Phase consistency analysis of the brain functional connectivity networks Beyin fonksiyonel baǧlantisallik aǧlarinin faz tutarlilik analizi


Nese H., BAYRAM A. , Hari E., KURT E. , Ademoglu A., DEMİRALP T.

29th IEEE Conference on Signal Processing and Communications Applications, SIU 2021, Virtual, Istanbul, Turkey, 9 - 11 June 2021 identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1109/siu53274.2021.9477871
  • City: Virtual, Istanbul
  • Country: Turkey
  • Keywords: Intrinsic connectivity networks, Resting state functional magnetic resonance imaging, Within-network phase consistency

Abstract

© 2021 IEEE.Intrinsic connectivity networks (ICN) are defined by the temporal correlations observed in low-frequency (0.01-0.1 Hz) oscillations of the blood oxygenation level (BOLD) signal between brain regions. These spatial connectivity maps overlap with areas of the brain known to be associated with various sensory, motor and cognitive functions. However, the brain is a complex dynamic system and phase synchronization may provide more illuminating measurements. In this study, we examined how the within-network phase consistency (WNPC) of ICNs changes according to frequencies and how these networks differ from each other in terms of within-network synchronization. The resting fMRI data of 96 participants (53 women) from the Human Connectome Project (HCP) were used. An average phase difference value of the network is calculated for the BOLD signal of each parcel. When ICNs are compared in terms of phase synchronization, it is observed that they are roughly divided into three main groups: sensory (visual, somatomotor), attention (dorsal attention, ventral attention) and higher cognitive (default mode, control and limbic). High-level cognitive networks have significantly lower within-network phase consistency compared to sensory and attention networks. Cluster-mass permutation test was used to see whether the differences between ICNs had frequency selectivity, and the frequency ranges with differentiation were determined. Different phase synchronization patterns of ICNs can provide new information about the intrinsic mechanisms of networks.