Between- and within-scanner variability in the CaliBrain study n-back cognitive task

Biomechanical correlates of symptomatic and asymptomatic neurophysiological impairment in high school football

“…Furthermore, while substantial inter-subject variability may exist in the raw value of the t-statistic in any given scanning session, this study focuses on the changes in t-statistic between the pre-season scan and an in-season scan. Given the good repeatability of the N-back task in non-athletes (Gradin et al, 2010), substantial inter-subject variability in the change from pre-season values is not expected, except for that variability arising from blows to the head during football gameplay. Therefore, the relative insensitivity of the N-back task to outside factors and the use of pre-season data to obtain changes in fMRI allowed us to connect neurophysiological changes to biomechanical insults sustained during football-related activity.…”

Multivariate classification of autism spectrum disorder using frequency-specific resting-state functional connectivity—A multi-center study

“…So multicenter datasets are needed. Recent data sharing projects such as the 1000 Functional Connectomes Project (Biswal et al, 2010), the International Neuroimaging Data-sharing Initiative (INDI) (Mennes et al, 2013) and the Autism Brain Imaging Data Exchange (ABIDE) (Di Martino et al, 2014) have revealed that resting-state fMRI datasets obtained from multi-sites are fruitfully aggregated for discovery and replication (Tomasi and Volkow, 2012) and is regarded that analysis using multi-center data can facilitate recruitment, increase study power, and overcome between-scanner variance to produced more generalizable results revealing common regions that contribute to classification consistently within each dataset (Biswal et al, 2010;Gradin et al, 2010;Moorhead et al, 2009;Suckling et al, 2010).…”

Reliability of an fMRI paradigm for emotional processing in a multisite longitudinal study

“…Traveling participant designs, in which participants are scanned at each site of a multisite study, uniquely allow for the comparison of variance in blood oxygen level-dependent (BOLD) signal due to person-versus site-related factors [e.g., Brown et al, 2011; Gountouna et al, 2010; Gradin et al, 2010; Yendiki et al, 2010]. If activation measures show greater variation related to person than site, person-related effects are likely to generalize across sites and would support the aggregation of data across sites.…”