Gregory Worrell - US grants

DESCRIPTION (provided by applicant): Worldwide, 50 million people suffer from epilepsy, and for 25% of these patients the seizures are not controlled by any available medical or surgical treatments. Development of new treatment options and improving the efficacy of epilepsy surgery are presently limited by our poor understanding of how epileptic brain generates spontaneous seizures (ictogenesis). There is accumulating evidence that high-frequency epileptiform oscillations (60 - 500 Hz) are a unique signature of epileptic brain, and play an important role in neocortical seizure ictogenesis [1-3]. As part of a program to develop the principal investigator's (PI) career as a clinician-investigator, we propose a multidisciplinary collaboration between the Mayo Clinic and University of Pennsylvania directed at understanding neocortical ictogenesis and improving the ability to localize regions of epileptogenic brain. This project is an initial step toward a more complete understanding of a common, and difficult to treat, neurological disease. We will develop bioengineering methods to detect and quantify high-frequency epileptiform oscillations (HFEO) from human intracranial EEG recordings. We will investigate the clinical usefulness of HFEO as a signature of epileptogenic brain for epilepsy surgery and seizure prediction. We believe understanding the cellular and network mechanisms underlying HFEO will improve our ability to localize regions of focal epileptogenic brain, an area presently limiting the success of epilepsy surgery, while laying the foundation for the rational development of new therapies such as implantable devices for seizure prediction and prevention. The proposed project will continue a collaboration that combines the neuroscience and neuroengineering strengths of the University of Pennsylvania with the clinical strength of the Mayo Clinic's large surgical epilepsy practice, thus providing a fertile environment for a developing clinician-investigator. The principal investigator has demonstrated potential for independent patient-based research, and with the training provided by this project will develop an independent research program translating advances in neuroengineering and clinical research into clinical practice.

DESCRIPTION (provided by applicant): The goal of this proposal is to localize human epileptic networks by characterizing their electrophysiological activity over a wide range of spatiotemporal scales. Decades of clinical intracranial EEG (IEEG) using restricted spatial (centimeter scale) and temporal (~0.5-100 Hz) bandwidth, based more on tradition than modern neuroscience, have frustrated epileptologists looking for discrete, resectable "electrographic lesions" during evaluation for epilepsy surgery. Similarly, recent efforts to apply direct brain stimulation to abort seizures after they are sufficiently established to be detected on standard clinical macroelectrodes have, so far, met with only partial success. We hypothesize that enhancing the spatial and temporal resolution of clinical intracranial EEG can improve the efficacy of epilepsy surgery and responsive brain stimulation to control seizures. Human epileptic networks produce pathological activity that ranges from seizures and spikes, generated by cubic centimeters of brain tissue, to high frequency oscillations that occur on sub-millimeter dimensions. Recent evidence suggests that important components of these signals are found at frequencies not detected by standard clinical IEEG. Using simultaneous IEEG recordings from microwire arrays and clinical macroelectrodes, our group has begun to characterize two potential signatures of epileptogenic brain, high frequency oscillations and "micro-seizures," that are outside the resolution of conventional clinical IEEG. In this application, we propose analysis of continuous, high-resolution, wide- bandwidth IEEG recorded simultaneously from microwire arrays and clinical macroelectrodes in order to localize human epileptic networks. We will correlate our findings with surgical outcome, prospectively, in a cohort of patients undergoing evaluation for epilepsy surgery. This work builds upon our established effort in Translational Neuroengineering melding state of the art epilepsy care with cutting-edge research. PUBLIC HEALTH RELEVANCE The neuronal networks of human epileptic brain are multiscale;extending from cellular assemblies organized on the scale of cortical columns (~300 - 600

DESCRIPTION: Despite taking daily medications, over 1/3 of patients with epilepsy continue to have seizures, and many more experience significant adverse side effects from antiepileptic drugs (AED). Though patients may spend as little as 0.01% of their time actually having seizures, they must maintain chronic therapeutic AED levels for years to decades. The reason AEDs are taken daily for seizures that only occur sporadically, and in many cases infrequently, is because patients do not know when a seizure will strike. Arguably the unpredictability of seizures and the adverse cognitive and physical side effects associated with AEDs, are the most disabling aspects of epilepsy. We now have compelling evidence from humans that seizures are not random events, but rather are associated with intracranial EEG (lEEG) changes that occur tens of minutes to hours before clinical events. This research has lead NeuroVista Inc. to develop a seizure advisory system (SAS) that uses iEEG and machine learning algorithms to track the probability of seizure occurrence. Using patient specific algorithms NeuroVista's SAS can forecast periods of increased and decreased seizure likelihood with high sensitivity and specificity, benchmarked against a chance predictor. NeuroVista's SAS has been validated in humans undergoing IEEG monitoring for epilepsy surgery, and has recently been approved for a human pilot clinical trial in Australia. We propose to use the NeuroVista's SAS device to guide the delivery of AEDs. We hypothesize that intelligent delivery of AEDs at times of increased seizure likelihood will effectively prevent clinical seizures. During periods of low seizure likelihood AEDs would not be required, reducing side effects. In this proposal we develop and test neurophysiologically-based responsive pharmacotherapy in naturally occurring canine epilepsy as the first step in creating a new treatment paradigm for medically resistant human partial epilepsy. Naturally occurring canine partial epilepsy is an ideal model for developing this therapy because of the clinical, physiological, and pharmacological similarities between canine and human partial epilepsy. In addition, dogs are large enough to tolerate implantation of the human SAS device. This project will lead to submission of an investigational device exemption to conduct a first-in-human clinical trial of SAS guided responsive AED therapy. Disclaimer: Please note that the following critiques were prepared by the reviewers prior to the Study Section meeting and are provided in an essentially unedited form. While there is opportunity for the reviewers to update or revise their written evaluation, based upon the group's discussion, there is no guarantee that individual critiques have been updated subsequent to the discussion at the meeting. Therefore, the critiques may not fully reflect the final opinions of th individual reviewers at the close of group discussion or the final majority opinion of the group. Thus the Resume and Summary of Discussion is the final word on what the reviewers actually considered critical at the meeting.

