The ENIGMA Stroke Recovery Working Group: Big data neuroimaging to study brain–behavior relationships after stroke: Big data neuroimaging to study brain–behavior relationships after stroke

Sook‐Lei Liew; Artemis Zavaliangos‐Petropulu; Neda Jahanshad; Catherine E. Lang; Kathryn S. Hayward; Keith R. Lohse; Julia M. Juliano; Francesca Assogna; Lee A. Baugh; Anup K. Bhattacharya; Bavrina Bigjahan; Michael R. Borich; Lara A. Boyd; Amy Brodtmann; Cathrin M. Buetefisch; Winston D. Byblow; Jessica M. Cassidy; Adriana B. Conforto; R. Cameron Craddock; Michael A. Dimyan; Adrienne N. Dula; Elsa Ermer; Mark R. Etherton; Kelene A. Fercho; Chris M. Gregory; Shahram Hadidchi; Jess A. Holguin; Darryl H. Hwang; Simon Jung; Steven A. Kautz; Mohamed Salah Khlif; Nima Khoshab; Bokkyu Kim; Hosung Kim; Amy Kuceyeski; Martin Lotze; Bradley J. MacIntosh; John L. Margetis; Feroze B. Mohamed; Fabrizio Piras; Ander Ramos‐Murguialday; Geneviève Richard; Pamela Roberts; Andrew D. Robertson; Jane M. Rondina; Natalia S. Rost; Nerses Sanossian; Nicolas Schweighofer; Na Jin Seo; Mark S. Shiroishi; Surjo R. Soekadar; Gianfranco Spalletta; Cathy M. Stinear; Anisha Suri; Wai Kwong W. Tang; Gregory T. Thielman; Daniela Vecchio; Arno Villringer; Nick S. Ward; Emilio Werden; Lars T. Westlye; Carolee Winstein; George F. Wittenberg; Kristin A. Wong; Chunshui Yu; Steven C. Cramer; Paul M. Thompson; Artemis Zavaliangos-Petropulu; Ander Ramos-Murguialday

doi:10.1002/hbm.25015

The ENIGMA Stroke Recovery Working Group: Big data neuroimaging to study brain–behavior relationships after stroke: Big data neuroimaging to study brain–behavior relationships after stroke

Sook‐Lei Liew
, Artemis Zavaliangos‐Petropulu
, Neda Jahanshad
, Catherine E. Lang
, Kathryn S. Hayward
, Keith R. Lohse
, Julia M. Juliano
, Francesca Assogna
, Lee A. Baugh
, Anup K. Bhattacharya
, Bavrina Bigjahan
, Michael R. Borich
, Lara A. Boyd
, Amy Brodtmann
, Cathrin M. Buetefisch
, Winston D. Byblow
, Jessica M. Cassidy
, Adriana B. Conforto
, R. Cameron Craddock
, Michael A. Dimyan

Adrienne N. Dula, Elsa Ermer, Mark R. Etherton, Kelene A. Fercho, Chris M. Gregory, Shahram Hadidchi, Jess A. Holguin, Darryl H. Hwang, Simon Jung, Steven A. Kautz, Mohamed Salah Khlif, Nima Khoshab, Bokkyu Kim, Hosung Kim, Amy Kuceyeski, Martin Lotze, Bradley J. MacIntosh, John L. Margetis, Feroze B. Mohamed, Fabrizio Piras, Ander Ramos‐Murguialday, Geneviève Richard, Pamela Roberts, Andrew D. Robertson, Jane M. Rondina, Natalia S. Rost, Nerses Sanossian, Nicolas Schweighofer, Na Jin Seo, Mark S. Shiroishi, Surjo R. Soekadar, Gianfranco Spalletta, Cathy M. Stinear, Anisha Suri, Wai Kwong W. Tang, Gregory T. Thielman, Daniela Vecchio, Arno Villringer, Nick S. Ward, Emilio Werden, Lars T. Westlye, Carolee Winstein, George F. Wittenberg, Kristin A. Wong, Chunshui Yu, Steven C. Cramer, Paul M. Thompson, Artemis Zavaliangos-Petropulu, Ander Ramos-Murguialday

Neuroengineering

University of Southern California
Washington University St. Louis
University of Melbourne
University of Utah
IRCCS Fondazione Santa Lucia - Roma
University of South Dakota
Sioux Falls VA Health Care System
Emory University
University of British Columbia
The University of Auckland
University of North Carolina at Chapel Hill
Universidade de São Paulo
Hospital Israelita Albert Einstein
University of Texas at Austin
University of Maryland, Baltimore
VA Medical Center
Massachusetts General Hospital
Harvard University
Federal Aviation Administration
Medical University of South Carolina
Wayne State University
University of Bern
Department of Veterans Affairs
University of California at Irvine
SUNY Upstate Medical University
Cornell University
University of Greifswald
University of Toronto
Sunnybrook Health Sciences Centre
Thomas Jefferson University
University of Tübingen
University of Oslo
Cedars-Sinai Medical Center
University of Waterloo
University College London
Charité Universitätsmedizin Berlin
Baylor College of Medicine
University of Pittsburgh
Chinese University of Hong Kong
University of Sciences in Philadelphia
Samson College
Max Planck Institute for Human Cognitive and Brain Sciences
Leipzig University
Tianjin Medical University
University of California, Los Angeles

