Self-supervised data-driven approach defines pathological high-frequency oscillations in epilepsy.

Journal: Epilepsia
Published Date:

Abstract

OBJECTIVE: Interictal high-frequency oscillations (HFOs) are a promising neurophysiological biomarker of the epileptogenic zone (EZ). However, objective criteria for distinguishing pathological from physiological HFOs remain elusive, hindering clinical application. We investigated whether the distinct mechanisms underlying pathological and physiological HFOs are encapsulated in their signal morphology in intracranial electroencephalographic (iEEG) recordings and whether this distinction could be captured by a deep generative model.

Authors

  • Yipeng Zhang
    Department of Electrical and Computer Engineering, University of California, Los Angeles, CA, United States of America.
  • Atsuro Daida
    Division of Pediatric Neurology, Department of Pediatrics, UCLA Mattel Children's Hospital, David Geffen School of Medicine, Los Angeles, CA, USA.
  • Lawrence Liu
    California Protons Cancer Therapy Center, San Diego, California, USA.
  • Naoto Kuroda
  • Yuanyi Ding
    Department of Electrical and Computer Engineering, University of California, Los Angeles, CA, United States of America.
  • Shingo Oana
    Division of Pediatric Neurology, Department of Pediatrics, UCLA Mattel Children's Hospital, David Geffen School of Medicine, Los Angeles, CA, USA.
  • Sotaro Kanai
    Division of Pediatric Neurology, Department of Pediatrics, UCLA Mattel Children's Hospital, David Geffen School of Medicine at UCLA, Los Angeles, California, USA.
  • Tonmoy Monsoor
    Department of Electrical and Computer Engineering, University of California, Los Angeles, CA, United States of America.
  • Chenda Duan
    Department of Electrical and Computer Engineering, University of California, Los Angeles (UCLA), Los Angeles, California, USA.
  • Shaun A Hussain
    Division of Pediatric Neurology, Department of Pediatrics, UCLA Mattel Children's Hospital, David Geffen School of Medicine, Los Angeles, CA, United States of America.
  • Joe X Qiao
    Department of Radiological Sciences, David Geffen School of Medicine at University of California Los Angeles, Los Angeles, CA, USA.
  • Noriko Salamon
    Department of Radiology, University of California, Los Angeles, Los Angeles, CA, USA.
  • Aria Fallah
    Department of Neurosurgery, UCLA Medical Center, David Geffen School of Medicine, Los Angeles, CA, United States of America.
  • Myung Shin Sim
    Department of Medicine, Statistics Core, University of California, Los Angeles, CA, United States of America.
  • Raman Sankar
    Division of Pediatric Neurology, Department of Pediatrics, UCLA Mattel Children's Hospital, David Geffen School of Medicine, Los Angeles, CA, United States of America.
  • Richard J Staba
    Department of Neurology, David Geffen School of Medicine and at UCLA, Los Angeles, CA 90095, United States.
  • Jerome Engel
    Department of Neurology, David Geffen School of Medicine and at UCLA, Los Angeles, CA 90095, United States; Department of Neurosurgery, David Geffen School of Medicine and at UCLA, Los Angeles, CA 90095, United States; Department of Neurobiology, David Geffen School of Medicine and at UCLA, Los Angeles, CA 90095, United States; Department of Psychiatry & Biobehavioral Sciences, David Geffen School of Medicine and at UCLA, Los Angeles, CA 90095, United States.
  • Eishi Asano
  • Vwani Roychowdhury
    Department of Electrical and Computer Engineering, University of California, Los Angeles, CA 90095; kailath@stanford.edu vwani@ucla.edu.
  • Hiroki Nariai
    Division of Pediatric Neurology, Department of Pediatrics, UCLA Mattel Children's Hospital, David Geffen School of Medicine, Los Angeles, CA, United States of America.

Keywords

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