The spatial structure of resting state connectivity stability on the scale of minutes

Gonzalez-Castillo, Javier; Handwerker, Daniel A.; Robinson, Meghan E.; Hoy, Colin W.; Buchanan, Laura C.; Saad, Ziad S.; Bandettini, Peter A.

doi:10.3389/fnins.2014.00138

Cited by 108 publications

(94 citation statements)

References 57 publications

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“…For instance, interhemispheric functional interactions between different communities are highly variable over the course of a resting-state scan. Meanwhile, interhemispheric connections within the same community, especially homotopic connections, are temporally stable (12)(13)(14). Together, these findings suggest that interhemispheric coordination may occur predominantly via homotopic functional connections.…”

mentioning

confidence: 79%

Stable long-range interhemispheric coordination is supported by direct anatomical projections

Shen¹,

Mišić

Cipollini

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

119

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The functional interaction between the brain's two hemispheres includes a unique set of connections between corresponding regions in opposite hemispheres (i.e., homotopic regions) that are consistently reported to be exceptionally strong compared with other interhemispheric (i.e., heterotopic) connections. The strength of homotopic functional connectivity (FC) is thought to be mediated by the regions' shared functional roles and their structural connectivity. Recently, homotopic FC was reported to be stable over time despite the presence of dynamic FC across both intrahemispheric and heterotopic connections. Here we build on this work by considering whether homotopic FC is also stable across conditions. We additionally test the hypothesis that strong and stable homotopic FC is supported by the underlying structural connectivity. Consistent with previous findings, interhemispheric FC between homotopic regions were significantly stronger in both humans and macaques. Across conditions, homotopic FC was most resistant to change and therefore was more stable than heterotopic or intrahemispheric connections. Across time, homotopic FC had significantly greater temporal stability than other types of connections. Temporal stability of homotopic FC was facilitated by direct anatomical projections. Importantly, temporal stability varied with the change in conductive properties of callosal axons along the anterior-posterior axis. Taken together, these findings suggest a notable role for the corpus callosum in maintaining stable functional communication between hemispheres.functional connectivity | structural connectivity | homotopy | dynamics T he brain's capacity for processing information relies on a modular and hierarchical functional architecture that allows both functional segregation and integration (1, 2). Distributed processing occurs within segregated communities responsible for highly specialized functions, whereas more comprehensive functions require long-range integration across communities. This long-range integration is especially important for coordinating functions between the two hemispheres. Functional connectivity (FC), computed as the temporal correlation or covariance between regionwise signals, varies across different interhemispheric regions. FC is significantly stronger between homotopic regions than between heterotopic regions (3) and is greater than would be expected from the anatomical distance between the homotopic regions (4). This strong homotopic FC is thought to be mediated by the strong underlying structural connectivity of the corpus callosum (CC). Indeed, the majority of callosal fibers are between homotopic brain regions (5-7), and the loss of callosal integrity leads to a loss in homotopic FC (8, 9).Recently, a growing number of resting-state functional MRI (fMRI) studies have reported how FC varies over time (10). Flexibility in cognitive processing is thought to arise from the ability of certain regions to participate dynamically in different network configurations (11). For instance, ...

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mentioning

confidence: 79%

Stable long-range interhemispheric coordination is supported by direct anatomical projections

Shen¹,

Mišić

Cipollini

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

119

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“…Furthermore, the results shown in Fig. 6b suggest that the level of the fluctuations is strongly influenced by the underlying anatomy, possibly explaining why the most stable functional connections are observed between symmetric inter-hemispheric ROIs, expected to be more densely connected, whereas the most variable connections are found between non-symmetric inter-hemispheric regions (Gonzalez-Castillo et al 2014).…”

Section: Structure Guides Transitions Between Functional Brain Statesmentioning

confidence: 96%

“…Using a dynamical framework, various studies have further shown that dynamical FC (dFC) can be seen as the transition between several FC patterns (Gao et al 2010;Deco et al 2013a;Yang et al 2014) presenting varying network properties (Lv et al 2013;Sidlauskaite et al 2014;Gollo and Breakspear 2014;Shen et al 2015). The level of variation, or flexibility of dFC between specific cerebral regions has also been studied (Bassett et al 2011;Allen et al 2012;Gonzalez-Castillo et al 2014), as well as the role of anatomy in these fluctuations (Gollo et al 2015) in the macaque cortex. Finally, many groups have explored daydreaming, or mind wandering using functional imaging.…”

