ArticleNeuromodulation : journal of the International Neuromodulation Society2026
Toward Individualized Deep Brain Stimulation: A Stereoelectroencephalography-Based Workflow for Neurostimulation Target Identification.
Article in Neuromodulation : journal of the International Neuromodulation Society, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- Human intracranial signal stability tracks anatomical accuracy after electrode reimplantation.Journal of neural engineering · 2026Trial
- Billions Spent, Few Saved: Rethinking National Institutes of Health HEAL Initiative in Light of Dopaminergic Alternatives to the Opioid Trap.International journal of spine surgery · 2025Article
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16 authors.
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Abstract
objectivesDeep brain stimulation (DBS) is increasingly being used to treat a variety of neuropsychiatric conditions, many of which exhibit idiosyncratic symptom presentations and neural correlates across individuals. Thus, we have used inpatient stereoelectroencephalography (sEEG) to identify personalized therapeutic stimulation sites for long-term implantation of DBS. Informed by our experience, we have developed a statistics-driven framework for stimulation testing to identify therapeutic targets. MATERIALS AND
methodsFourteen participants (major depressive disorder = 6, chronic pain = 6, obsessive-compulsive disorder = 2) underwent inpatient testing using sEEG and symptom monitoring to identify personalized stimulation targets for subsequent DBS implantation. We present a structured approach to this sEEG testing, integrating a Stimulation Testing Decision Tree with power analysis and effect size considerations to inform adequately powered results to detect therapeutic stimulation sites with statistical rigor.
resultsEffect sizes (Hedges' g) of stimulation-induced symptom score changes ranged from -1.5 to +2.39. The SD of sham trial responses was a strong predictor of stimulation response variability, as confirmed by a leave-one-out cross-validated linear regression (R
conclusionsThe presented workflow is adaptable to multiple indications and is specifically designed to overcome key challenges experienced during stimulation site testing. Through incorporating sham trials, effect size calculations, and tolerability testing, the described approach can be used to identify personalized and clinically efficacious stimulation sites.
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