Human interictal epileptiform discharges are bidirectional traveling waves echoing ictal discharges

  1. Elliot H Smith  Is a corresponding author
  2. Jyun-you Liou
  3. Edward M Merricks
  4. Tyler Davis
  5. Kyle Thomson
  6. Bradley Greger
  7. Paul House
  8. Ronald G Emerson
  9. Robert Goodman
  10. Guy M McKhann
  11. Sameer Sheth
  12. Catherine Schevon
  13. John D Rolston  Is a corresponding author
  1. University of Utah, United States
  2. Weill Cornell Medicine, United States
  3. Columbia University Medical Center, United States
  4. Arizona State University, United States
  5. Neurosurgical Associates, LLC, United States
  6. Hospital for Special Surgery, United States
  7. Lenox Hill Hospital, United States
  8. Baylor College of Medicine, United States
  9. Columbia University, United States

Abstract

Interictal epileptiform discharges (IEDs), also known as interictal spikes, are large intermittent electrophysiological events observed between seizures in patients with epilepsy. Though they occur far more often than seizures, IEDs are less studied, and their relationship to seizures remains unclear. To better understand this relationship, we examined multi-day recordings of microelectrode arrays implanted in human epilepsy patients, allowing us to precisely observe the spatiotemporal propagation of IEDs, spontaneous seizures, and how they relate. These recordings showed that the majority of IEDs are traveling waves, traversing the same path as ictal discharges during seizures, and with a fixed direction relative to seizure propagation. Moreover, the majority of IEDs, like ictal discharges, were bidirectional, with one predominant and a second, less frequent antipodal direction. These results reveal a fundamental spatiotemporal similarity between IEDs and ictal discharges. These results also imply that most IEDs arise in brain tissue outside the site of seizure onset and propagate toward it, indicating that the propagation of IEDs provides useful information for localizing the seizure focus.

Data availability

Raw data is available upon establishment of a data use agreement with Columbia University Medical Center as required by their Institutional Review Board (IRB). Data from human subjects was analyzed, from which the dates of implants can potentially be reconstructed. This is especially true for a study like this one, in which chronic recordings were carried out for the full duration of the patients' hospital stays. Sharing these data widely could therefore expose private health information of participants, which is why a data use agreement is required by the IRB. Interested Researchers should contact Dr. Schevon to get the data use agreement process started with the Columbia University Medical Center IRB.Analysis code is upload to GitHub: https://github.com/elliothsmith/IEDs. We have included preprocessed data files for all IEDs, hosted online at OSF: https://osf.io/zhk24/. Data files include LFP, MUA event times, and traveling wave model coefficients for all detected IEDs.

The following data sets were generated

Article and author information

Author details

  1. Elliot H Smith

    Department of Neurolosurgery, University of Utah, Salt Lake City, United States
    For correspondence
    e.h.smith@utah.edu
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4323-4643
  2. Jyun-you Liou

    Department of Anesthesiology, Weill Cornell Medicine, New York, United States
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4851-3676
  3. Edward M Merricks

    Department of Neurology, Columbia University Medical Center, New York CIty, United States
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-8172-3152
  4. Tyler Davis

    Department of Neurosurgery, University of Utah, Salt Lake City, United States
    Competing interests
    No competing interests declared.
  5. Kyle Thomson

    Departments of Neurosurgery, University of Utah, Salt Lake City, United States
    Competing interests
    No competing interests declared.
  6. Bradley Greger

    Department of Bioengineering, Arizona State University, Tempe, United States
    Competing interests
    No competing interests declared.
  7. Paul House

    Neurosurgical Associates, LLC, Murray, United States
    Competing interests
    Paul House, is affiliated with Neurosurgical Associates, LLC. The author has no financial interests to declare..
  8. Ronald G Emerson

    Hospital for Special Surgery, New York, United States
    Competing interests
    No competing interests declared.
  9. Robert Goodman

    Lenox Hill Hospital, New York, United States
    Competing interests
    No competing interests declared.
  10. Guy M McKhann

    Department of Neurological Surgery, Columbia University Medical Center, New York, United States
    Competing interests
    Guy M McKhann, reports fees from Koh Young, Inc.
  11. Sameer Sheth

    Department of Neurological Surgery, Baylor College of Medicine, Houston, United States
    Competing interests
    Sameer Sheth, consulting for Boston Scientific, Abbott, Neuropace, Zimmer Biomet..
  12. Catherine Schevon

    Department of Neurology, Columbia University, New York, United States
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-4485-7933
  13. John D Rolston

    Departments of Neurosurgery, University of Utah, Salt Lake City, United States
    For correspondence
    john.rolston@utah.edu
    Competing interests
    John D Rolston, reports fees from Medtronic, Inc..
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-8843-5468

Funding

National Institutes of Health (NINDS R21 NS113031)

  • Elliot H Smith
  • Catherine Schevon
  • John D Rolston

National Institutes of Health (NINDS K23 NS114178)

  • John D Rolston

National Institutes of Health (S10 OD018211)

  • Catherine Schevon

National Institutes of Health (R01 NS084142)

  • Catherine Schevon

American Epilepsy Society (JIA)

  • Elliot H Smith

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. Matthew Shtrahman, University of California, San Diego, United States

Ethics

Human subjects: The Institutional Review Boards at the University of Utah (IRB_00114691) and Columbia University Medical Center (IRB- AAAB6324) approved these studies. All participants provided informed consent prior to surgery for implantation of the clinical and research electrodes.

