Data Quality Influences Observed Links Between Functional Connectivity and Behavior

By J. Siegel, Anish Mitra, Timothy O. Laumann, B. Seitzman, Marcus E. Raichle, Maurizio Corbetta, Abraham Z. Snyder. Cerebral Cortex, 2017

299 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Experimental and Cognitive Psychology

View Paper: https://www.semanticscholar.org/paper/ceac5739cedbad9a124c987e98530e6d48ab01ac

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In Cognitive Neuroscience

In Experimental and Cognitive Psychology

Citations in the corpus

Development of large-scale functional networks from birth to adulthood: a guide to neuroimaging literature (2017, background): “Motion artifacts appear to be tightly related to clinical factors (Fair et al., 2012b) and a whole host of behavioral phenotypes and metrics (Siegel et al., 2016).”
Spatial Topography of Individual-Specific Cortical Networks Predicts Human Cognition, Personality and Emotion (2017, background): “Network topography estimated by all four parcellation approaches (MS-HBM, YeoBackProject, Gordon2017, Wang2015) could predict FD and DVARS quite well (Table S4), suggesting that individual-specific network topography might encode information about motion-related imaging artifacts or motion-related t”
A distributed brain network predicts general intelligence from resting-state human neuroimaging data (2018, background): “Cleaning resting-state fMRI data of the effects of motion remains a very intense topic of research for studies of brain-behavior relationships [83,85,125].”
Ten simple rules for predictive modeling of individual differences in neuroimaging (2019, background): “Additionally, state-of-the-art preprocessing strategies can remove many confound and nuisance variables that cannot be accounted for in data collection, such as physiological and head motion artifacts (Murphy et al., 2013; Power et al., 2012; Siegel et al., 2017; Tagliazucchi and Laufs, 2014).”
Quantitative Assessment of Structural Image Quality (2017, unknown): “Notably, because data quality is likely to be collinear with other subject-level variables including cognitive performance (Siegel et al., 2017), symptom burden, and group status (Yendiki et al.”