Show simple item record

dc.contributor.authorShrey, Daniel W.
dc.contributor.authorKim McManus, Olivia
dc.contributor.authorRajaraman, Rajsekar
dc.contributor.authorOmbao, Hernando
dc.contributor.authorHussain, Shaun A.
dc.contributor.authorLopour, Beth A.
dc.date.accessioned2018-12-31T13:29:28Z
dc.date.available2018-12-31T13:29:28Z
dc.date.issued2018-08-04
dc.identifier.citationShrey DW, Kim McManus O, Rajaraman R, Ombao H, Hussain SA, et al. (2018) Strength and stability of EEG functional connectivity predict treatment response in infants with epileptic spasms. Clinical Neurophysiology 129: 2137–2148. Available: http://dx.doi.org/10.1016/j.clinph.2018.07.017.
dc.identifier.issn1388-2457
dc.identifier.doi10.1016/j.clinph.2018.07.017
dc.identifier.urihttp://hdl.handle.net/10754/630510
dc.description.abstractEpileptic spasms (ES) are associated with pathological neuronal networks, which may underlie characteristic EEG patterns such as hypsarrhythmia. Here we evaluate EEG functional connectivity as a quantitative marker of treatment response, in comparison to classic visual EEG features.We retrospectively identified 21 ES patients and 21 healthy controls. EEG data recorded before treatment and after ≥10 days of treatment underwent blinded visual assessment, and functional connectivity was measured using cross-correlation techniques. Short-term treatment response and long-term outcome data were collected.Subjects with ES had stronger, more stable functional networks than controls. After treatment initiation, all responders (defined by cessation of spasms) exhibited decreases in functional connectivity strength, while an increase in connectivity strength occurred only in non-responders. There were six subjects with unusually strong pre-treatment functional connectivity, and all were responders. Visually assessed EEG features were not predictive of treatment response.Changes in network connectivity and stability correlate to treatment response for ES, and high pre-treatment connectivity may predict favorable short-term treatment response. Quantitative measures outperform visual analysis of the EEG.Functional networks may have value as objective markers of treatment response in ES, with potential to facilitate rapid identification of personalized, effective treatments.
dc.description.sponsorshipThe authors would like to thank Mary Zupanc, MD, for her mentorship and critical review of the manuscript, as well as Vaibhav Bajaj and Rachel Smith, who contributed preliminary data analysis. This work was supported by a Children’s Hospital of Orange Country (CHOC) PSF Tithe grant and an ICTS CHOC-UC Irvine Collaborative Pilot grant.
dc.publisherElsevier BV
dc.relation.urlhttps://www.sciencedirect.com/science/article/pii/S1388245718311787
dc.relation.urlhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC6193760
dc.rightsNOTICE: this is the author’s version of a work that was accepted for publication in [JournalTitle]. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in [JournalTitle], [[Volume], [Issue], (2018-08-04)] DOI: 10.1016/j.clinph.2018.07.017 . © 2018. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rightsThis file is an open access version redistributed from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6193760
dc.subjectBrain network
dc.subjectHypsarrhythmia
dc.subjectBASED score
dc.subjectWest syndrome
dc.subjectElectroencephalography
dc.subjectAdrenocorticotropic hormone (ACTH)
dc.subjectInfantile spasms
dc.titleStrength and stability of EEG functional connectivity predict treatment response in infants with epileptic spasms
dc.typeArticle
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentStatistics Program
dc.identifier.journalClinical Neurophysiology
dc.rights.embargodate2019-08-13
dc.eprint.versionPost-print
dc.contributor.institutionDepartment of Pediatrics, University of California, Irvine, CA, USA.
dc.contributor.institutionDivision of Neurology, Children's Hospital Orange County, Orange, CA, USA
dc.contributor.institutionDivision of Pediatric Neurology, University of California, San Diego, CA, USA.
dc.contributor.institutionDivision of Pediatric Neurology, University of California, Los Angeles, CA, USA.
dc.contributor.institutionDepartment of Statistics, University of California, Irvine, CA, USA
dc.contributor.institutionDepartment of Biomedical Engineering, University of California, Irvine, CA, USA.
kaust.personOmbao, Hernando
refterms.dateFOA2020-04-23T11:54:39Z
dc.date.published-online2018-08-04
dc.date.published-print2018-10


Files in this item

Thumbnail
Name:
Articlefile1.pdf
Size:
1.228Mb
Format:
PDF
Description:
Article

This item appears in the following Collection(s)

Show simple item record