Sydney S. Cash - US grants

DESCRIPTION (provided by applicant): Epilepsy is a devastating illness affecting 3 million Americans. Unfortunately, we currently have only a rudimentary understanding of the intertwined issues of how to define the cortical areas which generate seizures and how those seizures start and spread. Based on preliminary data we posit that within the seizure onset zone epileptiform activity arises from deep cortical layers and then spreads via cortico-cortical connections to superficial layers. There is, consequently, a discernable physiological signature of the seizure focus and events leading to seizure initiation and propagation. We will test this hypothesis by recording synaptic activity, intrinsic currents, and action potential firing from all layers of human cortex during and between seizures using unique microelectrode arrays. Specifically, we aim to: 1. Demonstrate that the intracolumnar dynamics of interictal discharges depend on the location of that column in the epileptogenic network. We hypothesize that interictal discharges in the epileptogenic focus are generated by current sinks and increased neuronal firing in deep cortical layers, whereas propagated epileptiform discharges will show initial sinks and activation in middle and upper cortical layers. Such results are consistent with epileptiform activity arising from recurrent excitatory activity in deep cortical layers augmented by rebound intrinsic currents and delineate a microphysiological signature of ictogenic cortex. 2. Determine the role of different cortical layers and neuronal firing during seizure initiation. We expect that action potential firing in deep cortical layers within the seizure focus precedes overt seizure initiation. Further, we expect that these same layers are the site of current sinks during discharges that occur at seizure initiation. These features further define the seizure focus, shed light on how seizures start, and may provide a novel method for seizure prediction. 3. Examine the role of neuronal group dynamics during seizure spread. Finally, we hypothesize that from the focus, seizures spread by direct recruitment via projections to upper cortical layers. Further, for certain regions there will be increased involvement of deeper cortical layers as the seizure progresses correlated with an ability of that region to independently generate epileptiform discharges. Consistent with this evolution from direct recruitment to multi-focal autonomous event generation, analysis of functional coupling between cortical regions will show progression from tight to loose association. This description may further differentiate the seizure focus and suggest new strategies for interrupting seizure propagation. These aims address essential aspects of the neurophysiology of human seizures at an unprecedented level of detail and breadth. The results will lead to a clear mechanistic understanding of what constitutes the seizure focus in humans. This can lead to increased effectiveness of surgical management of medically refractory epilepsy, as well as innovative approaches to seizure prediction, detection and termination. PUBLIC HEALTH RELEVANCE: Epilepsy remains a devastating and poorly understood illness. The experiments proposed in this project utilize novel techniques to record detailed neuronal activity directly from human cortex before and during seizures. We hope to use these techniques to better appreciate the differences between cortical tissue that will and will not generate seizures and what happens in those different areas as seizures start and spread. The information obtained will allow us to understand the neuronal dynamics underlying epilepsy at an unprecedented level of resolution. This will foster the development of new approaches to seizure prediction, detection and termination as well as more effective surgical management of medically refractory focal epilepsy.

? DESCRIPTION (provided by applicant): Seizure focus delineation using spontaneous and stimulus evoked EEG features Abstract an estimated 50 million people worldwide suffer from epilepsy. Of these, it is expected that ~30% continue to have seizures despite maximal medical therapy. The seizures of these patients may be controlled through appropriate surgical intervention if the region of brain giving rise to seizure activity is full circumscribed. Buildingon preliminary work, this study will pursue three research aims focused on (a) using brief recordings of neural activity, sophisticated signal processing techniques and advanced decision algorithms to delineate the epileptogenic region in patients with intractable epilepsy; augment this procedure with (b) examinations of the stimulation-response characteristics of different brain regions and (c) move toward non-invasive methodologies including high-density scalp EEG and transcranial magnetic stimulation that leverage the above approaches. The other major goal of the proposed project is to allow Dr. Cash to build on a successful record of mentoring and build a mentoring program tailored to the needs of residents and fellows in neurology who are preparing for a career in patient oriented research. The primary aims of this aspect of the proposal are to (a) bolster existing individual mentoring capabilities, (b) create group based career development experiences and (c) broaden the ability of residents and fellows to obtain mentoring and foundational research experiences in translational neuroscience. These goals ultimately are intended to greatly improve the ability of highly qualified, motived junior investigators to reach independence and begin productive patient-oriented research careers.

