Forskning
Udskriv Udskriv
Switch language
Region Hovedstaden - en del af Københavns Universitetshospital
Udgivet

Dissociated brain functional connectivity of fast versus slow frequencies underlying individual differences in fluid intelligence: a DTI and MEG study

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

DOI

  1. Biochemical abnormalities among patients referred for celiac disease antibody blood testing in a primary health care setting

    Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

  2. Reduced levels of pulmonary surfactant in COVID-19 ARDS

    Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

  3. Chronic inflammation markers and cytokine-specific autoantibodies in Danish blood donors with restless legs syndrome

    Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

  4. Assessment of immunogenicity and drug activity in patient sera by flow-induced dispersion analysis

    Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

  5. Evaluation of 2D super-resolution ultrasound imaging of the rat renal vasculature using ex vivo micro-computed tomography

    Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

Vis graf over relationer

Brain network analysis represents a powerful technique to gain insights into the connectivity profile characterizing individuals with different levels of fluid intelligence (Gf). Several studies have used diffusion tensor imaging (DTI) and slow-oscillatory resting-state fMRI (rs-fMRI) to examine the anatomical and functional aspects of human brain networks that support intelligence. In this study, we expand this line of research by investigating fast-oscillatory functional networks. We performed graph theory analyses on resting-state magnetoencephalographic (MEG) signal, in addition to structural brain networks from DTI data, comparing degree, modularity and segregation coefficient across the brain of individuals with high versus average Gf scores. Our results show that high Gf individuals have stronger degree and lower segregation coefficient than average Gf participants in a significantly higher number of brain areas with regards to structural connectivity and to the slower frequency bands of functional connectivity. The opposite result was observed for higher-frequency (gamma) functional networks, with higher Gf individuals showing lower degree and higher segregation across the brain. We suggest that gamma oscillations in more intelligent individuals might support higher local processing in segregated subnetworks, while slower frequency bands would allow a more effective information transfer between brain subnetworks, and stronger information integration.

OriginalsprogEngelsk
Artikelnummer4746
TidsskriftScientific Reports
Vol/bind12
Udgave nummer1
Sider (fra-til)4746
ISSN2045-2322
DOI
StatusUdgivet - 18 mar. 2022

Bibliografisk note

© 2022. The Author(s).

ID: 77931255