The brain must dynamically integrate, coordinate, and respond to internal and external stimuli across multiple time scales. Non-invasive measurements of brain activity with fMRI have greatly advanced ...our understanding of the large-scale functional organization supporting these fundamental features of brain function. Conclusions from previous resting-state fMRI investigations were based upon static descriptions of functional connectivity (FC), and only recently studies have begun to capitalize on the wealth of information contained within the temporal features of spontaneous BOLD FC. Emerging evidence suggests that dynamic FC metrics may index changes in macroscopic neural activity patterns underlying critical aspects of cognition and behavior, though limitations with regard to analysis and interpretation remain. Here, we review recent findings, methodological considerations, neural and behavioral correlates, and future directions in the emerging field of dynamic FC investigations.
•Imaging studies have recently begun to examine dynamic properties of FC.•Dynamic FC may yield novel insights into brain function and dysfunction.•We review results, methods, interpretations, and limitations in this emerging field.
Spontaneous fMRI fluctuations are organized in large-scale spatiotemporal structures, or resting-state networks (RSN). However, it is unknown how task performance affects RSN dynamics. We use MEG to ...measure slow (∼0.1 Hz) coherent fluctuations of band-limited power (BLP), a robust correlate of RSN, during rest and movie observation and compare them to fMRI-RSN. BLP correlation, especially in α band, dropped in multiple RSN during movie although overall topography was maintained. Variability of power correlation increased in visual occipital cortex, and transient decrements corresponded to scenes perceived as “event boundaries.” Additionally, stronger task-dependent interactions developed between vision and language networks in θ and β bands, and default and language networks in γ band. The topography of fMRI connectivity and relative changes induced by the movie were well matched to MEG. We conclude that resting-state and task network interactions are clearly different in the frequency domain despite maintenance of underlying network topography.
•The topography of fMRI and MEG RSN is similar during rest and movie observation•The α band BLP network correlation is broadly suppressed during movie observation•Focal task-dependent temporal correlations emerge during movie observation•Sensory stimuli contribute to nonstationary properties of BLP correlation
Betti et al. explore resting-state network (RSN) changes of the temporal dynamics under movie watching with respect to resting state. Movie watching preserves the RSN topography but alters the band-limited power correlation. Resting-state and task network interactions are clearly different in the frequency domain.
Significance The brain is never at rest, and patterns of ongoing correlated activity have been found to resemble patterns during active behavior. A fundamental problem in neuroscience concerns the ...relationship between spontaneous and task-driven activity. During a demanding task that requires selective attention to sensory stimuli, correlated patterns of spontaneous (rest) activity are generally preserved. However, specific changes in synchronization occur within and between networks that correlate with behavioral performance. These results indicate that attention modifies spontaneous activity patterns in support of task performance.
Fundamental problems in neuroscience today are understanding how patterns of ongoing spontaneous activity are modified by task performance and whether/how these intrinsic patterns influence task-evoked activation and behavior. We examined these questions by comparing instantaneous functional connectivity (IFC) and directed functional connectivity (DFC) changes in two networks that are strongly correlated and segregated at rest: the visual (VIS) network and the dorsal attention network (DAN). We measured how IFC and DFC during a visuospatial attention task, which requires dynamic selective rerouting of visual information across hemispheres, changed with respect to rest. During the attention task, the two networks remained relatively segregated, and their general pattern of within-network correlation was maintained. However, attention induced a decrease of correlation in the VIS network and an increase of the DANâVIS IFC and DFC, especially in a top-down direction. In contrast, within the DAN, IFC was not modified by attention, whereas DFC was enhanced. Importantly, IFC modulations were behaviorally relevant. We conclude that a stable backbone of within-network functional connectivity topography remains in place when transitioning between resting wakefulness and attention selection. However, relative decrease of correlation of ongoing âidlingâ activity in visual cortex and synchronization between frontoparietal and visual cortex were behaviorally relevant, indicating that modulations of resting activity patterns are important for task performance. Higher order resting connectivity in the DAN was relatively unaffected during attention, potentially indicating a role for simultaneous ongoing activity as a âpriorâ for attention selection.
