TY - JOUR
T1 - A resting state fMRI analysis pipeline for pooling inference across diverse cohorts
T2 - an ENIGMA rs-fMRI protocol
AU - Adhikari, Bhim M.
AU - Jahanshad, Neda
AU - Shukla, Dinesh
AU - Turner, Jessica
AU - Grotegerd, Dominik
AU - Dannlowski, Udo
AU - Kugel, Harald
AU - Engelen, Jennifer
AU - Dietsche, Bruno
AU - Krug, Axel
AU - Kircher, Tilo
AU - Fieremans, Els
AU - Veraart, Jelle
AU - Novikov, Dmitry S.
AU - Boedhoe, Premika S.W.
AU - van der Werf, Ysbrand D.
AU - van den Heuvel, Odile A.
AU - Ipser, Jonathan
AU - Uhlmann, Anne
AU - Stein, Dan J.
AU - Dickie, Erin
AU - Voineskos, Aristotle N.
AU - Malhotra, Anil K.
AU - Pizzagalli, Fabrizio
AU - Calhoun, Vince D.
AU - Waller, Lea
AU - Veer, Ilja M.
AU - Walter, Hernik
AU - Buchanan, Robert W.
AU - Glahn, David C.
AU - Hong, L. Elliot
AU - Thompson, Paul M.
AU - Kochunov, Peter
N1 - Publisher Copyright:
© 2018, Springer Science+Business Media, LLC, part of Springer Nature.
PY - 2019/10/1
Y1 - 2019/10/1
N2 - 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.
AB - 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.
KW - ENIGMA EPI template
KW - Large multi-site studies
KW - Processing pipelines
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U2 - 10.1007/s11682-018-9941-x
DO - 10.1007/s11682-018-9941-x
M3 - Article
C2 - 30191514
AN - SCOPUS:85053437315
SN - 1931-7557
VL - 13
SP - 1453
EP - 1467
JO - Brain Imaging and Behavior
JF - Brain Imaging and Behavior
IS - 5
ER -