ABSTRACT In the course of a day we naturally make multiple shifts in our overall cognitive state and in our aims and intents. We go from sleep to awake, from internal dialogue to external communication, from relative immobility to planned complex movements. The neural activity which distinguishes these different high-level states is unknown and yet is a fundamental aspect to understanding overall cognitive processes. It is also a baseline substrate that is adversely impacted by a wide range of neuropsychiatric diseases. Our understanding of human cortical neurophysiology is almost entirely based on cognitive processes examined within the constraints of experimentally controlled tasks with time-locked, stimulus-driven behaviors. However, brain activity is fluid and continuous; much of our essential cognitive activity is not externally triggered but internally generated. The overarching goal of this research is to create platforms which allow for continuous acquisition of high-fidelity neural ensemble activity synchronized with behavioral data and contextual information to allow investigations into volitional changes in focus and intent. Data will be acquired from two groups of patients: those undergoing intracranial exploration for treatment of their epilepsy and patients implanted with multi- electrode arrays as part of the BrainGate clinical trial to restore communication and mobility to people with paralysis. Using this novel paradigm for investigation, we will explore the neural basis for changes in state which are dominated by receptive activities, internal thought and external interaction. We initially focus on motor behavior with a traditional task construction constraining the participant to watch, imagine and then attempt or actually move. We expand this to spontaneous activity in Aim 2. Finally, we move toward more general and abstracted investigations of volitional state by looking at an analogous task and spontaneous behavior with respect to language and communication (Aim 3). At each stage we will employ spectral, functional connectivity and data mining techniques to understand the neural underpinnings of these different states as well as the temporal dynamics that portend changes in state. Supporting all of these aims will be improvements and expansions in state-of-the-art human micro- and mesoscale neural recording environments to enable the study of continuous, real-time neural activity underlying state changes. Across aims we will explore the extent to which motor cortex alone contains the information which may be present in more widespread and higher order cortical regions. Our hypothesis is that motor cortex, does in fact, encode significant information about state in ways which encapsulate or summarize the information available in more wide spread regions. Most importantly, the questions inherent in this research are key to understanding human thought patterns at a fundamental level. This understanding has important implications not just for basic cognitive neuroscience but for our understanding of the processes which are altered in a wide range of neuropsychiatric disorders such as epilepsy, the dementias, depression, and psychosis. The results of these studies are also essential for the practical instantiation of effective brain-machine interfaces which would allow patients to act autonomously.

Project Abstract: Establishing a Brain Health Index from the Sleep Electroencephalogram Although cognitive decline is a ?normal? part of aging, some individuals clearly age better than others. However, the concept of differential aging has been minimally studied for the brain. Electroencephalogram (EEG) oscillations signals carry rich information regarding brain health and brain aging. Alzheimer's disease (AD) is associated with fragmented sleep and altered sleep oscillations. Clearance of cerebral beta amyloid through the brain's glymphatic drainage system occurs mainly in non-rapid eye movement (NREM) sleep, and depends on EEG slow oscillations. Cortical generators of sleep EEG oscillations overlap with regions of cortical thinning and loss of functional connectivity in AD. Disturbances of NREM disrupt memory consolidation. Finally, deficient REM sleep contributes to dementia. These observations suggest that brain health may be measurable from information contained in the sleep EEG. In preliminary work we have developed EEG-brain age ? a machine learning model that predicts a patient's age based on patterns of overnight sleeping EEG oscillations. This allows prediction of age with a precision of +/- 7 years. Our preliminary data suggest diabetes and hypertension, chronic HIV infection, an MCI or AD are reflected in the EEG as excessive brain age, and that excessive brain age is independently associated with reduced life expectancy. Our central hypothesis is that sleep physiology data can provide sensitive and specific biomarkers of brain health. This hypothesis is based on our prior work showing that BAI is elevated in several clinical populations. BAI can be accurately calculated using frontal EEG signals, making it suitable for implementation on at-home EEG devices. The rationale for the proposed research is that validating sleep EEG-derived biomarkers as measures of brain health at the level of individual patients would lay the ground for use in clinical trials and patient care. We plan to accomplish the central objective by pursuing two complementary aims. In Aim 1, we will take a hypothesis-driven approach, and test for associations of specific sleep features with specific cognitive deficits and specific structural pathology. In Aim 2, we will take ad data-driven approach, and develop optimized biomarkers of brain health using a novel form of machine learning known as multitask learning, which combine multiple features of sleep ? including conventional features, as well as data-driven features directly learned from the data ? to predict or ?explain? variation in cognitive performance and in structural brain MRI measures that are indicative of brain health or disease. The project will take advantage of a large and diverse set of sleep data (>33,000 patients), as well as thousands of brain MRI and cognitive testing results. At the conclusion of this study, we expect to have a better understanding of the role sleep oscillations play in brain health, and clinically useful brain health biomarkers. These outcomes will aid development of interventions to promote brain health.