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dc.contributor.authorSisodiya, S.M.
dc.contributor.authorWhelan, C.D.
dc.contributor.authorKochunov, P.
dc.date.accessioned2020-06-08T20:21:02Z
dc.date.available2020-06-08T20:21:02Z
dc.date.issued2020
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85085547126&doi=10.1002%2fhbm.25037&partnerID=40&md5=79a92ab8a5986ac2f8a1eacc030cf7c4
dc.identifier.urihttp://hdl.handle.net/10713/13001
dc.description.abstractEpilepsy is a common and serious neurological disorder, with many different constituent conditions characterized by their electro clinical, imaging, and genetic features. MRI has been fundamental in advancing our understanding of brain processes in the epilepsies. Smaller-scale studies have identified many interesting imaging phenomena, with implications both for understanding pathophysiology and improving clinical care. Through the infrastructure and concepts now well-established by the ENIGMA Consortium, ENIGMA-Epilepsy was established to strengthen epilepsy neuroscience by greatly increasing sample sizes, leveraging ideas and methods established in other ENIGMA projects, and generating a body of collaborating scientists and clinicians to drive forward robust research. Here we review published, current, and future projects, that include structural MRI, diffusion tensor imaging (DTI), and resting state functional MRI (rsfMRI), and that employ advanced methods including structural covariance, and event-based modeling analysis. We explore age of onset- and duration-related features, as well as phenomena-specific work focusing on particular epilepsy syndromes or phenotypes, multimodal analyses focused on understanding the biology of disease progression, and deep learning approaches. We encourage groups who may be interested in participating to make contact to further grow and develop ENIGMA-Epilepsy. Copyright 2020 The Authors.en_US
dc.description.urihttp://doi.org/10.1002/hbm.25037en_US
dc.language.isoen_USen_US
dc.publisherJohn Wiley and Sons Inc.en_US
dc.relation.ispartofHuman Brain Mapping
dc.subjectcovarianceen_US
dc.subjectdeep learningen_US
dc.subjectDTIen_US
dc.subjectevent-based modelingen_US
dc.subjectgene expressionen_US
dc.subjectgeneticsen_US
dc.subjectimagingen_US
dc.subjectMRIen_US
dc.subjectquantitativeen_US
dc.subjectrsfMRIen_US
dc.titleThe ENIGMA-Epilepsy working group: Mapping disease from large data setsen_US
dc.typeArticleen_US
dc.identifier.doi10.1002/hbm.25037


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