Functional network organization of the human brain

By Jonathan D. Power, Alexander Li Cohen, Steven M. Nelson, Gagan S. Wig, Kelly Anne Barnes, Jessica A. Church, Alecia C. Vogel, Timothy O. Laumann, Francis M. Miezin, Bradley L. Schlaggar and 1 more. Neuron, 2011

4,147 citations recorded by the source corpus.

Summary Real-world complex systems may be mathematically modeled as graphs, revealing properties of the system. Here we study graphs of functional brain organization in healthy adults using resting state functional connectivity MRI. We propose two novel brain-wide graphs, one of 264 putative functional areas, the other a modification of voxelwise networks that eliminates potentially artificial short-distance relationships. These graphs contain many subgraphs in good agreement with known functional brain systems. Other subgraphs lack established functional identities; we suggest possible functional characteristics for these subgraphs. Further, graph measures of the areal network indicate that the default mode subgraph shares network properties with sensory and motor subgraphs: it is internally integrated but isolated from other subgraphs, much like a “processing” system. The modified voxelwise graph also reveals spatial motifs in the patterning of systems across the cortex.

Subfields: Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/9c38c19e382866587d825afe5336dd9c76cfa02f

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Citations in the corpus

Heterogeneity within the frontoparietal control network and its relationship to the default and dorsal attention networks (2017, neutral): “1D) or Power parcellation (58) (SI Appendix, Fig.”
Functional Magnetic Resonance Imaging Phase Synchronization as a Measure of Dynamic Functional Connectivity (2012, positive): “For ROI analysis, we used a template with 264 functional areas (Power et al., 2011), with a sphere of radius of 4 mm for each ROI.”
Diaschisis: past, present, future. (2014, background): “The functional coupling between brain regions can be determined with the study of temporal correlations between slow fluctuations of the neurovascular signal (functional MRI) or EEG and MEG signals (Deuker et al., 2009; He and Evans, 2010; Power et al., 2011).”
The theory of constructed emotion: an active inference account of interoception and categorization (2017, positive): “…to adjust its internal model to the conditions of the sensory periphery, again in the service of allostasis (e.g. see Figure 6) This is consistent with the salience network’s role in attention regulation; e.g. (Power et al., 2011; Touroutoglou et al., 2012; Ullsperger et al., 2014; Uddin, 2015).”
Network neuroscience (2017, background): “Major themes include the definition of coherent subnetworks spanning the whole brain 28 that exhibit changing topology in conditions of rest (spontaneous activity) and task demand 29 , or in relation to visual input 30 .”
The Segregation and Integration of Distinct Brain Networks and Their Relationship to Cognition (2016, methodology): “…we partitioned the brain into cortical ROIs using two different whole-brain atlases: the 96 cortical ROIs from the anatomical Harvard–Oxford atlas (Desikan et al., 2006) and the 264 cortical and subcortical ROIs from a commonly used functional brain atlas, the areal atlas from Power et al. (2011).”
An evaluation of the efficacy, reliability, and sensitivity of motion correction strategies for resting-state functional MRI (2017, background): “, 2016) and the other containing 264 cortical and subcortical regions (Power et al., 2011).”
Using connectome-based predictive modeling to predict individual behavior from brain connectivity (2017, background): “Several large-scale network definitions exist (see, for example, Finn et al. 4 , Yeo et al. 36 , and Power et al. 12 ).”