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.
► MEG resting state networks (RSNs) can be identified by BLP temporal correlation ► DMN is a core of BLP interaction with other RSNs especially in the β band ► RSNs with stronger internal coupling tend to interact less with other RSNs
de Pasquale et al. investigate the dynamic segregation and interaction among resting state networks showing that the default mode network and the posterior cingulate cortex are highly connected with other resting state networks via the β band.
Functional MRI (fMRI) studies have shown that low-frequency (<0.1 Hz) spontaneous fluctuations of the blood oxygenation level dependent (BOLD) signal during restful wakefulness are coherent within ...distributed large-scale cortical and subcortical networks (resting state networks, RSNs). The neuronal mechanisms underlying RSNs remain poorly understood. Here, we describe magnetoencephalographic correspondents of two well-characterized RSNs: the dorsal attention and the default mode networks. Seed-based correlation mapping was performed using time-dependent MEG power reconstructed at each voxel within the brain. The topography of RSNs computed on the basis of extended (5 min) epochs was similar to that observed with fMRI but confined to the same hemisphere as the seed region. Analyses taking into account the nonstationarity of MEG activity showed transient formation of more complete RSNs, including nodes in the contralateral hemisphere. Spectral analysis indicated that RSNs manifest in MEG as synchronous modulation of band-limited power primarily within the theta, alpha, and beta bands--that is, in frequencies slower than those associated with the local electrophysiological correlates of event-related BOLD responses.
The human hand possesses both consolidated motor skills and remarkable flexibility in adapting to ongoing task demands. However, the underlying mechanisms by which the brain balances stability and ...flexibility remain unknown. In the absence of external input or behavior, spontaneous (intrinsic) brain connectivity is thought to represent a prior of stored memories. In this study, we investigated how manual dexterity modulates spontaneous functional connectivity in the motor cortex during hand movement. Using magnetoencephalography, in 47 human participants (both sexes), we examined connectivity modulations in the α and β frequency bands at rest and during two motor tasks (i.e., finger tapping or toe squeezing). The flexibility and stability of such modulations allowed us to identify two groups of participants with different levels of performance (high and low performers) on the nine-hole peg test, a test of manual dexterity. In the α band, participants with higher manual dexterity showed distributed decreases of connectivity, specifically in the motor cortex, increased segregation, and reduced nodal centrality. Participants with lower manual dexterity showed an opposite pattern. Notably, these patterns from the brain to behavior are mirrored by results from behavior to the brain. Indeed, when participants were divided using the median split of the dexterity score, we found the same connectivity patterns. In summary, this experiment shows that a long-term motor skill-manual dexterity-influences the way the motor systems respond during movements.
Learning through intensive practice has been largely observed in motor, sensory and higher-order cognitive processing. Neuroimaging studies have shown that learning phases are associated with ...different patterns of functional and structural neural plasticity in spatially distributed brain systems. Yet, it is unknown whether distinct neural signatures before practice can foster different subsequent learning stages over time. Here, we employed a bimanual implicit sequence reaction time task (SRTT) to investigate whether the rates of early (one day after practice) and late (one month after practice) post-training motor skill learning were predicted by distinct patterns of pre-training resting state functional connectivity (rs-FC), recorded with functional MRI. We observed that both motor learning descriptors were positively correlated with the strength of rs-FC among pairs of regions within a SRTT-relevant network comprising cerebellar as well as cortical and subcortical motor areas. Crucially, we detected a double dissociation such that early post-training learning was significantly associated with the functional connections within cerebellar regions, whereas late post-training learning was significantly related to the functional connections between cortical and subcortical motor areas. These findings indicate that spontaneous brain activity prospectively carries out behaviorally relevant information to perform experience-dependent cognitive operations far distant in time.