Section: Introductionmentioning

confidence: 99%

Cerebral functional connectivity periodically (de)synchronizes with anatomical constraints

et al. 2015

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This paper studies the link between restingstate functional connectivity (FC), measured by the correlations of fMRI BOLD time courses, and structural connectivity (SC), estimated through fiber tractography. Instead of a static analysis based on the correlation between SC and FC averaged over the entire fMRI time series, we propose a dynamic analysis, based on the time evolution of the correlation between SC and a suitably windowed FC. Assessing the statistical significance of the time series against random phase permutations, our data show a pronounced peak of significance for time window widths around 20-30 TR (40-60 s). Using the appropriate window width, we show that FC patterns oscillate between phases of high modularity, primarily shaped by anatomy, and phases of low modularity, primarily shaped by inter-network connectivity. Building upon recent results in dynamic FC, this emphasizes the potential role of SC as a transitory architecture between different highly connected restingstate FC patterns. Finally, we show that the regions contributing the most to these whole-brain level fluctuations of FC on the supporting anatomical architecture belong to the default mode and the executive control networks Steven Laureys and Rodolphe Sepulchre contributed equally. Electronic supplementary material 123Brain Struct Funct DOI 10.1007/s00429-015-1083-y suggesting that they could be capturing consciousness-related processes such as mind wandering.

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“…Furthermore, FC dynamics exhibit rich spatiotemporal structure. Connections between higher order cognitive regions are more variable than those between primary sensorymotor regions (13)(14)(15), and a limited set of whole-brain, quasistable FC configurations-known as FC states-reliably recur both within and across subjects at rest (13,16).…”

mentioning

confidence: 99%

Tracking ongoing cognition in individuals using brief, whole-brain functional connectivity patterns

Gonzalez-Castillo

Hoy

Handwerker

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

Self Cite

340

358

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Functional connectivity (FC) patterns in functional MRI exhibit dynamic behavior on the scale of seconds, with rich spatiotemporal structure and limited sets of whole-brain, quasi-stable FC configurations (FC states) recurring across time and subjects. Based on previous evidence linking various aspects of cognition to grouplevel, minute-to-minute FC changes in localized connections, we hypothesized that whole-brain FC states may reflect the global, orchestrated dynamics of cognitive processing on the scale of seconds. To test this hypothesis, subjects were continuously scanned as they engaged in and transitioned between mental states dictated by tasks. FC states computed within windows as short as 22.5 s permitted robust tracking of cognition in single subjects with near perfect accuracy. Accuracy dropped markedly for subjects with the lowest task performance. Spatially restricting FC information decreased accuracy at short time scales, emphasizing the distributed nature of whole-brain FC dynamics, beyond univariate magnitude changes, as valuable markers of cognition.fMRI | connectivity dynamics | functional connectivity states | cognitive states | classification R esting state functional MRI (rs-fMRI) focuses on spatial patterns of blood oxygenation level dependent (BOLD) signal cofluctuations recorded in the absence of externally driven tasks or stimulation. These patterns, known as functional connectivity (FC) patterns, are usually computed on the basis of an entire scan (often >6 min). Their cognitive significance (1) and long term reproducibility (2) are well established, and preliminary data suggest that they have potential clinical value (3). However, recent studies have shown that FC patterns are highly dynamic at shorter temporal scales (4) (i.e., tens of seconds), adding yet another challenge to developing fMRI-based protocols with sufficient single-subject specificity and sensitivity to inform clinical decisions.FC patterns computed with 1-to 2-min portions of a scan can vary substantially around a mean FC pattern obtained using complete 6-to 20-min scans. This dynamic behavior has been observed in awake and sleeping humans (5-8), as well as in anesthetized animals (9, 10). Several studies involving simultaneous fMRI and electrophysiological recordings have suggested that FC dynamics may be driven by neurophysiological sources rather than noise (6,11,12). Furthermore, FC dynamics exhibit rich spatiotemporal structure. Connections between higher order cognitive regions are more variable than those between primary sensorymotor regions (13-15), and a limited set of whole-brain, quasistable FC configurations-known as FC states-reliably recur both within and across subjects at rest (13,16).Given that cognition is supported by highly dynamic brain processes, it has been hypothesized that FC states may reflect changes in ongoing cognitive states during rest (13). Initial task-based studies have been able to differentiate between a limited set of mental tasks (17, 18) and arousal levels (19) on the basis of l...

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The spatial structure of resting state connectivity stability on the scale of minutes

Cited by 108 publications

References 57 publications

Stable long-range interhemispheric coordination is supported by direct anatomical projections

Stable long-range interhemispheric coordination is supported by direct anatomical projections

Cerebral functional connectivity periodically (de)synchronizes with anatomical constraints

Tracking ongoing cognition in individuals using brief, whole-brain functional connectivity patterns

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