Functional Connectivity Density Mapping

National Institute on Alcohol Abuse and Alcoholism, Bethesda, MD 20892, USA.
Proceedings of the National Academy of Sciences (Impact Factor: 9.67). 05/2010; 107(21):9885-90. DOI: 10.1073/pnas.1001414107
Source: PubMed


Brain networks with energy-efficient hubs might support the high cognitive performance of humans and a better understanding of their organization is likely of relevance for studying not only brain development and plasticity but also neuropsychiatric disorders. However, the distribution of hubs in the human brain is largely unknown due to the high computational demands of comprehensive analytical methods. Here we propose a 10(3) times faster method to map the distribution of the local functional connectivity density (lFCD) in the human brain. The robustness of this method was tested in 979 subjects from a large repository of MRI time series collected in resting conditions. Consistently across research sites, a region located in the posterior cingulate/ventral precuneus (BA 23/31) was the area with the highest lFCD, which suggest that this is the most prominent functional hub in the brain. In addition, regions located in the inferior parietal cortex (BA 18) and cuneus (BA 18) had high lFCD. The variability of this pattern across subjects was <36% and within subjects was 12%. The power scaling of the lFCD was consistent across research centers, suggesting that that brain networks have a "scale-free" organization.

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Available from: Dardo Tomasi, Sep 09, 2015
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    • "depressive symptoms and loneliness , especially since depressive symptoms and loneliness are highly correlated . This study aims to search for brain areas with functional connectivity density ( FCD ; Tomasi and Volkow , 2010 ) changes associated with either depressive symptoms or loneliness in a group of non - demented male elders by conducting a resting state fMRI analysis . "
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    • "This idea is supported by a growing number of EEG/MEG/ECOG studies (He et al. 2008; Nir et al. 2008) that have identified different frequency-specific correlates of fMRI-RSNs, as well as mechanisms of their interaction (de Pasquale et al. 2010; Brookes, Woolrich, et al. 2011; de Pasquale et al. 2012; Hipp et al. 2012; Betti et al. 2013; Marzetti et al. 2013). Electrophysiological RSNs therefore provide a model to study functional segregation and integration in the brain (Bullmore and Sporns 2009; Tomasi and Volkow 2010). One MEG correlate of fMRI RSNs is the coupled fluctuation of BLP in alpha/beta frequency band between different RSN nodes (de Pasquale et al. 2010; Brookes, Woolrich, et al. 2011; de Pasquale et al. 2012; Hipp et al. 2012; Betti et al. 2013). "
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