research in programming is shifting beyond the one-size-fits-all protocols, incorporating closed-loop biomarkers, integrating multimodal data and predictive modeling that hold promise for improving seizure control and reducing adverse effects. This review synthesizes current evidence on standard and individualized programming approaches for deep brain stimulation and responsive neurostimulation in epilepsy, highlighting practical strategies, clinical outcomes, and insights from recent studies. Although emerging tools such as biomarker-guided programming and predictive modeling are gaining interest, the focus of this review is on existing clinical literature shaping programming today. copy; by the American Clinical Neurophysiology Society. Unauthorized reproduction of this article is prohibited.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 513-520 |
| Number of pages | 8 |
| Journal | Journal of Clinical Neurophysiology |
| Volume | 42 |
| Issue number | 6 |
| DOIs | |
| State | Published - Sep 1 2025 |
Bibliographical note
Publisher Copyright:© 2025 Lippincott Williams and Wilkins. All rights reserved.
Keywords
- Adaptive stimulation
- DBS
- Individualized therapy
- Programming parameters
- RNS
PubMed: MeSH publication types
- Journal Article
- Review
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