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. 2012 May 24;74(4):753-64.
doi: 10.1016/j.neuron.2012.03.031.

A cortical core for dynamic integration of functional networks in the resting human brain

Francesco de Pasquale  1 , Stefania Della Penna, Abraham Z Snyder, Laura Marzetti, Vittorio Pizzella, Gian Luca Romani, Maurizio Corbetta
Affiliations

A cortical core for dynamic integration of functional networks in the resting human brain

Francesco de Pasquale et al. Neuron. .

Abstract

We used magneto-encephalography to study the temporal dynamics of band-limited power correlation at rest within and across six brain networks previously defined by prior functional magnetic resonance imaging (fMRI) studies. Epochs of transiently high within-network band limited power (BLP) correlation were identified and correlation of BLP time-series across networks was assessed in these epochs. These analyses demonstrate that functional networks are not equivalent with respect to cross-network interactions. The default-mode network and the posterior cingulate cortex, in particular, exhibit the highest degree of transient BLP correlation with other networks especially in the 14-25 Hz (β band) frequency range. Our results indicate that the previously demonstrated neuroanatomical centrality of the PCC and DMN has a physiological counterpart in the temporal dynamics of network interaction at behaviorally relevant timescales. This interaction involved subsets of nodes from other networks during periods in which their internal correlation was low.

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Figures

Figure 1
Figure 1
fMRI nodes and MEG resting-state networks (RSNs). A) Location of RSN nodes from the fMRI literature. Arrows denote regions used as seed in temporal correlation maps in Figs. 1B–C; PCC=posterior cingulate cortex; LPIPS=left intraparietal sulcus. B) Topography of wide band band-limited power (BLP) correlation between seed PCC and the rest of the brain during temporal epochs in which within-network correlation is higher than with a control node (maximal correlation windows, or MCWs)(see Methods and SI). Input nodes to define MCWs for default-mode network (DMN): right angular gyrus (RAG) and dorsomedial prefrontal cortex (dMPFC). Other nodes detected in the DMN: ventromedial prefrontal cortex (VMPFC); and, left angular gyrus (LAG). Other nodes detected outside DMN: visual cortex (Vis.Cx); left sensorimotor cortex (SMC). C) Same as B) but seed in LPIPS. Input nodes to define dorsal attention network (DAN)-MCWs: right PIPS (RPIPS) and right frontal eye field (RFEF). Other nodes detected in the DAN: left FEF (LFEF). D) Topography of separate MEG RSNs: Yellow: DAN; Cyan: DMN; Pink: ventral attention network (VAN); Red: visual (VIS); Green: somatomotor (MOT); Orange: language (LAN). Voxels containing more than one network are displayed as white. The map for each RSN is an intersection (logical AND operation) of thresholded Z-score maps for different seeds of a network (see Table S2 for combination of seeds in each network). Therefore only voxels that show consistent correlation with all seeds are retained.
Figure 2
Figure 2
Average cross-network interactions by network and frequency band. Frequency band is indicated above each matrix. The represented quantity is the Z-score computed by comparing the correlation between a pair of nodes vs. the mean correlation with the rest of the brain (see SI for details). This quantity is averaged across all pair-wise correlation between the nodes of one network and the nodes of another network. The matrix is not symmetrical. Each row represents the average correlation of one RSN with others during its MCWs. Each column represents the average correlation of one RSN with others during their MCWs. Statistical significance: *= p<0.01; **= p<0.005.
Figure 3
Figure 3
Cross-network interactions in the beta band by node. A) Same as Fig. 2, but with each network node represented. The matrix is not symmetrical. Each row represents the correlation between one node and all other nodes during the MCWs of the network to which the first node belongs. See Table S1 for a complete list of nodes and abbreviations. Each column represents the correlation between one node and all other nodes during the MCWs of the networks to which the other nodes belong. White cells represent node pairs closer than 35 mm. The bar plots on the right represent the connectivity of each node averaged across the other RSN nodes. Statistical significance: *= p<0.05; **=p<0.001. B) Same as Fig. 3A, but correlation is computed in temporal epochs outside each network’s MCWs. Note lack of within-network correlation and across-network interactions outside of MCWs.
Figure 4
Figure 4
Networks’ temporal properties: MCWs overlap and duration. A) Fraction of temporal overlap of MCWs in the beta band by RSN. B) Ratio of MCW time over total recording time by network in the alpha and beta band. Statistical significance: *=p<0.05; **=p<0.02; ***=p<0.01.
Figure 5
Figure 5
Example of cross-network interaction as a function of MCWs. A) The average power for DAN (red) and DMN (blue) (averaged over all nodes) during one DMN-MCW. The two time series appear strongly correlated. B) Power fluctuations (standard deviation, SD) across different nodes within each network during the same MCW. Small SD in the DMN while high SD in the DAN are observed. C) Within-network correlation is stronger in the DMN (blue bar) than in the DAN (red bar) while cross-network correlation is high (green bar). D) Schematic representation of node-pair coupling. The DMN is strongly internally correlated (thick blue lines). Internal correlation within the DAN is reduced (thin dotted red lines). Some nodes in the DAN (e.g. left PIPS) couples with nodes of the DMN (e.g. PCC) (thick green lines).
See this image and copyright information in PMC

References

    1. Beckmann CF, DeLuca M, Devlin JT, Smith SM. Investigations into resting-state connectivity using independent component analysis. Philos Trans R Soc Lond B Biol Sci. 2005;360:1001–1013. - PMC - PubMed
    1. Biswal BB, Van Kylen J, Hyde JS. Simultaneous assessment of flow and BOLD signals in resting-state functional connectivity maps. NMR Biomed. 1997;10:165–170. - PubMed
    1. Boynton GM, Engel SA, Glover GH, Heeger DJ. Linear systems analysis of functional magnetic resonance imaging in human V1. J Neurosci. 1996;16:4207–4221. - PMC - PubMed
    1. Brookes MJ, Hale JR, Zumer JM, Stevenson CM, Francis ST, Barnes GR, Owen JP, Morris PG, Nagarajan SS. Measuring functional connectivity using MEG: Methodology and comparison with fcMRI. Neuroimage. 2011a;56:1082–1104. - PMC - PubMed
    1. Brookes MJ, Woolrich M, Luckhoo H, Price D, Hale JR, Stephenson MC, Barnes GR, Smith SM, Morris PG. Investigating the electrophysiological basis of resting state networks using magnetoencephalography. Proc Natl Acad Sci U S A. 2011b;108:16783–16788. - PMC - PubMed

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