Research output: Contribution to journal › Article › peer-review

67 Citations (Scopus)

6 Downloads (Pure)

Abstract

The goal of the Enhancing Neuroimaging Genetics through Meta‐Analysis (ENIGMA) Stroke Recovery working group is to understand brain and behavior relationships using well‐powered meta‐ and mega‐analytic approaches. ENIGMA Stroke Recovery has data from over 2,100 stroke patients collected across 39 research studies and 10 countries around the world, comprising the largest multisite retrospective stroke data collaboration to date. This article outlines the efforts taken by the ENIGMA Stroke Recovery working group to develop neuroinformatics protocols and methods to manage multisite stroke brain magnetic resonance imaging, behavioral and demographics data. Specifically, the processes for scalable data intake and preprocessing, multisite data harmonization, and large‐scale stroke lesion analysis are described, and challenges unique to this type of big data collaboration in stroke research are discussed. Finally, future directions and limitations, as well as recommendations for improved data harmonization through prospective data collection and data management, are provided.

Original language	English
Pages (from-to)	129-148
Number of pages	20
Journal	Human Brain Mapping
Volume	unknown
Issue number	1
DOIs	https://doi.org/10.1002/hbm.25015
Publication status	Published - 2020

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

Big data
Lesions
MRI
Neuroinformatics
Stroke

Access to Document

10.1002/hbm.25015

HbmFinal published version, 2.32 MB

Cite this

Liew, SL., Zavaliangos‐Petropulu, A., Jahanshad, N., Lang, C. E., Hayward, K. S., Lohse, K. R., Juliano, J. M., Assogna, F., Baugh, L. A., Bhattacharya, A. K., Bigjahan, B., Borich, M. R., Boyd, L. A., Brodtmann, A., Buetefisch, C. M., Byblow, W. D., Cassidy, J. M., Conforto, A. B., Craddock, R. C., ... Ramos-Murguialday, A. (2020). The ENIGMA Stroke Recovery Working Group: Big data neuroimaging to study brain–behavior relationships after stroke: Big data neuroimaging to study brain–behavior relationships after stroke. Human Brain Mapping, unknown(1), 129-148. https://doi.org/10.1002/hbm.25015

@article{181757ad7d304467b9ff237820a1592c,

title = "The ENIGMA Stroke Recovery Working Group: Big data neuroimaging to study brain–behavior relationships after stroke: Big data neuroimaging to study brain–behavior relationships after stroke",

abstract = "The goal of the Enhancing Neuroimaging Genetics through Meta‐Analysis (ENIGMA) Stroke Recovery working group is to understand brain and behavior relationships using well‐powered meta‐ and mega‐analytic approaches. ENIGMA Stroke Recovery has data from over 2,100 stroke patients collected across 39 research studies and 10 countries around the world, comprising the largest multisite retrospective stroke data collaboration to date. This article outlines the efforts taken by the ENIGMA Stroke Recovery working group to develop neuroinformatics protocols and methods to manage multisite stroke brain magnetic resonance imaging, behavioral and demographics data. Specifically, the processes for scalable data intake and preprocessing, multisite data harmonization, and large‐scale stroke lesion analysis are described, and challenges unique to this type of big data collaboration in stroke research are discussed. Finally, future directions and limitations, as well as recommendations for improved data harmonization through prospective data collection and data management, are provided.",

keywords = "Big data, Lesions, MRI, Neuroinformatics, Stroke, Big data, Lesions, MRI, Neuroinformatics, Stroke",

