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
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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 |
Allocation: | N/A |
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 |

Arm | Intervention/treatment |
---|---|
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.

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Ages Eligible for Study: | 18 Years and older (Adult, Older Adult) |
Sexes Eligible for Study: | All |
Accepts Healthy Volunteers: | No |
Inclusion Criteria:
- Patients being evaluated for surgical treatment of medication refractory epilepsy and brain tumors will be studied. ONLY patients with electrodes implanted based on clinical criteria to locate their seizure focus will be studied. Most patients are healthy adults, outside of their epilepsy and/or brain tumor.
- Subjects >= 18 are only included in this study.
- All patients with the above conditions and with implanted electrode arrays who are willing to participate and able to cooperate and follow research instructions will be recruited. However, analysis of research recording data will focus on those subjects with an IQ >= 80, with no impairments of reading, naming, or articulation (to minimize confounds such as abnormal language processing that may affect their self-reporting with the questionnaire), and with no cerebral pathology affecting the cortical regions from which recordings are made.
Exclusion Criteria:
- Subjects < 18 years old will be excluded from this study due to the high concordance of developmental disorders (cognitive and language-related) in pediatric epilepsies.
- There will be no involvement of special classes of subjects, such as fetuses, neonates, pregnant women, children, prisoners, institutionalized individuals, or others who may be considered vulnerable populations.
- Patients who are unable to give informed consent due to a brain disorder will be excluded from the study, as it is very likely that they would be unable to carry out the tasks demanded by the study.

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, PhD | 213-740-1377 | shanechi@usc.edu | |
Contact: Omid G Sani, PhD | 213-740-1377 | ghasemsa@usc.edu |
United States, California | |
University of Southern California | Recruiting |
Los Angeles, California, United States, 90089 | |
Contact: Maryam Shanechi, PhD 213-740-1377 shanechi@usc.edu | |
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 edward.chang@ucsf.edu | |
Principal Investigator: Edward F Chang, MD |
Principal Investigator: | Maryam M Shanechi, PhD | University of Southern California |
Responsible Party: | Maryam Shanechi, Associate Professor of Electrical and Computer Engineering and Biomedical Engineering, University of Southern California |
ClinicalTrials.gov Identifier: | NCT05327387 |
Other Study ID Numbers: |
HS-21-00108 R01MH123770 ( U.S. NIH Grant/Contract ) DP2MH126378 ( U.S. NIH Grant/Contract ) |
First Posted: | April 14, 2022 Key Record Dates |
Last Update Posted: | April 14, 2022 |
Last Verified: | April 2022 |
Individual Participant Data (IPD) Sharing Statement: | |
Plan to Share IPD: | Yes |
Plan Description: | Upon completion of the study and after publication, fully de-identified IPD can be made available for research purposes. |
Supporting Materials: |
Analytic Code |
Time Frame: | The sharing will happen upon completion of the study and after publication. |
Access Criteria: | Data will be accessed through data publishing platforms such as the NIH/NIMH Data Archive (NDA). |
Studies a U.S. FDA-regulated Drug Product: | No |
Studies a U.S. FDA-regulated Device Product: | No |
deep brain stimulation model-based stimulation closed-loop stimulation neural biomarkers of depression |
neurotechnology neuropsychiatric disorders depression brain-machine interface |
Drug Resistant Epilepsy Epilepsy Brain Diseases Central Nervous System Diseases Nervous System Diseases |