Functional connectivity density mapping

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 th...

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Published inProceedings of the National Academy of Sciences - PNAS Vol. 107; no. 21; pp. 9885 - 9890
Main Authors Tomasi, Dardo, Volkow, Nora D
Format Journal Article
LanguageEnglish
Published United States National Academy of Sciences 25.05.2010
National Acad Sciences
Subjects
Adolescent
Adult
Aged
Biological Sciences
Brain
Brain - cytology
Brain - physiology
Brain Mapping
cognition
Cognition & reasoning
Cognitive ability
Connected regions
Connectivity
Correlation analysis
cortex
Datasets
Energy efficiency
Female
Humans
Imaging
Magnetic Resonance Imaging
Male
Middle Aged
Neurons
Neuropsychology
NMR
Nuclear magnetic resonance
Spatial distribution
Statistical variance
Time series
time series analysis
Young Adult
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Summary: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 10³ 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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Author contributions: D.T. and N.D.V. designed research; D.T. performed research; D.T. contributed new reagents/analytic tools; D.T. analyzed data; and D.T. and N.D.V. wrote the paper.
Edited by Robert Desimone, Massachusetts Institute of Technology, Cambridge, MA, and approved April 21, 2010 (received for review February 4, 2010)
ISSN:0027-8424
1091-6490
1091-6490
DOI:10.1073/pnas.1001414107