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Abstract

Large-scale consortium efforts such as Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) and other collaborative efforts show that combining statistical data from multiple independent studies can boost statistical power and achieve more accurate estimates of effect sizes, contributing to more reliable and reproducible research. A meta- analysis would pool effects from studies conducted in a similar manner, yet to date, no such harmonized protocol exists for resting state fMRI (rsfMRI) data. Here, we propose an initial pipeline for multi-site rsfMRI analysis to allow research groups around the world to analyze scans in a harmonized way, and to perform coordinated statistical tests. The challenge lies in the fact that resting state fMRI measurements collected by researchers over the last decade vary widely, with variable quality and differing spatial or temporal signal-to-noise ratio (tSNR). An effective harmonization must provide optimal measures for all quality data. Here we used rsfMRI data from twenty-two independent studies with approximately fifty corresponding T1-weighted and rsfMRI datasets each, to (A) review and aggregate the state of existing rsfMRI data, (B) demonstrate utility of principal component analysis (PCA)-based denoising and (C) develop a deformable ENIGMA EPI template based on the representative anatomy that incorporates spatial distortion patterns from various protocols and populations.

Details

Title
A resting state fMRI analysis pipeline for pooling inference across diverse cohorts: an ENIGMA rs-fMRI protocol
Author
Adhikari, Bhim M 1 ; Jahanshad, Neda 2 ; Shukla, Dinesh 1 ; Turner, Jessica 3 ; Grotegerd, Dominik 4 ; Dannlowski, Udo 4 ; Kugel, Harald 5 ; Engelen, Jennifer 6 ; Dietsche, Bruno 6 ; Krug, Axel 6 ; Kircher, Tilo 6 ; Fieremans, Els 7 ; Veraart, Jelle 7 ; Novikov, Dmitry S 7 ; Premika S W Boedhoe 8 ; Ysbrand D van der Werf 8 ; Odile A van den Heuvel 8 ; Ipser, Jonathan 9 ; Uhlmann, Anne 9 ; Stein, Dan J 9 ; Dickie, Erin 10 ; Voineskos, Aristotle N 11 ; Malhotra, Anil K 12 ; Pizzagalli, Fabrizio 2 ; Calhoun, Vince D 13 ; Waller, Lea 14 ; Veer, Ilja M 14 ; Hernik Walter 14 ; Buchanan, Robert W 1 ; Glahn, David C 15 ; L Elliot Hong 1 ; Thompson, Paul M 2 ; Kochunov, Peter 1 

 Maryland Psychiatric Research Center, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA 
 Imaging Genetics Center, Keck School of Medicine of USC, Los Angeles, CA, USA 
 Department of Psychology, Georgia State University, Atlanta, GA, USA 
 Department of Psychiatry, University of Münster, Münster, Germany 
 Department of Clinical Radiology, University of Münster, Münster, Germany 
 Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany 
 Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, NY, USA 
 Department of Psychiatry, Department of Anatomy & Neurosciences, VU University Medical Center, Amsterdam, Netherlands 
 Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa 
10  Centre for Addiction and Mental Health, Toronto, ON, Canada 
11  Centre for Addiction and Mental Health, Campbell Family Mental Health Research Institute, Toronto, ON, Canada; Department of Psychiatry, University of Toronto, Toronto, ON, Canada 
12  Department of Psychiatry, The Zucker Hillside Hospital, New York, NY, USA 
13  The Mind Research Network & The University of New Mexico, Albuquerque, NM, USA 
14  Department of Psychiatry and Psychotherapy, Charité Universitätsmedizin Berlin, Berlin, Germany 
15  Department of Psychiatry, Yale University, School of Medicine, New Haven, CT, USA 
Pages
1453-1467
Publication year
2019
Publication date
Oct 2019
Publisher
Springer Nature B.V.
ISSN
19317557
e-ISSN
19317565
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2100105225
Copyright
Brain Imaging and Behavior is a copyright of Springer, (2018). All Rights Reserved.