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A resting state fMRI analysis pipeline for pooling inference across diverse cohorts: an ENIGMA rs-fMRI protocol

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.

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Funding

Support was received from NIH grants U54 EB020403, U01MH108148, 2R01EB015611, R01MH112180, R01DA027680, R01MH085646. MarbG and MuenG (FOR2107 study): Work was supported by the German Research Foundation (DFG), grant numbers FOR2107; KI 588/15–1 to TK, DA 1151/5–1 to UD, KO 4291/4–1 and KR 3822/5–1 to AK. JV is a Postdoctoral Fellow of the Research Foundation - Flanders (FWO; grant number 12S1615N).

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Correspondence to Bhim M. Adhikari.

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All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

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Adhikari, B.M., Jahanshad, N., Shukla, D. et al. A resting state fMRI analysis pipeline for pooling inference across diverse cohorts: an ENIGMA rs-fMRI protocol. Brain Imaging and Behavior 13, 1453–1467 (2019). https://doi.org/10.1007/s11682-018-9941-x

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Keywords

  • ENIGMA EPI template
  • Large multi-site studies
  • Processing pipelines