author = "Sook‐Lei Liew and Artemis Zavaliangos‐Petropulu and Neda Jahanshad and Lang, \{Catherine E.\} and Hayward, \{Kathryn S.\} and Lohse, \{Keith R.\} and Juliano, \{Julia M.\} and Francesca Assogna and Baugh, \{Lee A.\} and Bhattacharya, \{Anup K.\} and Bavrina Bigjahan and Borich, \{Michael R.\} and Boyd, \{Lara A.\} and Amy Brodtmann and Buetefisch, \{Cathrin M.\} and Byblow, \{Winston D.\} and Cassidy, \{Jessica M.\} and Conforto, \{Adriana B.\} and Craddock, \{R. Cameron\} and Dimyan, \{Michael A.\} and Dula, \{Adrienne N.\} and Elsa Ermer and Etherton, \{Mark R.\} and Fercho, \{Kelene A.\} and Gregory, \{Chris M.\} and Shahram Hadidchi and Holguin, \{Jess A.\} and Hwang, \{Darryl H.\} and Simon Jung and Kautz, \{Steven A.\} and Khlif, \{Mohamed Salah\} and Nima Khoshab and Bokkyu Kim and Hosung Kim and Amy Kuceyeski and Martin Lotze and MacIntosh, \{Bradley J.\} and Margetis, \{John L.\} and Mohamed, \{Feroze B.\} and Fabrizio Piras and Ander Ramos‐Murguialday and Genevi{\`e}ve Richard and Pamela Roberts and Robertson, \{Andrew D.\} and Rondina, \{Jane M.\} and Rost, \{Natalia S.\} and Nerses Sanossian and Nicolas Schweighofer and Seo, \{Na Jin\} and Shiroishi, \{Mark S.\} and Soekadar, \{Surjo R.\} and Gianfranco Spalletta and Stinear, \{Cathy M.\} and Anisha Suri and Tang, \{Wai Kwong W.\} and Thielman, \{Gregory T.\} and Daniela Vecchio and Arno Villringer and Ward, \{Nick S.\} and Emilio Werden and Westlye, \{Lars T.\} and Carolee Winstein and Wittenberg, \{George F.\} and Wong, \{Kristin A.\} and Chunshui Yu and Cramer, \{Steven C.\} and Thompson, \{Paul M.\} and Artemis Zavaliangos-Petropulu and Ander Ramos-Murguialday",

note = "Publisher Copyright: {\textcopyright} 2020 The Authors. Human Brain Mapping published by Wiley Periodicals, Inc.",

year = "2020",

doi = "10.1002/hbm.25015",

language = "English",

volume = "unknown",

pages = "129--148",

journal = "Human Brain Mapping",

issn = "1065-9471",

publisher = "Wiley-Liss Inc.",

number = "1",

}

Liew, SL, Zavaliangos‐Petropulu, A, Jahanshad, N, Lang, CE, Hayward, KS, Lohse, KR, Juliano, JM, Assogna, F, Baugh, LA, Bhattacharya, AK, Bigjahan, B, Borich, MR, Boyd, LA, Brodtmann, A, Buetefisch, CM, Byblow, WD, Cassidy, JM, Conforto, AB, Craddock, RC, Dimyan, MA, Dula, AN, Ermer, E, Etherton, MR, Fercho, KA, Gregory, CM, Hadidchi, S, Holguin, JA, Hwang, DH, Jung, S, Kautz, SA, Khlif, MS, Khoshab, N, Kim, B, Kim, H, Kuceyeski, A, Lotze, M, MacIntosh, BJ, Margetis, JL, Mohamed, FB, Piras, F, Ramos‐Murguialday, A, Richard, G, Roberts, P, Robertson, AD, Rondina, JM, Rost, NS, Sanossian, N, Schweighofer, N, Seo, NJ, Shiroishi, MS, Soekadar, SR, Spalletta, G, Stinear, CM, Suri, A, Tang, WKW, Thielman, GT, Vecchio, D, Villringer, A, Ward, NS, Werden, E, Westlye, LT, Winstein, C, Wittenberg, GF, Wong, KA, Yu, C, Cramer, SC, Thompson, PM, Zavaliangos-Petropulu, A & Ramos-Murguialday, A 2020, 'The ENIGMA Stroke Recovery Working Group: Big data neuroimaging to study brain–behavior relationships after stroke: Big data neuroimaging to study brain–behavior relationships after stroke', Human Brain Mapping, vol. unknown, no. 1, pp. 129-148. https://doi.org/10.1002/hbm.25015

The ENIGMA Stroke Recovery Working Group: Big data neuroimaging to study brain–behavior relationships after stroke: Big data neuroimaging to study brain–behavior relationships after stroke. / Liew, Sook‐Lei; Zavaliangos‐Petropulu, Artemis; Jahanshad, Neda et al.
In: Human Brain Mapping, Vol. unknown, No. 1, 2020, p. 129-148.

Research output: Contribution to journal › Article › peer-review

TY - JOUR

T1 - The ENIGMA Stroke Recovery Working Group: Big data neuroimaging to study brain–behavior relationships after stroke

T2 - Big data neuroimaging to study brain–behavior relationships after stroke

AU - Liew, Sook‐Lei

AU - Zavaliangos‐Petropulu, Artemis

AU - Jahanshad, Neda

AU - Lang, Catherine E.

AU - Hayward, Kathryn S.

AU - Lohse, Keith R.

AU - Juliano, Julia M.

AU - Assogna, Francesca

AU - Baugh, Lee A.

