Abstract #3760

Wavelet variance analysis of brain resting state temporal dynamics reveals role of precuneus to reach and sustain abnormal default-mode network activity in major depressive disorder

Masaya Misaki¹, Hideo Suzuki¹, Jonathan Savitz^1,2, Brett McKinney³, and Jerzy Bodurka^1,4

¹Laureate Institute for Brain Research, Tulsa, OK, United States, ²Dept. of Medicine, Tulsa School of Community Medicine, University of Tulsa, Tulsa, OK, United States, ³Tandy School of Computer Science, Dept. of Mathematics, University of Tulsa, Tulsa, OK, United States, ⁴College of Engineering, University of Oklahoma, Tulsa, OK, United States

We investigated temporal dynamics of resting-state brain activation in BOLD resting-state networks (RSNs) in patients with major depressive disorder (MDD) and healthy controls (HC). The wavelet variance analysis was applied to the RSNs time courses to assess frequency specific temporal fluctuations. Comparing to HC, MDD subjects had significantly lower fluctuation in the default-mode network (DMN) and the high-visual network in 0.031-0.125Hz and higher fluctuation in the language/auditory and the cerebellum networks in 0.125-0.25Hz and 0.0156-0.031Hz. The low DMN fluctuation in MDD was associated with high precuneus activity that triggered increase of DMN activity.

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