The ENIGMA-Epilepsy working group: Mapping disease from large data sets

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Sisodiya, Sanjay M, Whelan, Christopher D, Hatton, Sean N, Huynh, Khoa, Altmann, Andre, Ryten, Mina, Vezzani, Annamaria, Caligiuri, Maria Eugenia, Labate, Angelo, Gambardella, Antonio et al (show 62 more authors) , Ives-Deliperi, Victoria, Meletti, Stefano, Munsell, Brent C, Bonilha, Leonardo, Tondelli, Manuela, Rebsamen, Michael, Rummel, Christian, Vaudano, Anna Elisabetta, Wiest, Roland, Balachandra, Akshara R, Bargallo, Nuria, Bartolini, Emanuele, Bernasconi, Andrea, Bernasconi, Neda, Bernhardt, Boris, Caldairou, Benoit, Carr, Sarah JA, 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, Kalviainen, Reetta, Keller, Simon S ORCID: 0000-0001-5247-9795, Kochunov, Peter, Kowalczyk, Magdalena A, Kreilkamp, Barbara AK, Kwan, Patrick, Lariviere, Sara, Lenge, Matteo, Lopez, Seymour M, Martin, Pascal, Mascalchi, Mario, Moreira, Jose CV, Morita-Sherman, Marcia E, Pardoe, Heath R, Pariente, Jose C, Raviteja, Kotikalapudi, Rocha, Cristiane S, Rodriguez-Cruces, Raul, Seeck, Margitta, Semmelroch, Mira KHG, 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 and McDonald, Carrie R (2022) The ENIGMA-Epilepsy working group: Mapping disease from large data sets HUMAN BRAIN MAPPING, 43 (1). pp. 113-128. ISSN 1065-9471, 1097-0193

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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.

Item Type:	Article
Uncontrolled Keywords:	covariance, deep learning, DTI, event-based modeling, gene expression, genetics, imaging, MRI, quantitative, rsfMRI
Depositing User:	Symplectic Admin
Date Deposited:	16 Jul 2020 07:22
Last Modified:	16 Jun 2026 15:12
DOI:	10.1002/hbm.25037
Related Websites:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3094139
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