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

Synopsis

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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