Can this data be saved? Techniques for high motion in resting state scans of first grade children. (December 2022)

• Record Type: Journal Article
• Authors: Smith, Jolinda; Wilkey, Eric; Clarke, Ben; Shanley, Lina; Men, Virany; Fair, Damien; Sabb, Fred W.
• Is Part Of: Developmental cognitive neuroscience. Volume 58(2022)
• Publication Date: 2022-12
• Subjects: Fmri -- Motion -- Artifact -- Resting-state -- Independent component analysis; Cognitive neuroscience -- Periodicals; Developmental neurobiology -- Periodicals; Neuropsychology -- Periodicals; Neuropsychiatry -- Periodicals; 612.8233
• DOI: 10.1016/j.dcn.2022.101178
• Languages: English
• ISSNs: 1878-9293

Abstract

Abstract: Motion remains a significant technical hurdle in fMRI studies of young children. Our aim was to develop a straightforward and effective method for obtaining and preprocessing resting state data from a high-motion pediatric cohort. This approach combines real-time monitoring of head motion with a preprocessing pipeline that uses volume censoring and concatenation alongside independent component analysis based denoising. We evaluated this method using a sample of 108 first grade children (age 6–8) enrolled in a longitudinal study of math development. Data quality was assessed by analyzing the correlation between participant head motion and two key metrics for resting state data, temporal signal-to-noise and functional connectivity. These correlations should be minimal in the absence of noise-related artifacts. We compared these data quality indicators using several censoring thresholds to determine the necessary degree of censoring. Volume censoring was highly effective at removing motion-corrupted volumes and ICA denoising removed much of the remaining motion artifact. With the censoring threshold set to exclude volumes that exceeded a framewise displacement of 0.3 mm, preprocessed data met rigorous standards for data quality while retaining a large majority of subjects (83 % of participants). Overall, results show it is possible to obtain usable resting-state data despite extreme motion in a group of young, untrained subjects.