Analysis of task-based functional MRI data preprocessed with fMRIPrep

doi:10.1038/s41596-020-0327-3

. 2020 Jul;15(7):2186-2202.

doi: 10.1038/s41596-020-0327-3. Epub 2020 Jun 8.

Analysis of task-based functional MRI data preprocessed with fMRIPrep

Oscar Esteban¹, Rastko Ciric², Karolina Finc³, Ross W Blair², Christopher J Markiewicz², Craig A Moodie², James D Kent⁴, Mathias Goncalves⁵, Elizabeth DuPre⁶, Daniel E P Gomez⁷, Zhifang Ye⁸, Taylor Salo⁹, Romain Valabregue¹⁰, Inge K Amlien¹¹, Franziskus Liem¹², Nir Jacoby¹³, Hrvoje Stojić¹⁴, Matthew Cieslak¹⁵, Sebastian Urchs⁶, Yaroslav O Halchenko¹⁶, Satrajit S Ghosh^{5

17}, Alejandro De La Vega¹⁸, Tal Yarkoni¹⁸, Jessey Wright², William H Thompson^{2

19}, Russell A Poldrack, Krzysztof J Gorgolewski²

Affiliations

¹ Department of Psychology, Stanford University, Stanford, CA, USA. phd@oscaresteban.es.
² Department of Psychology, Stanford University, Stanford, CA, USA.
³ Centre for Modern Interdisciplinary Technologies, Nicolaus Copernicus University in Toruń, Toruń, Poland.
⁴ Neuroscience Program, University of Iowa, Iowa City, IA, USA.
⁵ McGovern Institute for Brain Research, MIT, Cambridge, MA, USA.
⁶ Montreal Neurological Institute, McGill University, Montreal, Canada.
⁷ Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, Netherlands.
⁸ State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China.
⁹ Department of Psychology, Florida International University, Miami, FL, USA.
¹⁰ CENIR, INSERM U 1127, CNRS UMR 7225, UPMC Univ Paris 06 UMR S 1127, Institut du Cerveau et de la Moelle épinière, ICM, Paris, France.
¹¹ Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo, Norway.
¹² URPP Dynamics of Healthy Aging, University of Zurich, Zürich, Switzerland.
¹³ Department of Psychology, Columbia University, New York, NY, USA.
¹⁴ Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, UK.
¹⁵ Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
¹⁶ Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH, USA.
¹⁷ Department of Otolaryngology, Harvard Medical School, Boston, MA, USA.
¹⁸ Department of Psychology, University of Texas at Austin, Austin, TX, USA.
¹⁹ Department of Clinical Neuroscience, Karolinska Institutet, Solna, Sweden.

PMID: 32514178
PMCID: PMC7404612
DOI: 10.1038/s41596-020-0327-3

Analysis of task-based functional MRI data preprocessed with fMRIPrep

Oscar Esteban et al. Nat Protoc. 2020 Jul.

. 2020 Jul;15(7):2186-2202.

doi: 10.1038/s41596-020-0327-3. Epub 2020 Jun 8.

Authors

Affiliations

¹ Department of Psychology, Stanford University, Stanford, CA, USA. phd@oscaresteban.es.
² Department of Psychology, Stanford University, Stanford, CA, USA.
³ Centre for Modern Interdisciplinary Technologies, Nicolaus Copernicus University in Toruń, Toruń, Poland.
⁴ Neuroscience Program, University of Iowa, Iowa City, IA, USA.
⁵ McGovern Institute for Brain Research, MIT, Cambridge, MA, USA.
⁶ Montreal Neurological Institute, McGill University, Montreal, Canada.
⁷ Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, Netherlands.
⁸ State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China.
⁹ Department of Psychology, Florida International University, Miami, FL, USA.
¹⁰ CENIR, INSERM U 1127, CNRS UMR 7225, UPMC Univ Paris 06 UMR S 1127, Institut du Cerveau et de la Moelle épinière, ICM, Paris, France.
¹¹ Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo, Norway.
¹² URPP Dynamics of Healthy Aging, University of Zurich, Zürich, Switzerland.
¹³ Department of Psychology, Columbia University, New York, NY, USA.
¹⁴ Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, UK.
¹⁵ Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
¹⁶ Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH, USA.
¹⁷ Department of Otolaryngology, Harvard Medical School, Boston, MA, USA.
¹⁸ Department of Psychology, University of Texas at Austin, Austin, TX, USA.
¹⁹ Department of Clinical Neuroscience, Karolinska Institutet, Solna, Sweden.

PMID: 32514178
PMCID: PMC7404612
DOI: 10.1038/s41596-020-0327-3

Abstract

Functional magnetic resonance imaging (fMRI) is a standard tool to investigate the neural correlates of cognition. fMRI noninvasively measures brain activity, allowing identification of patterns evoked by tasks performed during scanning. Despite the long history of this technique, the idiosyncrasies of each dataset have led to the use of ad-hoc preprocessing protocols customized for nearly every different study. This approach is time consuming, error prone and unsuitable for combining datasets from many sources. Here we showcase fMRIPrep (http://fmriprep.org), a robust tool to prepare human fMRI data for statistical analysis. This software instrument addresses the reproducibility concerns of the established protocols for fMRI preprocessing. By leveraging the Brain Imaging Data Structure to standardize both the input datasets (MRI data as stored by the scanner) and the outputs (data ready for modeling and analysis), fMRIPrep is capable of preprocessing a diversity of datasets without manual intervention. In support of the growing popularity of fMRIPrep, this protocol describes how to integrate the tool in a task-based fMRI investigation workflow.

