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dc.contributor.authorDEMİRALP, Tamer
dc.contributor.authorNese, Huden
dc.contributor.authorBAYRAM, Ali
dc.contributor.authorHari, Emre
dc.contributor.authorKURT, Elif
dc.contributor.authorAdemoglu, Ahmet
dc.date.accessioned2021-12-10T11:46:39Z
dc.date.available2021-12-10T11:46:39Z
dc.identifier.citationNese H., BAYRAM A., Hari E., KURT E., Ademoglu A., DEMİRALP T., "Phase consistency analysis of the brain functional connectivity networks Beyin fonksiyonel baǧlantisallik aǧlarinin faz tutarlilik analizi", 29th IEEE Conference on Signal Processing and Communications Applications, SIU 2021, Virtual, Istanbul, Türkiye, 9 - 11 Haziran 2021
dc.identifier.othervv_1032021
dc.identifier.otherav_94127203-5979-4f38-a0d7-59a2d1752a60
dc.identifier.urihttp://hdl.handle.net/20.500.12627/172609
dc.identifier.urihttps://doi.org/10.1109/siu53274.2021.9477871
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85111463449&origin=inward
dc.description.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.
dc.language.isoeng
dc.subjectBilgisayar Bilimleri
dc.subjectSinyal İşleme
dc.subjectBilgi Sistemleri, Haberleşme ve Kontrol Mühendisliği
dc.subjectMATEMATİK, UYGULAMALI
dc.subjectMÜHENDİSLİK, ELEKTRİK VE ELEKTRONİK
dc.subjectTELEKOMÜNİKASYON
dc.subjectMühendislik ve Teknoloji
dc.subjectComputer Networks and Communications
dc.subjectPhysical Sciences
dc.subjectArtificial Intelligence
dc.subjectComputer Science Applications
dc.subjectComputer Vision and Pattern Recognition
dc.subjectSignal Processing
dc.subjectModeling and Simulation
dc.subjectTemel Bilimler (SCI)
dc.subjectTemel Bilimler
dc.subjectAlgoritmalar
dc.subjectBİLGİSAYAR BİLİMİ, YAPAY ZEKA
dc.subjectMatematik
dc.subjectMühendislik
dc.subjectBilgisayar Bilimi
dc.subjectMühendislik, Bilişim ve Teknoloji (ENG)
dc.titlePhase consistency analysis of the brain functional connectivity networks Beyin fonksiyonel baǧlantisallik aǧlarinin faz tutarlilik analizi
dc.typeBildiri
dc.contributor.departmentBoğaziçi Üniversitesi , ,
dc.contributor.firstauthorID2720997


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