fMRIPrep: a robust preprocessing pipeline for functional MRI

被引：1842

作者：

Esteban, Oscar ^{[1
]}

Markiewicz, Christopher J. ^{[1
]}

Blair, Ross W. ^{[1
]}

Moodie, Craig A. ^{[1
]}

Isik, A. Ilkay ^{[2
]}

Erramuzpe, Asier ^{[3
]}

Kent, James D. ^{[4
]}

Goncalves, Mathias ^{[5
]}

DuPre, Elizabeth ^{[6
]}

Snyder, Madeleine ^{[7
]}

Oya, Hiroyuki ^{[8
]}

Ghosh, Satrajit S. ^{[5
,9
]}

Wright, Jessey ^{[1
]}

Durnez, Joke ^{[1
]}

Poldrack, Russell A. ^{[1
]}

Gorgolewski, Krzysztof J. ^{[1
]}

机构：

[1] Stanford Univ, Dept Psychol, Stanford, CA 94305 USA

[2] Max Planck Inst Empir Aesthet, Hesse, Germany

[3] Biocruces Hlth Res Inst, Computat Neuroimaging Lab, Bilbao, Spain

[4] Univ Iowa, Neurosci Program, Iowa City, IA USA

[5] MIT, McGovern Inst Brain Res, 77 Massachusetts Ave, Cambridge, MA 02139 USA

[6] McGill Univ, Montreal Neurol Inst, Montreal, PQ, Canada

[7] Stanford Univ, Dept Psychiat, Stanford Med Sch, Stanford, CA 94305 USA

[8] Univ Iowa Hlth Care, Dept Neurosurg, Iowa City, IA USA

[9] Harvard Med Sch, Dept Otolaryngol, Boston, MA USA

来源：

NATURE METHODS | 2019年 / 16卷 / 01期

关键词：

MOTION CORRECTION; MEMORY-SYSTEMS; MOTOR CORTEX; BRAIN; BOLD; ORGANIZATION; CONNECTIVITY; REGISTRATION; ATTENTION; NETWORKS;

D O I：

10.1038/s41592-018-0235-4

中图分类号：

Q5 [生物化学];

学科分类号：

071010 ; 081704 ;

摘要：

Preprocessing of functional magnetic resonance imaging (fMRI) involves numerous steps to clean and standardize the data before statistical analysis. Generally, researchers create ad hoc preprocessing workflows for each dataset, building upon a large inventory of available tools. The complexity of these workflows has snowballed with rapid advances in acquisition and processing. We introduce fMRIPrep, an analysis-agnostic tool that addresses the challenge of robust and reproducible preprocessing for fMRI data. fMRIPrep automatically adapts a best-in-breed workflow to the idiosyncrasies of virtually any dataset, ensuring high-quality preprocessing without manual intervention. By introducing visual assessment checkpoints into an iterative integration framework for software testing, we show that fMRIPrep robustly produces high-quality results on a diverse fMRI data collection. Additionally, fMRIPrep introduces less uncontrolled spatial smoothness than observed with commonly used preprocessing tools. fMRIPrep equips neuroscientists with an easy-to-use and transparent preprocessing workflow, which can help ensure the validity of inference and the interpretability of results.

引用

页码：111 / +

页数：10

共 110 条

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