DESCRIPTION (provided by applicant): The goal of this proposal is to localize human epileptic networks by characterizing their electrophysiological activity over a wide range of spatiotemporal scales. Decades of clinical intracranial EEG (IEEG) using restricted spatial (centimeter scale) and temporal (~0.5-100 Hz) bandwidth, based more on tradition than modern neuroscience, have frustrated epileptologists looking for discrete, resectable electrographic lesions during evaluation for epilepsy surgery. Similarly, recent efforts to apply direct brain stimulation to abort seizures after they are sufficiently established to be detected on standard clinical macroelectrodes have, so far, met with only partial success. We hypothesize that enhancing the spatial and temporal resolution of clinical intracranial EEG can improve the efficacy of epilepsy surgery and responsive brain stimulation to control seizures. Human epileptic networks produce pathological activity that ranges from seizures and spikes, generated by cubic centimeters of brain tissue, to high frequency oscillations that occur on sub-millimeter dimensions. Recent evidence suggests that important components of these signals are found at frequencies not detected by standard clinical IEEG. Using simultaneous IEEG recordings from microwire arrays and clinical macroelectrodes, our group has begun to characterize two potential signatures of epileptogenic brain, high frequency oscillations and micro-seizures, that are outside the resolution of conventional clinical IEEG. In this application, we propose analysis of continuous, high-resolution, wide- bandwidth IEEG recorded simultaneously from microwire arrays and clinical macroelectrodes in order to localize human epileptic networks. We will correlate our findings with surgical outcome, prospectively, in a cohort of patients undergoing evaluation for epilepsy surgery. This work builds upon our established effort in Translational Neuroengineering melding state of the art epilepsy care with cutting-edge research.

? DESCRIPTION (provided by applicant): Approximately 1/3 of people living with epilepsy (PWE) continue to have seizures despite anti-epileptic drugs (AEDs). Recent trials using therapeutic brain stimulation show reductions in seizures, but rarely provide seizure free outcomes. Although seizures occupy a small fraction of their life, as little as 0.01%, PWE take anti-epileptic drugs (AED) daily, suffer AED related side effects, and spend their lives dreading when the next seizure will strike. The apparent randomness of seizures is associated with significant psychological consequences. We hypothesize that epilepsy can be more effectively managed, both the seizures and their psychological impact, by providing patients with accurate seizure diaries, real-time seizure forecasting, and responsive stimulation for brain state modulation. With accurate seizure forecasting patients would be empowered to manage their life activities. The optimal epilepsy management device requires: 1) Automated seizure detection 2) Accurate Automated Electronic Seizure Diaries 3) Seizure Forecasting and 4) Programmable Brain Stimulation. In this grant we develop an epilepsy management and therapy platform using Medtronic's 3rd generation device implantable device. The RC+S provides chronic nervous system sensing and analytics using embedded scientific instrumentation (e.g. - sensors, classification, and control policy implementation), and provides a unique opportunity for exploring and managing epileptic neural networks.

? DESCRIPTION (provided by applicant): For most individuals living with epilepsy, seizures are relatively infrequent events occupying a small fraction of their life. Despite spending as little a 0.01% of their lives having seizures (typically only minutes per month), people with epilepsy take anti-epileptic drugs (AED) daily, suffer AED related side effects, and spend their lives dreading when the next seizure will strike. The apparent randomness of seizures is associated with significant psychological consequences. In addition, despite daily AED approximately 1/3 of patients continue to have seizures. We hypothesize that epilepsy can be more effectively treated, both the seizures and their psychological impact, by providing patients with real-time seizure forecasting. Periods of low seizure probability would not require AEDs, or at least lower doses of AEDs, thus reducing AED exposure and their side effects. Periods of high seizure probability may respond to acute AED and patients could alter their activities to avoid injury. Patients would be empowered to manage their medications and life activities using reliable seizure forecasts. In this grant we investigate the hypothesis that seizures are predictable events, and pursue accurate, clinically relevant seizure forecasting using recent advances in support vector machines (SVM), data-analytic models, and Universum-SVM applied to continuous intracranial EEG (iEEG) in focal canine epilepsy. This is an initial step in establishin a new treatment paradigm for focal epilepsy, whereby the probability of seizure occurrence is continuously tracked for patient warning and intelligent responsive therapies. Naturally occurring focal canine epilepsy is an excellent model for investigation of seizure forecasting because of the clinical and electrophsyiological similarity to focal human epilepsy. This study provides a unique opportunity to study seizure forecasting in naturally occurring canine epilepsy under uniform conditions (the same environment). Importantly, dogs are large enough to accommodate devices designed for human use. The hypotheses driving this proposal are that focal seizures are not random events and there are brain states associated with low or high probability of seizure occurrence, and that these states can be reliably classified using machine learning approaches (SVM & Universum-SVM) that combine features from iEEG, behavioral state tracking, and electrocardiogram (ECG) heart rate variability. The goal of this proposal is to develop reliable seizure forecasting (when possible) and improved understanding (data characterization) when good forecasting is not possible.

