Poster C82, Sunday, March 25, 1:00-3:00 pm, Exhibit Hall C
Quasi-Periodic Patterns of Intrinsic Brain Activity: Stability and Individual-Specificity
Behnaz Yousefi1, Eric Schumacher2, Shella Keilholz1; 1School of Biomedical Engineering, Emory University/Georgia Institute of Technology, Atlanta, GA, USA, 2School of Psychology, Georgia Institute of Technology
Intrinsic brain activity, as reflected in spontaneous fluctuations of functional MRI signal in resting states, has shown to exhibit a quasi-periodic spatiotemporal pattern (QPP), roughly occurring every 20s in humans, and mainly revealing the course of activation and deactivation of the default mode network (DMN)[1,2]. Spatial extend of areas strongly anti-correlated with DMN in a QPP has shown to vary among individuals, based on which QPP can be coarsely categorized into two types: anti-correlated type and most-correlated type . To examine stability and individual-specificity of QPP, we used Human Connectome Project resting state dataset, which is acquired on two subsequent days, and performed QPP analysis for each day for 470 individuals with low to moderate head motion. We found: I) individuals with anti-correlated type QPP are more stable in their QPP type; out of 245 individuals with anti-correlated type QPP on day 1, 178 (~%73) exhibit the same type on day 2, and out of 225 individuals with most-correlated type QPP on day 1, 130 (~%58) exhibit the same type on day 2, II) QPPs are significantly more correlated between days within-subjects (median:0.78) than between-subjects (median: 0.65; pKolmogorov-Smirnov-test:1.4e-88); this result is unchanged by global signal regression, although medians are reduced (within-subject: 0.63, between-subject:0.42, pKStest:1.4e-88). Our findings show QPPs are reasonably stable and individual-specific hence could serve as markers of traits and we can further examine their behavioral correlates. Moreover, quasi-periodic spatiotemporal patterns might be rich enough to significantly enhance fingerprinting of individuals [3,4] and expand our insight into brain functionality.
Topic Area: METHODS: Neuroimaging