Version history

  1. Preprint posted: April 29, 2021 (view preprint)
  2. Received: September 2, 2021
  3. Accepted: January 19, 2022
  4. Accepted Manuscript published: January 20, 2022 (version 1)
  5. Accepted Manuscript updated: January 24, 2022 (version 2)
  6. Version of Record published: February 3, 2022 (version 3)

Copyright

© 2022, Smith et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 5,243
    views
  • 474
    downloads
  • 22
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Elliot H Smith
  2. Jyun-you Liou
  3. Edward M Merricks
  4. Tyler Davis
  5. Kyle Thomson
  6. Bradley Greger
  7. Paul House
  8. Ronald G Emerson
  9. Robert Goodman
  10. Guy M McKhann
  11. Sameer Sheth
  12. Catherine Schevon
  13. John D Rolston
(2022)
Human interictal epileptiform discharges are bidirectional traveling waves echoing ictal discharges
eLife 11:e73541.
https://doi.org/10.7554/eLife.73541

Share this article

https://doi.org/10.7554/eLife.73541

Further reading

    1. Computational and Systems Biology
    Qianmu Yuan, Chong Tian, Yuedong Yang
    Tools and Resources

    Revealing protein binding sites with other molecules, such as nucleic acids, peptides, or small ligands, sheds light on disease mechanism elucidation and novel drug design. With the explosive growth of proteins in sequence databases, how to accurately and efficiently identify these binding sites from sequences becomes essential. However, current methods mostly rely on expensive multiple sequence alignments or experimental protein structures, limiting their genome-scale applications. Besides, these methods haven’t fully explored the geometry of the protein structures. Here, we propose GPSite, a multi-task network for simultaneously predicting binding residues of DNA, RNA, peptide, protein, ATP, HEM, and metal ions on proteins. GPSite was trained on informative sequence embeddings and predicted structures from protein language models, while comprehensively extracting residual and relational geometric contexts in an end-to-end manner. Experiments demonstrate that GPSite substantially surpasses state-of-the-art sequence-based and structure-based approaches on various benchmark datasets, even when the structures are not well-predicted. The low computational cost of GPSite enables rapid genome-scale binding residue annotations for over 568,000 sequences, providing opportunities to unveil unexplored associations of binding sites with molecular functions, biological processes, and genetic variants. The GPSite webserver and annotation database can be freely accessed at https://bio-web1.nscc-gz.cn/app/GPSite.

    1. Cell Biology
    2. Computational and Systems Biology
    Thomas Grandits, Christoph M Augustin ... Alexander Jung
    Research Article

    Computer models of the human ventricular cardiomyocyte action potential (AP) have reached a level of detail and maturity that has led to an increasing number of applications in the pharmaceutical sector. However, interfacing the models with experimental data can become a significant computational burden. To mitigate the computational burden, the present study introduces a neural network (NN) that emulates the AP for given maximum conductances of selected ion channels, pumps, and exchangers. Its applicability in pharmacological studies was tested on synthetic and experimental data. The NN emulator potentially enables massive speed-ups compared to regular simulations and the forward problem (find drugged AP for pharmacological parameters defined as scaling factors of control maximum conductances) on synthetic data could be solved with average root-mean-square errors (RMSE) of 0.47 mV in normal APs and of 14.5 mV in abnormal APs exhibiting early afterdepolarizations (72.5% of the emulated APs were alining with the abnormality, and the substantial majority of the remaining APs demonstrated pronounced proximity). This demonstrates not only very fast and mostly very accurate AP emulations but also the capability of accounting for discontinuities, a major advantage over existing emulation strategies. Furthermore, the inverse problem (find pharmacological parameters for control and drugged APs through optimization) on synthetic data could be solved with high accuracy shown by a maximum RMSE of 0.22 in the estimated pharmacological parameters. However, notable mismatches were observed between pharmacological parameters estimated from experimental data and distributions obtained from the Comprehensive in vitro Proarrhythmia Assay initiative. This reveals larger inaccuracies which can be attributed particularly to the fact that small tissue preparations were studied while the emulator was trained on single cardiomyocyte data. Overall, our study highlights the potential of NN emulators as powerful tool for an increased efficiency in future quantitative systems pharmacology studies.