Author:
Zanin Massimiliano,Güntekin Bahar,Aktürk Tuba,Yıldırım Ebru,Yener Görsev,Kiyi Ilayda,Hünerli-Gündüz Duygu,Sequeira Henrique,Papo David
Abstract
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.
Funder
H2020 European Research Council
Agencia Estatal de Investigación
Türkiye Bilimsel ve Teknolojik Araştirma Kurumu
Publisher
Springer Science and Business Media LLC
Cited by
1 articles.
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