AU - Bhattacharya, Anup K.

AU - Bigjahan, Bavrina

AU - Borich, Michael R.

AU - Boyd, Lara A.

AU - Brodtmann, Amy

AU - Buetefisch, Cathrin M.

AU - Byblow, Winston D.

AU - Cassidy, Jessica M.

AU - Conforto, Adriana B.

AU - Craddock, R. Cameron

AU - Dimyan, Michael A.

AU - Dula, Adrienne N.

AU - Ermer, Elsa

AU - Etherton, Mark R.

AU - Fercho, Kelene A.

AU - Gregory, Chris M.

AU - Hadidchi, Shahram

AU - Holguin, Jess A.

AU - Hwang, Darryl H.

AU - Jung, Simon

AU - Kautz, Steven A.

AU - Khlif, Mohamed Salah

AU - Khoshab, Nima

AU - Kim, Bokkyu

AU - Kim, Hosung

AU - Kuceyeski, Amy

AU - Lotze, Martin

AU - MacIntosh, Bradley J.

AU - Margetis, John L.

AU - Mohamed, Feroze B.

AU - Piras, Fabrizio

AU - Ramos‐Murguialday, Ander

AU - Richard, Geneviève

AU - Roberts, Pamela

AU - Robertson, Andrew D.

AU - Rondina, Jane M.

AU - Rost, Natalia S.

AU - Sanossian, Nerses

AU - Schweighofer, Nicolas

AU - Seo, Na Jin

AU - Shiroishi, Mark S.

AU - Soekadar, Surjo R.

AU - Spalletta, Gianfranco

AU - Stinear, Cathy M.

AU - Suri, Anisha

AU - Tang, Wai Kwong W.

AU - Thielman, Gregory T.

AU - Vecchio, Daniela

AU - Villringer, Arno

AU - Ward, Nick S.

AU - Werden, Emilio

AU - Westlye, Lars T.

AU - Winstein, Carolee

AU - Wittenberg, George F.

AU - Wong, Kristin A.

AU - Yu, Chunshui

AU - Cramer, Steven C.

AU - Thompson, Paul M.

AU - Zavaliangos-Petropulu, Artemis

AU - Ramos-Murguialday, Ander

PY - 2020

Y1 - 2020

N2 - The goal of the Enhancing Neuroimaging Genetics through Meta‐Analysis (ENIGMA) Stroke Recovery working group is to understand brain and behavior relationships using well‐powered meta‐ and mega‐analytic approaches. ENIGMA Stroke Recovery has data from over 2,100 stroke patients collected across 39 research studies and 10 countries around the world, comprising the largest multisite retrospective stroke data collaboration to date. This article outlines the efforts taken by the ENIGMA Stroke Recovery working group to develop neuroinformatics protocols and methods to manage multisite stroke brain magnetic resonance imaging, behavioral and demographics data. Specifically, the processes for scalable data intake and preprocessing, multisite data harmonization, and large‐scale stroke lesion analysis are described, and challenges unique to this type of big data collaboration in stroke research are discussed. Finally, future directions and limitations, as well as recommendations for improved data harmonization through prospective data collection and data management, are provided.

AB - The goal of the Enhancing Neuroimaging Genetics through Meta‐Analysis (ENIGMA) Stroke Recovery working group is to understand brain and behavior relationships using well‐powered meta‐ and mega‐analytic approaches. ENIGMA Stroke Recovery has data from over 2,100 stroke patients collected across 39 research studies and 10 countries around the world, comprising the largest multisite retrospective stroke data collaboration to date. This article outlines the efforts taken by the ENIGMA Stroke Recovery working group to develop neuroinformatics protocols and methods to manage multisite stroke brain magnetic resonance imaging, behavioral and demographics data. Specifically, the processes for scalable data intake and preprocessing, multisite data harmonization, and large‐scale stroke lesion analysis are described, and challenges unique to this type of big data collaboration in stroke research are discussed. Finally, future directions and limitations, as well as recommendations for improved data harmonization through prospective data collection and data management, are provided.

KW - Big data

KW - Lesions

KW - MRI

KW - Neuroinformatics

KW - Stroke

KW - Big data

KW - Lesions

KW - MRI

KW - Neuroinformatics

KW - Stroke

UR - https://www.scopus.com/pages/publications/85083706027

U2 - 10.1002/hbm.25015

DO - 10.1002/hbm.25015

M3 - Article

C2 - 32310331

SN - 1065-9471

VL - unknown

SP - 129

EP - 148

JO - Human Brain Mapping

JF - Human Brain Mapping

IS - 1

ER -

The ENIGMA Stroke Recovery Working Group: Big data neuroimaging to study brain–behavior relationships after stroke: Big data neuroimaging to study brain–behavior relationships after stroke

Abstract

UN SDGs

Keywords

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