Uncovering Intrinsic Modular Organization of Spontaneous Brain Activity in Humans

By Yong He, Jinhui Wang, Liang Wang, Zhang John Chen, Chaogan Yan, Hong Yang, Hehan Tang, Chaozhe Zhu, Qiyong Gong, Yufeng Zang and 1 more. PLoS ONE, 2009

657 citations recorded by the source corpus.

The characterization of topological architecture of complex brain networks is one of the most challenging issues in neuroscience. Slow (<0.1 Hz), spontaneous fluctuations of the blood oxygen level dependent (BOLD) signal in functional magnetic resonance imaging are thought to be potentially important for the reflection of spontaneous neuronal activity. Many studies have shown that these fluctuations are highly coherent within anatomically or functionally linked areas of the brain. However, the underlying topological mechanisms responsible for these coherent intrinsic or spontaneous fluctuations are still poorly understood. Here, we apply modern network analysis techniques to investigate how spontaneous neuronal activities in the human brain derived from the resting-state BOLD signals are topologically organized at both the temporal and spatial scales. We first show that the spontaneous brain functional networks have an intrinsically cohesive modular structure in which the connections between regions are much denser within modules than between them. These identified modules are found to be closely associated with several well known functionally interconnected subsystems such as the somatosensory/motor, auditory, attention, visual, subcortical, and the “default” system. Specifically, we demonstrate that the module-specific topological features can not be captured by means of computing the corresponding global network parameters, suggesting a unique organization within each module. Finally, we identify several pivotal network connectors and paths (predominantly associated with the association and limbic/paralimbic cortex regions) that are vital for the global coordination of information flow over the whole network, and we find that their lesions (deletions) critically affect the stability and robustness of the brain functional system. Together, our results demonstrate the highly organized modular architecture and associated topological properties in the temporal and spatial brain functional networks of the human brain that underlie spontaneous neuronal dynamics, which provides important implications for our understanding of how intrinsically coherent spontaneous brain activity has evolved into an optimal neuronal architecture to support global computation and information integration in the absence of specific stimuli or behaviors.

Subfields: Cognitive Neuroscience, Experimental and Cognitive Psychology

View Paper: https://www.semanticscholar.org/paper/978a7b8720c416672f8a607314f008c9d2f4a4db

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Citations in the corpus

Test-retest reliability of resting-state connectivity network characteristics using fMRI and graph theoretical measures (2012, methodology): “Since most studies and especially those focusing on clinical aspects have used the Anatomic-Automatic-Labeling (AAL) template (Ferrarini et al., 2009;He et al., 2009; Liu et al., 2008; Tzourio-Mazoyer et al., 2002; Wang et al., 2009), we decided on using the AAL node approach aswell, providing a…”
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Patterns of hemodynamic low-frequency oscillations in the brain are modulated by the nature of free thought during rest (2012, background): “An increasing number of studies have also described positive or negative temporal correlations between RNs (Fox et al., 2005; He et al., 2009; Tian et al., 2007).”
Eigenvector Centrality Mapping for Analyzing Connectivity Patterns in fMRI Data of the Human Brain (2010, result): “In contrast to previous studies using centrality measures [6,8,9], we have applied them here to a large region of interest consisting of thousands of voxels.”
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