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Abstract #2683

Quality control and nuisance regression of fMRI, looking out where signal should not be found

Céline Provins1, Christopher J. Markiewicz2, Rastko Ciric2, Mathias Goncalves2, Cesar Caballero-Gaudes3, Russell A. Poldrack2, Patric Hagmann1, and Oscar Esteban1
1Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland, 2Department of Psychology, Stanford University, Stanford, CA, US, Stanford, CA, United States, 3Basque Center on Cognition, Brain and Language, Donostia, Spain, Donostia, Spain


Quality control of functional MRI data is essential as artifacts can have a critical impact on subsequent analysis. Yet, visual assessment of a dataset is tedious and time-consuming. By extending the carpet plot with the voxels located on a closed band (or “crown”) around the brain, we showed that fMRI data quality can be assessed more effectively. This new feature has been incorporated into MRIQC and fMRIPrep. In addition, a new nuisance regressor has been added to the latter, calculated from timeseries within this new “crown”.

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