Model-based Electrical Brain Stimulation
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|ClinicalTrials.gov Identifier: NCT05327387|
Recruitment Status : Recruiting
First Posted : April 14, 2022
Last Update Posted : April 14, 2022
Neuropsychiatric disorders are a leading cause of disability worldwide with depressive disorders being one of the most disabling among them. Also, millions of patients do not respond to current medications or psychotherapy, which makes it critical to find an alternative therapy. Applying electrical stimulation at various brain targets has shown promise but there is a critical need to improve efficacy.
Given inter- and intra-subject variabilities in neuropsychiatric disorders, this study aims to enable personalizing the stimulation therapy via i) tracking a patient's own symptoms based on their neural activity, and ii) a model of how their neural activity responds to stimulation therapy. The study will develop the modeling elements needed to realize a model-based personalized closed-loop system for electrical brain stimulation to achieve this aim.
The study will provide proof-of-concept demonstration in epilepsy patients who already have intracranial electroencephalography (iEEG) electrodes implanted for their standard clinical monitoring unrelated to this study, and who consent to being part of the study.
|Condition or disease||Intervention/treatment||Phase|
|Medication Refractory Epilepsy Patients With Electrodes Already Implanted Based on Clinical Criteria for Standard Monitoring||Other: model-based electrical brain stimulation||Not Applicable|
The investigators will conduct the study for each subject during their stay in the epilepsy monitoring unit (EMU), which is dictated purely based on their standard clinical needs unrelated to our study. iEEG will be recorded from each patient throughout their stay in the EMU, during which the self-reports from them will be also intermittently collected using validated questionnaires that relate to depression symptoms.
The investigators will build decoders that can track these depression symptoms from iEEG activity. The investigators will also apply electrical stimulation to learn a personalized input-output model that predicts the iEEG response to ongoing stimulation. The resulting personalized decoder and the input-output model will be combined to achieve model-based personalization of stimulation therapy.
Successful completion of this study will help enable precisely-tailored deep brain stimulation therapies across diverse conditions and have a broad public health impact.
|Study Type :||Interventional (Clinical Trial)|
|Estimated Enrollment :||25 participants|
|Intervention Model:||Single Group Assignment|
|Intervention Model Description:||In each patient, the investigators will test the decoders of the symptom level and the input-output models of the neural response to stimulation therapy.|
|Masking:||None (Open Label)|
|Primary Purpose:||Basic Science|
|Official Title:||Model-based Electrical Brain Stimulation|
|Actual Study Start Date :||February 8, 2022|
|Estimated Primary Completion Date :||March 31, 2026|
|Estimated Study Completion Date :||March 31, 2026|
|Experimental: model-based electrical brain stimulation||
Other: model-based electrical brain stimulation
Electrical pulse train stimulation delivered to medication refractory epilepsy patients with electrodes already implanted based on clinical criteria for standard monitoring unrelated to this study. The delivery of the electrical brain stimulation can be guided by neural biomarkers of symptom levels computed from ongoing neural activity and by input-output models of neural response to stimulation therapy. The parameters of electrical stimulation will be constrained to be within clinically safe ranges.
- Decoded depression symptom ratings based on neural activity [ Time Frame: 5-10 days ]A personalized decoder is trained for each patient using the recorded neural activity and self-reports. Then this decoder is used to estimate the biomarker purely from neural activity; that is, based on neural activity, it will return the estimation of depression symptom ratings (HAMD-6 or VAS self-reports)
- Hamilton Depression Rating (HAMD-6) self-reports [ Time Frame: 5-10 days ]Hamilton Depression Rating (HAMD-6) is a widely used questionnaire that measures depressive state severity and intervention response. It can range from 0 to 22, with 22 corresponding to the worst depression symptom. Self-reports are obtained intermittently from the patient.
- Visual Analog Scale (VAS) self-reports [ Time Frame: 5-10 days ]Visual Analog Scale (VAS) is a fast self-report validated against the Hamilton scale. It can range from 0 to 300, with 300 corresponding to the worst depression symptom. Self-reports are obtained intermittently from the patient.
To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.
Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT05327387
|Contact: Maryam M Shanechi, PhDemail@example.com|
|Contact: Omid G Sani, PhDfirstname.lastname@example.org|
|United States, California|
|University of Southern California||Recruiting|
|Los Angeles, California, United States, 90089|
|Contact: Maryam Shanechi, PhD 213-740-1377 email@example.com|
|Principal Investigator: Maryam M Shanechi, PhD|
|University of California, San Francisco||Recruiting|
|San Francisco, California, United States, 94143|
|Contact: Edward F Chang, MD 415-502-7346 firstname.lastname@example.org|
|Principal Investigator: Edward F Chang, MD|
|Principal Investigator:||Maryam M Shanechi, PhD||University of Southern California|