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Conflict of interest statement

Competing interests

The authors declare no competing interests.

Figures

**Fig. 1 |. Overall workflow of the fMRIPrep protocol.**
The analytic workflow is subdivided into three principal stages. First, a BIDS-compliant dataset is generated and validated. Next, dataset quality is assessed, and the data are preprocessed. Finally, the preprocessed data undergo a GLM fitting, which yields participant- and group-level statistical maps of task-related BOLD activity. FSL, FMRIB Software Library.

**Fig. 2 |. Running fMRIPrep on HPC.**
Execution of BIDS apps (such as MRIQC or fMRIPrep) is easy to configure on HPC clusters. This figure provides an example execution script for our SLURM-based cluster, Stanford’s Sherlock. An up-to-date, complete version of the script is available at https://fmriprep.readthedocs.io/en/latest/singularity.html#running-singularity-on-a-slurm-system.

**Fig. 3 |. Output of the first-level analysis step.**
Glass brain visualization of a statistical (z-stat) map reflecting the ‘intask-vs.-nontask’ activation obtained for subject 10 (thresholded at z = ±5).

**Fig. 4 |. Group analysis results.**
Visualization of a group statistical (z-stat) map (cluster threshold = 3.2) reflecting the ‘task-vs.-nontask’ activation for all subjects. a, Glass brain visualization. b, Left and right hemisphere surface plot visualizations. Visualizations were generated using a function from Nilearn (see Visualization of results for details).

See this image and copyright information in PMC

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References

1. Poldrack RA & Farah MJ Progress and challenges in probing the human brain. Nature 526, 371–379 (2015). - PubMed
1. Ogawa S, Lee TM, Kay AR & Tank DW Brain magnetic resonance imaging with contrast dependent on blood oxygenation. Proc. Natl Acad. Sci. USA 87, 9868–9872 (1990). - PMC - PubMed
1. Poldrack RA et al. Toward open sharing of task-based fMRI data: the OpenfMRI project. Front. Neuroinformatics 7, 12 (2013). - PMC - PubMed
1. Gorgolewski KJ, Esteban O, Schaefer G, Wandell B & Poldrack RA OpenNeuro—a free online platform for sharing and analysis of neuroimaging data. in Organization for Human Brain Mapping 1677 (2017).
1. Carp J On the plurality of (methodological) worlds: estimating the analytic flexibility of fMRI experiments. Front. Neurosci 6, 149 (2012). - PMC - PubMed

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[1] Poldrack RA & Farah MJ Progress and challenges in probing the human brain. Nature 526, 371–379 (2015). - PubMed

[2] Poldrack RA & Farah MJ Progress and challenges in probing the human brain. Nature 526, 371–379 (2015). - PubMed

[3] Ogawa S, Lee TM, Kay AR & Tank DW Brain magnetic resonance imaging with contrast dependent on blood oxygenation. Proc. Natl Acad. Sci. USA 87, 9868–9872 (1990). - PMC - PubMed

[4] Ogawa S, Lee TM, Kay AR & Tank DW Brain magnetic resonance imaging with contrast dependent on blood oxygenation. Proc. Natl Acad. Sci. USA 87, 9868–9872 (1990). - PMC - PubMed

[5] Poldrack RA et al. Toward open sharing of task-based fMRI data: the OpenfMRI project. Front. Neuroinformatics 7, 12 (2013). - PMC - PubMed

[6] Poldrack RA et al. Toward open sharing of task-based fMRI data: the OpenfMRI project. Front. Neuroinformatics 7, 12 (2013). - PMC - PubMed

[7] Gorgolewski KJ, Esteban O, Schaefer G, Wandell B & Poldrack RA OpenNeuro—a free online platform for sharing and analysis of neuroimaging data. in Organization for Human Brain Mapping 1677 (2017).

[8] Gorgolewski KJ, Esteban O, Schaefer G, Wandell B & Poldrack RA OpenNeuro—a free online platform for sharing and analysis of neuroimaging data. in Organization for Human Brain Mapping 1677 (2017).

[9] Carp J On the plurality of (methodological) worlds: estimating the analytic flexibility of fMRI experiments. Front. Neurosci 6, 149 (2012). - PMC - PubMed

[10] Carp J On the plurality of (methodological) worlds: estimating the analytic flexibility of fMRI experiments. Front. Neurosci 6, 149 (2012). - PMC - PubMed

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Analysis of task-based functional MRI data preprocessed with fMRIPrep

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Analysis of task-based functional MRI data preprocessed with fMRIPrep

Authors

Affiliations

Abstract

Conflict of interest statement

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