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Abstract #3133

Regression of Quasi-Periodic patterns diminishes BOLD functional connectivity and reveals hidden dynamic correlations

Michaƫl Belloy1, Behnaz Yousefi2, Anzar Abbas2, Annemie van Der Linden1, Georgios A. Keliris1, Marleen Verhoye1, and Shella Keilholz2

1University of Antwerp, Antwerpen, Belgium, 2Emory university, Atlanta, GA, United States

Quasi-Periodic patterns (QPPs) represent large-scale recurring patterns in the brain, which appear as promising contributors to low frequency BOLD fluctuations. To assess the impact of QPPs on functional connectivity (FC), we used a general linear model approach to regress their contribution out of the functional images of a group of wild-type mice. We show that QPP regression diminished FC in co-active regions within the QPP, while anti-correlated regions became correlated. By calculating FC on QPP-scrubbed images, we highlight that these effects are not solely an artifact of regression. These results suggest that QPPs orchestrate dynamic correlations between resting state networks.

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