Telling functional networks apart using ranked network features stability

Basit Öğe Kaydı
dc.authorid0000-0002-0860-0524
dc.authorid0000-0002-7555-3801
dc.authorid0000-0002-7715-3035
dc.contributor.authorZanin, Massimiliano
dc.contributor.authorGüntekin, Bahar
dc.contributor.authorAktürk, Tuba
dc.contributor.authorYıldırım, Ebru
dc.contributor.authorYener, Görsev
dc.contributor.authorKıyı, İlayda
dc.contributor.authorHünerli Gündüz, Duygu
dc.contributor.authorSequeira, Henrique
dc.contributor.authorPapo, David
dc.date.accessioned2022-02-25T08:06:45Z
dc.date.available2022-02-25T08:06:45Z
dc.date.issued2022
dc.departmentİstanbul Medipol Üniversitesi, Tıp Fakültesi, Temel Tıp Bilimleri Bölümü, Biyofizik Ana Bilim Dalı
dc.departmentİstanbul Medipol Üniversitesi, Rektörlük, Sağlık Bilim ve Teknolojileri Araştırma Enstitüsü
dc.departmentİstanbul Medipol Üniversitesi, İMÜ Meslek Yüksekokulu, Elektronörofizyoloji Ana Bilim Dalı
dc.description.abstractOver the past few years, it has become standard to describe brain anatomical and functional organisation in terms of complex networks, wherein single brain regions or modules and their connections are respectively identified with network nodes and the links connecting them. Often, the goal of a given study is not that of modelling brain activity but, more basically, to discriminate between experimental conditions or populations, thus to find a way to compute differences between them. This in turn involves two important aspects: defining discriminative features and quantifying differences between them. Here we show that the ranked dynamical stability of network features, from links or nodes to higher-level network properties, discriminates well between healthy brain activity and various pathological conditions. These easily computable properties, which constitute local but topographically aspecific aspects of brain activity, greatly simplify inter-network comparisons and spare the need for network pruning. Our results are discussed in terms of microstate stability. Some implications for functional brain activity are discussed.
dc.description.sponsorshipTurkiye Bilimsel ve Teknolojik Arastirma Kurumu (TUBITAK)-218S314en_US
dc.description.sponsorshipFrench Ministry of Foreign Affairs PHC-Bosphore Programen_US
dc.description.sponsorshipEuropean Research Council (ERC)en_US
dc.description.sponsorshipSpanish State Research Agency, through the Severo Ochoa and Maria de Maeztu Program for Centers and Units of Excellence in RDen_US
dc.identifier.citationZanin, M., Güntekin, B., Aktürk, T., Yıldırım, E., Yener, G., Kıyı, İ. ... Papo, D. (2022). Telling functional networks apart using ranked network features stability. Scientific Reports, 12(1), 2562-2562. http://doi.org/10.1038/s41598-022-06497-w
dc.identifier.doi10.1038/s41598-022-06497-w
dc.identifier.endpage2562
dc.identifier.issn2045-2322
dc.identifier.issue1
dc.identifier.pmid35169227
dc.identifier.scopus2-s2.0-85124680483
dc.identifier.scopusqualityQ1
dc.identifier.startpage2562
dc.identifier.urihttp://doi.org/10.1038/s41598-022-06497-w
dc.identifier.urihttps://hdl.handle.net/20.500.12511/9005
dc.identifier.volume12
dc.identifier.wos000756701900003en_US
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.indekslendigikaynakPubMed
dc.institutionauthorGüntekin, Bahar
dc.institutionauthorAktürk, Tuba
dc.institutionauthorYıldırım, Ebru
dc.language.isoen
dc.publisherNLM (Medline)
dc.relation.ispartofScientific Reportsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsAttribution 4.0 International*
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/*
dc.subjectNetwork Features
dc.subjectFunctional Networks
dc.subjectRanked
dc.titleTelling functional networks apart using ranked network features stability
dc.typeArticle

Dosyalar

Orijinal paket
Listeleniyor 1 - 1 / 1
Küçük Resim
İsim:
Guntekin-Bahar-2022.pdf
Boyut:
1.5 MB
Biçim:
Adobe Portable Document Format
Açıklama:
Tam Metin / Full Text
İndir
Lisans paketi
Listeleniyor 1 - 1 / 1
Küçük Resim Yok
İsim:
license.txt
Boyut:
1.44 KB
Biçim:
Item-specific license agreed upon to submission
Açıklama:
İndir

Koleksiyon

Makale Koleksiyonu
Makale Koleksiyonu
Makale Koleksiyonu
PubMed İndeksli Yayınlar Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu
WoS İndeksli Yayınlar Koleksiyonu