Graphical interface for automated management of motion artifact within fMRI acquisitions: INFOBAR

• Authors: Manish Anand, Cincinnati Children's Hospital; Jed Diekfuss, Emory University; Alexis B. Slutsky-Ganesh, University of North Carolina Greensboro; Scott Bonnette, Cincinnati Children's Hospital; Dustin R. Grooms, Ohio University; Gregory Myer, Emory University
• Journal Title: SOFTWAREX
• Volume: Volume 12
• Publisher: ELSEVIER | 2020-07-01
• Type of Work: Article | Final Publisher PDF
• Publisher DOI: http://doi.org/10.1016/j.softx.2020.100598
• Subjects: Computer Science; Biology, Neuroscience
• Keywords: Science & Technology; Technology; Computer Science, Software Engineering; Computer Science; ICA-AROMA; GUI; Batch process; Python; INDEPENDENT COMPONENT ANALYSIS; BRAIN ACTIVITY; STRATEGIES; KNEE

Abstract

Independent Component Analysis-based Automatic Removal of Motion Artifacts (ICA-AROMA; Pruim et al., 2015) is a robust approach to remove brain activity related to head motion within functional magnetic resonance imaging (fMRI) datasets. However, ICA-AROMA requires command line implementation and customized code to batch process large datasets. We developed a cross-platform, open-source graphical user Interface for Batch processing fMRI datasets using ICA-AROMA (INFOBAR). INFOBAR allows a user to search directories, identify appropriate datasets, and batch execute ICA-AROMA. INFOBAR also has additional data processing options and visualization features to support all researchers interested in mitigating head motion artifact in post-processing using ICA-AROMA.