Epilepsy Clinical Trials

Depression is one of the most common disorders of mental health, affecting 7-8% of the population and causing tremendous disability to afflicted individuals and economic burden to society. In order to optimize existing treatments and develop improved ones, the investigators need a deeper understanding of the mechanistic basis of this complex disorder. Previous work in this area has made important progress but has two main limitations. (1) Most studies have used non-invasive and therefore imprecise measures of brain activity. (2) Black box modeling used to link neural activity to behavior remain difficult to interpret, and although sometimes successful in describing activity within certain contexts, may not generalize to new situations, provide mechanistic insight, or efficiently guide therapeutic interventions. To overcome these challenges, the investigators combine precise intracranial neural recordings in humans with a suite of new eXplainable Artificial Intelligence (XAI) approaches. The investigators have assembled a team of experimentalists and computational experts with combined experience sufficient for this task. Our unique dataset comprises two groups of subjects: the Epilepsy Cohort consists of patients with refractory epilepsy undergoing intracranial seizure monitoring, and the Depression Cohort consists of subjects in an NIH/BRAIN-funded research trial of deep brain stimulation for treatment-resistant depression (TRD). As a whole, this dataset provides precise, spatiotemporally resolved human intracranial recording and stimulation data across a wide dynamic range of depression severity. Our Aims apply a progressive approach to modeling and manipulating brain-behavior relationships. Aim 1 seeks to identify features of neural activity associated with mood states. Beginning with current state-of-the-art AI models and then uses a "ladder" approach to bridge to models of increasing expressiveness while imposing mechanistically explainable structure. Whereas Aim 1 focuses on self-reported mood level as the behavioral index of interest, Aim 2 uses an alternative approach of focusing on measurable neurobiological features inspired by the Research Domain Criteria (RDoC). These features, such as reward sensitivity, loss aversion, executive attention, etc. are extracted from behavioral task performance using a novel "inverse rational control" XAI approach. Relating these measures to neural activity patterns provides additional mechanistic and normative understanding of the neurobiology of depression. Aim 3 uses recurrent neural networks to model the consequences of richly varied patterns of multi-site intracranial stimulation on neural activity. Then employing an innovative "inception loop" XAI approach to derive stimulation strategies for open- and closed-loop control that can drive the neural system towards a desired, healthier state. If successful, this project would enhance our understanding of the pathophysiology of depression and improve neuromodulatory treatment strategies. This can also be applied to a host of other neurological and psychiatric disorders, taking an important step towards XAI-guided precision neuroscience. Read Less

Background: Epilepsy affects about 1 percent of the U.S. population. Most people with epilepsy respond well to medicine, but some do not. Researchers want people who have diagnosed or suspected epilepsy to participate in ongoing studies. They want to learn more about clinical care for epilepsy. They want fellows and residents to learn more about the care of people with epilepsy. Objectives: To learn more about seizures and find ways to best treat people with drug-resistant epilepsy. Eligibility: Adults and children ages 8 years and older with diagnosed or suspected epilepsy Design: Participants will be screened with: Physical exam Medical history Questionnaires Participants will have many visits. They may be admitted to the hospital for several weeks. Their medication might be stopped or changed. Participants will have many tests: Blood and urine tests EEG: Wires attached to the head with paste record brain waves. This may be videotaped. Thinking and memory tests MRI: Participants lie on a table that slides in and out of a tube. They perform simple tasks in the tube. MEG: Participants lie on a table and place their head in a helmet to record brain waves. PET scan: Participants lie on a table that slides into a machine. A small amount of radioactive dye is injected into their arm with an IV. For the IV, a small tube is inserted into the arm with a needle. Participants will stay enrolled in this study if they join other epilepsy-related studies. They may be contacted at intervals for follow-up. Their participation will end if they have not been seen clinically for their epilepsy for 3 years. Read Less

The acute and chronic effects of VNS stimulation on various on the autonomic nervous, cardiovascular, immune, and metabolic systems will be compared from noninvasive and minimally invasive physiological recordings and blood draws at various time points throughout the study. These interventions and assessments will be performed in individuals 18 years of age and older who are implanted with a VNS device, which consists of patients who have been diagnosed with drug resistant epilepsy or major depressive disorder. The REVEAL study is not a treatment study; its primary objective is to scientifically investigate the contributing roles of efferent versus afferent vagus nerve modulation of multiple peripheral organs and their dependence on stimulation parameters, in which participants are those who have been implanted with a VNS device be receive standard of care treatment for their epilepsy or depressive disorder. Read Less

The purpose of this study is to systematically evaluate the results of medical investigations to identify symptom and biological patterns and common etiologies of neurodevelopmental disorders. Read Less

This research is being done to determine if Mozart music and/or age-appropriate music can reduce the frequency of seizures and epileptiform discharges. Read Less

This study will investigate the role of coordinated brain rhythms during sleep in memory consolidation and determine whether playing precisely timed brief bursts of noise can enhance these rhythms and improve memory in epilepsy inpatients with implanted hippocampal electrodes. Read Less

We aim to determine the clinical utility of 'dynamic tractography': a novel method for visualizing electrical neural transfers that incorporates the underlying white matter tracts and supporting linguistic processing. We will also determine how well objective electrophysiology biomarkers will improve the prediction of language outcomes following epilepsy surgery. This project will ultimately optimize understanding of how the human brain develops its language network dynamics. Read Less

The objective is to understand how amygdala activation affects other medial temporal lobe structures to prioritize long-term memories. The project is relevant to disorders of memory and to disorders involving affect and memory, including traumatic brain injury and post-traumatic stress disorder. Read Less

The NSR-GENE study is a longitudinal cohort study of approximately 300 parent-child trios from the Neonatal Seizure Registry and participating site outpatient clinics that aims to evaluate whether and how genes alter the risk of post-neonatal epilepsy among children with acute provoked neonatal seizures. The researchers aim to develop prediction rules to stratify neonates into low, medium, and high risk for post-neonatal epilepsy based on clinical, electroencephalogram (EEG), magnetic resonance imaging (MRI), and genetic risk factors. Read Less

The Epilepsy Learning Health System (ELHS) is a quality improvement and research network to improve outcomes for people with epilepsy. The ELHS is designed as a model of value-based chronic care for epilepsy as envisioned by the National Academies of Medicine Committee in their landmark reports "The Learning Health System" and "Epilepsy Across the Spectrum: Promoting Health and Understanding". The ELHS network is a collaboration among clinicians, patients and researchers that promotes the use of data for multiple purposes including one-on-one clinical care, population management, quality improvement and research. The ELHS Registry includes data on children and adults with epilepsy collected during the process of standard epilepsy care. These data are used to create population health reports and to track changes in outcomes over time. ELHS teams use quality improvement methods, such as Plan-Do-Study-Act (PDSA) cycles, to continuously learn how to improve care. Read Less

Language is a signature human cognitive skill, but the precise computations that support language understanding remain unknown. This study aims to combine high-quality human neural data obtained through intracranial recordings with advances in computational modeling of human cognition to shed light on the construction and understanding of speech. Read Less

To generate preliminary safety and effectiveness data for brain-responsive neurostimulation of thalamocortical networks as an adjunctive therapy in reducing the frequency of generalized seizures in individuals 12 years of age or older with Lennox Gastaut Syndrome (LGS) who are refractory to antiseizure medications. The intent is to determine the feasibility and the optimal design of a subsequent pivotal study in order to expand the indication for use for the RNS System as a treatment for patients with medically intractable LGS. Read Less