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PLoS One. 2011;6(12):e28817. doi: 10.1371/journal.pone.0028817. Epub 2011 Dec 13.

Resting-state brain organization revealed by functional covariance networks.

Author information

1
Department of Medical Imaging, Jinling Hospital, Nanjing University School of Medicine, Nanjing, Jiangsu Province, China.

Abstract

BACKGROUND:

Brain network studies using techniques of intrinsic connectivity network based on fMRI time series (TS-ICN) and structural covariance network (SCN) have mapped out functional and structural organization of human brain at respective time scales. However, there lacks a meso-time-scale network to bridge the ICN and SCN and get insights of brain functional organization.

METHODOLOGY AND PRINCIPAL FINDINGS:

We proposed a functional covariance network (FCN) method by measuring the covariance of amplitude of low-frequency fluctuations (ALFF) in BOLD signals across subjects, and compared the patterns of ALFF-FCNs with the TS-ICNs and SCNs by mapping the brain networks of default network, task-positive network and sensory networks. We demonstrated large overlap among FCNs, ICNs and SCNs and modular nature in FCNs and ICNs by using conjunctional analysis. Most interestingly, FCN analysis showed a network dichotomy consisting of anti-correlated high-level cognitive system and low-level perceptive system, which is a novel finding different from the ICN dichotomy consisting of the default-mode network and the task-positive network.

CONCLUSION:

The current study proposed an ALFF-FCN approach to measure the interregional correlation of brain activity responding to short periods of state, and revealed novel organization patterns of resting-state brain activity from an intermediate time scale.

PMID:
22174905
PMCID:
PMC3236756
DOI:
10.1371/journal.pone.0028817
[Indexed for MEDLINE]
Free PMC Article

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