Austin Health

Title
The ENIGMA-Epilepsy working group: Mapping disease from large data sets.
Publication Date
2020-05-29
Author(s)
Sisodiya, Sanjay M
Whelan, Christopher D
Hatton, Sean N
Huynh, Khoa
Altmann, Andre
Ryten, Mina
Vezzani, Annamaria
Caligiuri, Maria Eugenia
Labate, Angelo
Gambardella, Antonio
Ives-Deliperi, Victoria
Meletti, Stefano
Munsell, Brent C
Bonilha, Leonardo
Tondelli, Manuela
Rebsamen, Michael
Rummel, Christian
Vaudano, Anna Elisabetta
Wiest, Roland
Balachandra, Akshara R
Bargalló, Núria
Bartolini, Emanuele
Bernasconi, Andrea
Bernasconi, Neda
Bernhardt, Boris
Caldairou, Benoit
Carr, Sarah J A
Cavalleri, Gianpiero L
Cendes, Fernando
Concha, Luis
Desmond, Patricia M
Domin, Martin
Duncan, John S
Focke, Niels K
Guerrini, Renzo
Hamandi, Khalid
Jackson, Graeme D
Jahanshad, Neda
Kälviäinen, Reetta
Keller, Simon S
Kochunov, Peter
Kowalczyk, Magdalena A
Kreilkamp, Barbara A K
Kwan, Patrick
Lariviere, Sara
Lenge, Matteo
Lopez, Seymour M
Martin, Pascal
Mascalchi, Mario
Moreira, José C V
Morita-Sherman, Marcia E
Pardoe, Heath R
Pariente, Jose C
Raviteja, Kotikalapudi
Rocha, Cristiane S
Rodríguez-Cruces, Raúl
Seeck, Margitta
Semmelroch, Mira K H G
Sinclair, Benjamin
Soltanian-Zadeh, Hamid
Stein, Dan J
Striano, Pasquale
Taylor, Peter N
Thomas, Rhys H
Thomopoulos, Sophia I
Velakoulis, Dennis
Vivash, Lucy
Weber, Bernd
Yasuda, Clarissa Lin
Zhang, Junsong
Thompson, Paul M
McDonald, Carrie R
Subject
DTI
MRI
covariance
deep learning
event-based modeling
gene expression
genetics
imaging
quantitative
rsfMRI
Type of document
Journal Article
OrcId
0000-0002-9149-8726
0000-0002-9265-2393
0000-0002-2030-5552
0000-0002-8827-7324
0000-0001-7384-3074
0000-0003-0334-539X
0000-0002-8441-1485
0000-0003-2345-7938
0000-0002-6280-7526
0000-0001-6284-5402
0000-0002-5683-1941
0000-0001-9256-6041
0000-0001-9336-9568
0000-0001-5486-6289
0000-0001-7116-262X
0000-0002-7917-5326
0000-0001-5247-9795
0000-0002-5410-0299
0000-0001-6881-5191
0000-0003-2848-621X
0000-0002-8531-3916
0000-0003-4604-3367
0000-0002-2917-1212
0000-0002-7302-6856
0000-0002-6065-1476
0000-0002-0046-4070
DOI
10.1002/hbm.25037
Abstract
Epilepsy 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.
Link
Citation
Human brain mapping 2020; online first: 29 May
Jornal Title
Human brain mapping

Files:

NameSizeformatDescriptionLink