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  fMRIPrep: A robust preprocessing pipeline for functional MRI

Esteban, O., Markiewicz, C. J., Blair, R. W., Moodie, C. A., Isik, A. I., Erramuzpe, A., et al. (2019). fMRIPrep: A robust preprocessing pipeline for functional MRI. Nature methods, 16(1), 111-116. doi:10.1038/s41592-018-0235-4.

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 Creators:
Esteban, Oscar1, Author
Markiewicz, Christopher J.1, Author
Blair, Ross W.1, Author
Moodie, Craig A.1, Author
Isik, Ayse Ilkay2, Author           
Erramuzpe, Asier3, Author
Kent, James D.4, Author
Goncalves, Mathias5, Author
DuPre, Elizabeth6, Author
Snyder, Madeleine7, Author
Oya, Hiroyuki8, Author
Ghosh, Satrajit S.5, 9, Author
Wright, Jessey1, Author
Durnez, Joke1, Author
Poldrack, Russell A.1, Author
Gorgolewski , Krzysztof J.1, Author
Affiliations:
1Department of Psychology, Stanford University , Stanford, CA, USA, ou_persistent22              
2Department of Neuroscience, Max Planck Institute for Empirical Aesthetics, Max Planck Society, ou_2421697              
3Computational Neuroimaging Lab, Biocruces Health Research Institute , Bilbao, Spain, ou_persistent22              
4Neuroscience Program, University of Iowa , Iowa City, IA, USA, ou_persistent22              
5McGovern Institute for Brain Research, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA, ou_persistent22              
6Montreal Neurological Institute, McGill University, Montreal, QC, Canada, ou_persistent22              
7Department of Psychiatry, Stanford Medical School, Stanford University, Stanford, CA, USA, ou_persistent22              
8Department of Neurosurgery, University of Iowa Health Care, Iowa City, IA, USA, ou_persistent22              
9Department of Otolaryngology, Harvard Medical School, Boston, MA, USA, ou_persistent22              

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Free keywords: MOTION CORRECTION; MEMORY-SYSTEMS; MOTOR CORTEX; BRAIN; BOLD; ORGANIZATION; CONNECTIVITY; REGISTRATION; ATTENTION; NETWORKS
 Abstract: 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.

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Language(s): eng - English
 Dates: 2018-04-272018-10-292018-10-292019-01
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: ISI: 000454162400038
DOI: 10.1038/s41592-018-0235-4
 Degree: -

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Title: Nature methods
  Other : Nature methods
Source Genre: Journal
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Publ. Info: New York, NY : Nature Pub. Group
Pages: - Volume / Issue: 16 (1) Sequence Number: - Start / End Page: 111 - 116 Identifier: ISSN: 1548-7091
CoNE: https://pure.mpg.de/cone/journals/resource/111088195279556