There is a critical unmet need to identify new strategies to control seizures in individuals with epilepsy who fail to respond to currently available drugs. Many of these individuals undergo invasive surgical resection of electroencephalographically aberrant tissue. However, seizures are likely to recur in up to half of these subjects within 5 years of surgery. Resistance to therapies that target electrophysiological mechanisms of aberrant neural activity coupled to post-surgical recurrence of seizures in previously non-ictal tissue may indicate a role for epileptogenic drivers that are non-neural and self-amplifying. Multiple studies have demonstrated changes in peripheral inflammatory factors in individuals with epilepsy, and steroids and other immunomodulatory therapies have proven effective in some patients. Likewise, evidence from animal models clearly supports a role for cytokines such as TNF? and IL1? in seizure activity. Therefore, neuroinflammation may be a critical driver of drug-resistant epilepsy. The central hypothesis of this proposal is that aberrant neural activity triggers local release of chemokines and cytokines that promote infiltration of innate inflammatory effector cells, production of additional inflammatory mediators, and further disruption of neural circuitry. Breaking this cycle may stop ictogenesis and/or epileptogenesis. The specific hypothesis of this proposal is that levels of the chemoattractant CCL2 and the effector cytokines TNF?, IL1?, and/or IL6 are elevated in spatial and temporal association with chemically induced epileptiform activity. This hypothesis will be tested using a strategy based on simultaneous collection of intracortical EEG activity and large molecule microdialysis to measure inflammatory mediators in the extracellular fluid of the peri-electrode space in mice and pigs and in humans undergoing resective surgery for drug-resistant epilepsy. Despite circumstantial evidence in humans indicating a role for inflammation in seizure disorders and epilepsy, no study has yet measured the in situ inflammatory characteristics of the epileptic brain or assessed the relationship between epileptiform activity and local release of inflammatory molecules. Though brain microdialysis has been established as a technique in the neurocritical care setting for assessment of small molecules, this study will be the first to employ an innovative strategy that combines intracranial EEG collection and the use of high molecular weight cut-off membranes (100 kDa) for the capture of chemokines and cytokines in the peri- electrode space. These experiments are significant as they will provide novel insights into the role of inflammatory mediators as both cause and effect of neural circuit dysfunction and they may identify individual inflammatory drivers that can be targeted for personalized treatment strategies. Regardless of outcomes, this study will generate new, fundamental knowledge about the interplay between seizure activity and inflammation. Understanding this relationship may provide support for the use of immunomodulatory therapies in the millions of individuals with epilepsy that are currently underserved by current standards of care.

PROJECT SUMMARY/ABSTRACT: Electrical brain stimulation (EBS) is a FDA-approved neuromodulation therapy applied to several neurological disorders. However, the molecular basis of its efficacy remains unclear. Here we propose investigation of a glial mechanism for EBS mediated by astrocytes-derived extracellular vesicles (EVs). We recently discovered from both in vitro and in vivo experiments that electrical stimulation affects the release of EVs from astrocytes. In this proposal we will address two questions: 1) what is the molecular mechanism of electrical stimulation induced EVs release; 2) what is the biological function of the EVs released under electrical stimulations. Our exploratory research plan includes the following three steps: First - molecular characterization of astrocytic EVs (Aim1). In this aim we start from primary cultured astrocytes and systematically evaluate the effect of electrical stimulation parameters on EV cargos; Second - molecular mechanisms of how stimulation affects astrocytic EVs (Aim 2). In this aim we apply a high-resolution imaging technique to primary cultured astrocytes and focus on the trafficking of intracellular vesicles, including vesicle fusion to or budding off the plasma membrane. Third - functional characterizations of astrocytic EVs (Aim 3). In this aim, we will subject purified EVs collected in step 1 to both in vitro and in vivo functional testing. Focusing on neuronal activities as readout, we will first examine EV functions on primary cultured neurons; then we use in vivo animal models combined with 2-photon microscope technology to examine how EVs affect neuronal activities in both short- and long-term periods, and also how EVs affect animal behavior. In summary, our findings will help guide optimization of stimulation with next-generation EBS devices, with the ultimate goal of enhancing efficacy and treatments for patients with neurological disorders.