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Toward Individualized Deep Brain Stimulation: A Stereoelectroencephalography-Based Workflow for Neurostimulation

Jeremy Saal1, Kelly Kadlec2, Anusha B Allawala1

  • 1UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA; Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA.

Neuromodulation : Journal of the International Neuromodulation Society
|December 13, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces a statistics-driven framework using stereoelectroencephalography (sEEG) to find personalized deep brain stimulation (DBS) targets for neuropsychiatric disorders. The method ensures statistically rigorous identification of effective stimulation sites.

Keywords:
Clinical workflowdeep brain stimulationneurostimulationpersonalized targetsstereoelectroencephalography

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Area of Science:

  • Neuroscience
  • Neurology
  • Psychiatry

Background:

  • Deep brain stimulation (DBS) is a growing treatment for neuropsychiatric conditions.
  • Individual symptom presentations and neural correlates necessitate personalized treatment approaches.
  • Identifying optimal stimulation sites is crucial for effective DBS therapy.

Purpose of the Study:

  • To develop and present a statistics-driven framework for stimulation testing using inpatient stereoelectroencephalography (sEEG).
  • To identify personalized therapeutic stimulation sites for subsequent DBS implantation.
  • To enhance the rigor and efficiency of stimulation site selection.

Main Methods:

  • Inpatient sEEG testing and symptom monitoring in 14 participants (MDD, chronic pain, OCD).
  • Integration of a Stimulation Testing Decision Tree with power analysis and effect size calculations.
  • Utilizing sham trials to estimate response variability and inform power analysis.

Main Results:

  • Effect sizes for stimulation-induced symptom changes ranged from -1.5 to +2.39.
  • Sham trial response standard deviation predicted stimulation response variability (R² = 0.67, p < 0.001).
  • Approximately ten sham trials are needed to estimate variability; ten trials per site ensure powered results for effect sizes ≥1.1.

Conclusions:

  • The presented workflow is adaptable across multiple neuropsychiatric indications.
  • The framework addresses challenges in stimulation site testing.
  • Incorporating sham trials, effect size, and tolerability testing identifies personalized and effective DBS sites.