Candidate: Dr. Stacey has the clinical and research expertise necessary to embark on his career goal as a tenure-track physician-scientist. He is Board-certified in Neurology and has completed an epilepsy fellowship. He has been engaged in multiple productive research endeavors in Bioengineering for over 15 years, earning a PhD with Dominique Durand, a pioneer in neural engineering. He has obtained competitive research grants and awards throughout his career, has several publications, and is demonstrating current productivity. His experience uniquely qualifies him to engage in the current research proposal and career plan, merging clinical knowledge of epilepsy and electroencephalography with a strong neurophysiologic and computational background. Environment: The University of Pennsylvania is a rich environment for both research and clinical endeavors, and the Department of Neurology is home to several successful K08 and K23 applicants. The lab and clinical space necessary to perform the proposed work are all within a single city block. Dr. Stacey has established strong collaborative ties to several researchers at Penn that will enable this work to succeed. A key aspect of this proposal is that Dr. Stacey already has a faculty position as an Instructor and has established a schedule with 80% protected research time for over 2 years now. This protected time will continue, following the schedule already established in the past year as Instructor and before that as a fellow. Both the Department of Neurology and Department of Bioengineering have given enthusiastic support for Dr. Stacey's career development. Dr. Stacey already has lab space in Dr. Litt's lab and is using the computing power and experimental data described in this proposal, resources which have produced publication in 2009, a second under revision at present, and additional work that has resulted in speaking invitations to international meetings. Dr. Litt has fully committed to provide the ongoing infrastructure and mentoring necessary to propel forward Dr. Stacey's research and his career as a physician-scientist. Research: A large number of people with epilepsy continue to have uncontrolled seizures despite the best available therapies. Currently available antiepileptic devices use electrical brain stimulation to arrest seizures. Although some moderate success using these therapies has been demonstrated, a better understanding of seizure generation and the role of electrical stimulation will lead to more effective second-generation devices. Recent evidence suggests that fast ripples (and other high-frequency oscillations) localize to epileptic networks and share the same pathology as epileptic tissue. I hypothesize that fast ripples, and the pathologic tissue that produces them, are integral to seizure generation and will thereby provide an ideal target for the rational development of new brain stimulation protocols. This project will use biophysically accurate computer simulations of fast ripples, iteratively based on human recordings, to design and test new stimulation protocols to control seizures. Focusing on a specific, highly localizable network phenomenon will allow for validation of the simulated results and comparison with clinically measurable parameters, critical aspects of computational modeling that have been difficult using more general simulation approaches in epilepsy research.
The Specific Aims of this proposal describe a method to design and validate models of fast ripples, then use them to test different forms of stimulation.
Aim 1 : To develop and use a computer model of the hippocampus to determine which pathological changes in epileptic tissue: interneuronal loss, gap junctions, recurrent axons, ephaptic effects and synaptic inputs, are responsible for generating Fast Ripples.
Aim 2 : To validate findings of the computer predictions in Aim 1 using data from human microelectrode recordings and animal models.
Aim 3 : To determine which electrical stimulus paradigms are most effective in disrupting Fast Ripples in the computer model, and how the network output will change with those stimuli. Later work, beyond the scope of this proposal, will take stimuli that are successful in the computer model and deploy them in rat models of epilepsy and eventually in human stimulation trials. The likely results of these studies will be more effective second-generation antiepileptic devices that direct targeted closed-loop stimulation to discrete regions vital to seizure generation.
Epilepsy is a very common disease, and 25% of affected people continue to have seizures despite best available therapies. Brain stimulation devices show great potential in controlling seizures, but early results have been somewhat limited. The goal of this proposal is to develop and test new stimulation methods that can improve the efficacy of antiseizure devices, providing new treatment options for people with uncontrolled epilepsy.
|Gliske, Stephen V; Stacey, William C; Moon, Kevin R et al. (2016) THE INTRINSIC VALUE OF HFO FEATURES AS A BIOMARKER OF EPILEPTIC ACTIVITY. Proc IEEE Int Conf Acoust Speech Signal Process 2016:6290-6294|
|Gliske, Stephen V; Irwin, Zachary T; Davis, Kathryn A et al. (2016) Universal automated high frequency oscillation detector for real-time, long term EEG. Clin Neurophysiol 127:1057-66|
|Gliske, Stephen V; Irwin, Zachary T; Chestek, Cynthia et al. (2016) Effect of sampling rate and filter settings on High Frequency Oscillation detections. Clin Neurophysiol 127:3042-50|
|Spinelli, Elena; Davis, Ryan P; Ren, Xiaodan et al. (2016) Thrombolytic-Enhanced Extracorporeal Cardiopulmonary Resuscitation After Prolonged Cardiac Arrest. Crit Care Med 44:e58-69|
|Fink, Christian G; Gliske, Stephen; Catoni, Nicholas et al. (2015) Network Mechanisms Generating Abnormal and Normal Hippocampal High-Frequency Oscillations: A Computational Analysis. eNeuro 2:|
|Jirsa, Viktor K; Stacey, William C; Quilichini, Pascale P et al. (2014) On the nature of seizure dynamics. Brain 137:2210-30|
|Stacey, William C; Kellis, Spencer; Greger, Bradley et al. (2013) Potential for unreliable interpretation of EEG recorded with microelectrodes. Epilepsia 54:1391-401|
|Pearce, Allison; Wulsin, Drausin; Blanco, Justin A et al. (2013) Temporal changes of neocortical high-frequency oscillations in epilepsy. J Neurophysiol 110:1167-79|
|Stacey, William C; Kellis, Spencer; Patel, Paras R et al. (2012) Signal distortion from microelectrodes in clinical EEG acquisition systems. J Neural Eng 9:056007|
|Blanco, Justin A; Stead, Matt; Krieger, Abba et al. (2011) Data mining neocortical high-frequency oscillations in epilepsy and controls. Brain 134:2948-59|
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