Emerging roles of network analysis for epilepsy

William Stacey; Mark Kramer; Kristin Gunnarsdottir; Jorge Gonzalez-Martinez; Kareem Zaghloul; Sara Inati; Sridevi Sarma; Jennifer Stiso; Ankit N Khambhati; Danielle S Bassett; Rachel J Smith; Virginia B Liu; Beth A Lopour; Richard Staba

doi:10.1016/j.eplepsyres.2019.106255

Emerging roles of network analysis for epilepsy

Epilepsy Res. 2020 Jan:159:106255. doi: 10.1016/j.eplepsyres.2019.106255. Epub 2019 Dec 9.

Authors

Affiliations

¹ Department of Neurology, Department of Biomedical Engineering, University of Michigan, United States. Electronic address: William.stacey@umich.edu.
² Department of Mathematics and Statistics, Center of Systems Neuroscience, Boston University, United States.
³ Department of Biomedical Engineering, Johns Hopkins University, United States.
⁴ Department of Neurological Surgery, University of Pittsburgh, United States.
⁵ Surgical Neurology Branch, National Institute of Neurological Disorders and Stroke, NIH, United States.
⁶ Office of the Clinical Director, National Institute of Neurological Disorders and Stroke, NIH, United States.
⁷ Department of Neurology, Department of Biomedical Engineering, University of Michigan, United States.
⁸ Department of Bioengineering, University of Pennsylvania, United States.
⁹ Department of Biomedical Engineering, University of California, Irvine, United States.
¹⁰ Department of Pediatrics, University of California, Irvine, United States; Department of Child Neurology, Children's Hospital of Orange County, CA, United States.
¹¹ Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States.

Abstract

In recent years there has been increasing interest in applying network science tools to EEG data. At the 2018 American Epilepsy Society conference in New Orleans, LA, the yearly session of the Engineering and Neurostimulation Special Interest Group focused on emerging, translational technologies to analyze seizure networks. Each speaker demonstrated practical examples of how network tools can be utilized in clinical care and provide additional data to help care for patients with intractable epilepsy. The groups presented advances using tools from functional connectivity, control theory, and graph theory to analyze human EEG data. These tools have great potential to augment clinical interpretation of EEG signals.

Keywords: Control theory; EEG; Functional connectivity; Graph theory; Infantile spasms; Network analysis.

Publication types

Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.
Review

MeSH terms

Brain / physiopathology*
Brain Mapping
Electroencephalography
Epilepsy / physiopathology*
Humans
Nerve Net / physiopathology*

Abstract

Publication types

MeSH terms

Grants and funding