William Charles Stacey, MD, PhD
Professor of Neurology
Professor of Biomedical Engineering
[email protected]

Available to mentor

William Charles Stacey, MD, PhD
Professor
  • About
  • Links
  • Center Memberships
  • Research Overview
  • Recent Publications
  • About

    I am a clinical epileptologist and physician scientist and spend the majority of my time doing neural engineering research. My dual training represents over 20 years of dedication to my career goal: to develop improved epilepsy devices and therapies with engineering tools and quantitative analysis of brain signals. My research integrates the wide range of training I have undertaken: clinical epileptology, computational neuroscience, advanced mathematical and engineering tools, basic electrophysiology, and translational research. From the beginning of my career, I have investigated the physiological methods by which neural ensembles detect and synchronize to rhythmic signals, and stimulation paradigms that can stop seizures.

    Much of my work has focused on biomarkers of epilepsy such as High Frequency Oscillations (HFOs). This work spans animal models, computational models, and analysis of human data. Overarching all of these is developing quantitative tools that can describe the phenomena on analogous terms across all models and in humans. I have developed tools to automatically detect and process HFOs in human EEG. This combination of clinical, computational, and machine learning tools is crucial in understanding the mechanisms and features of epilepsy.

    A separate line of research involves understanding and manipulating the underlying dynamics of seizures. My collaborators and I developed a novel method of characterizing seizures based upon their dynamics. Using seizure data from many species and human EEG, we modeled the onset and offset of seizures by focusing on the invariant properties of the most common bifurcations, then made a taxonomy of seizures in human epilepsy. The result was the Taxonomy of Seizure Dynamics, which found all predicted bifurcations in human seizures. This work was able to explain several unusual epileptic phenomena and has enabled a novel branch of epilepsy research in which we characterize how the brain state can move and influence seizure activity. Our ongoing collaboration, combining the disciplines of physics, engineering, neuroscience, and clinical epilepsy, is focused on leveraging this model to improve our understanding and treatment options in epilepsy.

    Overlying all of our work is the goal of acquiring better neural data, interpreting it with advanced tools, and manipulating the system to control seizures better. This goal has led us to several novel quantitative tools and robust findings, each with the overriding goal of implementation into humans.

    Links
    • Stacey Lab Website
    Center Memberships
    • Center Member
      Biointerfaces Institute
    Research Overview

    The lab uses a combination of electrophysiology, machine learning, signal processing, and computational modeling to model and describe neural data. Data for these projects are acquired from a large database of human patients, an ongoing clinical study in patients undergoing surgical implantation of electrodes, and several outside collaborations in other models. The lab is specifically researching the relationship of high frequency oscillations with seizure mechanisms, developing methods to target and stimulate the brain to stop seizures, and methods to quantify seizure dynamics.

    Recent Publications See All Publications
    • Journal Article
      Spike ripples localize the epileptogenic zone best: an international intracranial study.
      Shi W, Shaw D, Walsh KG, Han X, Eden UT, Richardson RM, Gliske SV, Jacobs J, Brinkmann BH, Worrell GA, Stacey WC, Frauscher B, Thomas J, Kramer MA, Chu CJ. Brain, 2024 Feb 7; DOI:10.1093/brain/awae037
      PMID: 38325327
    • Journal Article
      Estimation of Circular Statistics in the Presence of Measurement Bias.
      Alsammani A, Stacey WC, Gliske SV. IEEE J Biomed Health Inform, 2024 Feb; 28 (2): 1089 - 1100. DOI:10.1109/JBHI.2023.3334684
      PMID: 38032776
    • Journal Article
      High frequency oscillation network dynamics predict outcome in non-palliative epilepsy surgery.
      Lin J, Smith GC, Gliske SV, Zochowski M, Shedden K, Stacey WC. Brain Commun, 2024 6 (1): fcae032 DOI:10.1093/braincomms/fcae032
      PMID: 38384998
    • Journal Article
      Passive and active markers of cortical excitability in epilepsy.
      Ramantani G, Westover MB, Gliske S, Sarnthein J, Sarma S, Wang Y, Baud MO, Stacey WC, Conrad EC. Epilepsia, 2023 Dec; 64 Suppl 3 (Suppl 3): S25 - S36. DOI:10.1111/epi.17578
      PMID: 36897228
    • Journal Article
      Seizure forecasting: Where do we stand?
      Andrzejak RG, Zaveri HP, Schulze-Bonhage A, Leguia MG, Stacey WC, Richardson MP, Kuhlmann L, Lehnertz K. Epilepsia, 2023 Dec; 64 Suppl 3 (Suppl 3): S62 - S71. DOI:10.1111/epi.17546
      PMID: 36780237
    • Journal Article
      Optimization of ictal aborting stimulation using the dynamotype taxonomy.
      Szuromi MP, Jirsa VK, Stacey WC. J Comput Neurosci, 2023 Nov; 51 (4): 445 - 462. DOI:10.1007/s10827-023-00859-7
      PMID: 37667137
    • Journal Article
      Increasing challenges to trial recruitment and conduct over time.
      Kerr WT, Reddy AS, Seo SH, Kok N, Stacey WC, Stern JM, Pennell PB, French JA. Epilepsia, 2023 Oct; 64 (10): 2625 - 2634. DOI:10.1111/epi.17716
      PMID: 37440282
    • Journal Article
      Therapeutic Effect of Argatroban During Cardiopulmonary Resuscitation and Streptokinase During Extracorporeal Cardiopulmonary Resuscitation in a Porcine Model of Prolonged Cardiac Arrest.
      VanZalen JJ, Harvey S, Hála P, Phillips A, Nakashima T, Gok E, Tiba MH, McCracken BM, Hill JE, Liao J, Jung J, Mergos J, Stacey WC, Bartlett RH, Hsu CH, Rojas-Peña A, Neumar RW. Crit Care Explor, 2023 May; 5 (5): e0902 DOI:10.1097/CCE.0000000000000902
      PMID: 37181541
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