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The Role of Nonlinearity in Computing Graph-Theoretical Properties of Resting-State Functional Magnetic Resonance Imaging Brain Networks

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F11%3A00358939" target="_blank" >RIV/67985807:_____/11:00358939 - isvavai.cz</a>

  • Result on the web

    <a href="http://dx.doi.org/10.1063/1.3553181" target="_blank" >http://dx.doi.org/10.1063/1.3553181</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1063/1.3553181" target="_blank" >10.1063/1.3553181</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    The Role of Nonlinearity in Computing Graph-Theoretical Properties of Resting-State Functional Magnetic Resonance Imaging Brain Networks

  • Original language description

    We present a comparison of network analysis results for the brain connectivity graphs capturing either linear and nonlinear or only linear connectivity using 24 sessions of human resting-state fMRI. For comparison, connectivity matrices for multivariatelinear Gaussian surrogate data preserving the correlations, but removing any nonlinearity are generated. Subsequent binarization with multiple thresholds generate graphs corresponding to linear and full nonlinear interactions. The effect of neglecting nonlinearity is then assessed by comparing the values of a range of graph-theoretical measures evaluated for both types of graphs. Statistical comparisons suggest a potential effect of nonlinearity on the local measures - clustering coefficient and betweenness centrality. A subsequent quantitative comparison shows that this effect is practically negligible when compared to the intersubject variability. Further, on the group-average graph level, the nonlinearity effect is unnoticeable.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

  • CEP classification

    BB - Applied statistics, operational research

  • OECD FORD branch

Result continuities

  • Project

    <a href="/en/project/7E08027" target="_blank" >7E08027: Large scale interactions in brain networks and their breakdown in brain diseases</a><br>

  • Continuities

    Z - Vyzkumny zamer (s odkazem do CEZ)

Others

  • Publication year

    2011

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Chaos

  • ISSN

    1054-1500

  • e-ISSN

  • Volume of the periodical

    21

  • Issue of the periodical within the volume

    1

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    13

  • Pages from-to

    "art.no 013119"

  • UT code for WoS article

    000289149100019

  • EID of the result in the Scopus database