Journal article
Analysis of task-based functional MRI data preprocessed with fMRIPrep.
- Esteban O Department of Psychology, Stanford University, Stanford, CA, USA. phd@oscaresteban.es.
- Ciric R Department of Psychology, Stanford University, Stanford, CA, USA.
- Finc K Centre for Modern Interdisciplinary Technologies, Nicolaus Copernicus University in Toruń, Toruń, Poland.
- Blair RW Department of Psychology, Stanford University, Stanford, CA, USA.
- Markiewicz CJ Department of Psychology, Stanford University, Stanford, CA, USA.
- Moodie CA Department of Psychology, Stanford University, Stanford, CA, USA.
- Kent JD Neuroscience Program, University of Iowa, Iowa City, IA, USA.
- Goncalves M McGovern Institute for Brain Research, MIT, Cambridge, MA, USA.
- DuPre E Montreal Neurological Institute, McGill University, Montreal, Canada.
- Gomez DEP Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, Netherlands.
- Ye Z State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China.
- Salo T Department of Psychology, Florida International University, Miami, FL, USA.
- Valabregue R 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.
- Amlien IK Center for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo, Norway.
- Liem F URPP Dynamics of Healthy Aging, University of Zurich, Zürich, Switzerland.
- Jacoby N Department of Psychology, Columbia University, New York, NY, USA.
- Stojić H Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, UK.
- Cieslak M Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
- Urchs S Montreal Neurological Institute, McGill University, Montreal, Canada.
- Halchenko YO Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH, USA.
- Ghosh SS McGovern Institute for Brain Research, MIT, Cambridge, MA, USA.
- De La Vega A Department of Psychology, University of Texas at Austin, Austin, TX, USA.
- Yarkoni T Department of Psychology, University of Texas at Austin, Austin, TX, USA.
- Wright J Department of Psychology, Stanford University, Stanford, CA, USA.
- Thompson WH Department of Psychology, Stanford University, Stanford, CA, USA.
- Poldrack RA Department of Psychology, Stanford University, Stanford, CA, USA.
- Gorgolewski KJ
- 2020-06-10
Published in:
- Nature protocols. - 2020
Animals
Brain
Humans
Image Processing, Computer-Assisted
Magnetic Resonance Imaging
Reference Standards
Rest
Workflow
English
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.
- Language
-
- English
- Open access status
- green
- Identifiers
-
- DOI 10.1038/s41596-020-0327-3
- PMID 32514178
- Persistent URL
- https://folia.unifr.ch/global/documents/266941
Statistics
Document views: 77
File downloads: