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 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.
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 this 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 subject-specific decoders that can track these depression symptoms from iEEG activity. The investigators will also apply electrical stimulation to learn a subject-specific input-output model that predicts the iEEG response to ongoing stimulation. 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
Allocation
NA
Purpose
BASIC_SCIENCE
Masking
NONE
Enrollment
25
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.
University of Southern California
Los Angeles, California, United States
RECRUITINGUniversity of California, San Francisco
San Francisco, California, United States
RECRUITINGDecoded depression symptom ratings based on neural activity
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)
Time frame: 5-10 days
Hamilton Depression Rating (HAMD-6) self-reports
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.
Time frame: 5-10 days
Visual Analog Scale (VAS) self-reports
Visual Analog Scale (VAS) is a fast self-report validated against the Hamilton scale. It indicates the symptom level along a continuous line from none to worst symptom level. Self-reports are obtained intermittently from the patient.
Time frame: 5-10 days
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