Networks hubs represent points of convergence for the integration of information across many different nodes and systems. Although a great deal is known on the topology of hub regions in the human ...brain, little is known about their temporal dynamics. Here, we examine the static and dynamic centrality of hub regions when measured in the absence of a task (rest) or during the observation of natural or synthetic visual stimuli. We used Magnetoencephalography (MEG) in humans (both sexes) to measure static and transient regional and network-level interaction in α- and β-band limited power (BLP) in three conditions: visual fixation (rest), viewing of movie clips (natural vision), and time-scrambled versions of the same clips (scrambled vision). Compared with rest, we observed in both movie conditions a robust decrement of α-BLP connectivity. Moreover, both movie conditions caused a significant reorganization of connections in the α band, especially between networks. In contrast, β-BLP connectivity was remarkably similar between rest and natural vision. Not only the topology did not change, but the joint dynamics of hubs in a core network during natural vision was predicted by similar fluctuations in the resting state. We interpret these findings by suggesting that slow-varying fluctuations of integration occurring in higher-order regions in the β band may be a mechanism to anticipate and predict slow-varying temporal patterns of the visual environment.
A fundamental question in neuroscience concerns the function of spontaneous brain connectivity. Here, we tested the hypothesis that topology of intrinsic brain connectivity and its dynamics might predict those observed during natural vision. Using MEG, we tracked the static and time-varying brain functional connectivity when observers were either fixating or watching different movie clips. The spatial distribution of connections and the dynamics of centrality of a set of regions were similar during rest and movie in the β band, but not in the α band. These results support the hypothesis that the intrinsic β-rhythm integration occurs with a similar temporal structure during natural vision, possibly providing advanced information about incoming stimuli.
Recently, new MRI systems working at magnetic field below 10 mT (Very and Ultra Low Field regime) have been developed, showing improved T1-contrast in projected 2D maps (i.e. images without slice ...selection). Moving from projected 2D to 3D maps is not trivial due to the low SNR of such devices. This work aimed to demonstrate the ability and the sensitivity of a VLF-MRI scanner operating at 8.9 mT in quantitatively obtaining 3D longitudinal relaxation rate (R1) maps and distinguishing between voxels intensities. We used phantoms consisting of vessels doped with different Gadolinium (Gd)-based Contrast Agent (CA) concentrations, providing a set of various R1 values. As CA, we used a commercial compound (MultiHance®, gadobenate dimeglumine) routinely used in clinical MRI.
3D R1 maps and T1-weighted MR images were analysed to identify each vessel. R1 maps were further processed by an automatic clustering analysis to evaluate the sensitivity at the single-voxel level. Results obtained at 8.9 mT were compared with commercial scanners operating at 0.2 T, 1.5 T, and 3 T.
VLF R1 maps offered a higher sensitivity in distinguishing the different CA concentrations and an improved contrast compared to higher fields. Moreover, the high sensitivity of 3D quantitative VLF-MRI allowed an effective clustering of the 3D map values, assessing their reliability at the single voxel level. Conversely, in all fields, T1-weighted images were less reliable, even at higher CA concentrations.
In summary, with few excitations and an isotropic voxel size of 3 mm, VLF-MRI 3D quantitative mapping showed a sensitivity better than 2.7 s-1 corresponding to a concentration difference of 0.17 mM of MultiHance in copper sulfate doped water, and improved contrast compared to higher fields. Based on these results, future studies should characterize R1 contrast at VLF, also with other CA, in the living tissues.
Functional connectivity (FC) of brain networks dynamically fluctuates during both rest and task execution. Individual differences in dynamic FC have been associated with several cognitive and ...behavioral traits. However, whether dynamic FC also contributes to sensorimotor representations guiding body-environment interactions, such as the representation of peripersonal space (PPS), is currently unknown. PPS is the space immediately surrounding the body and acts as a multisensory interface between the individual and the environment. We used an audio-tactile task with approaching sounds to map the individual PPS extension, and fMRI to estimate the background FC. Specifically, we analyzed FC values for each stimulus type (near and far space) and its across-trial variability. FC was evaluated between task-relevant nodes of two fronto-parietal networks (the Dorsal Attention Network, DAN, and the Fronto-Parietal Network, FPN) and a key PPS region in the premotor cortex (PM). PM was significantly connected to specific task-relevant nodes of the DAN and the FPN during the audio-tactile task, and FC was stronger while processing near space, as compared to far space. At the individual level, less PPS extension was associated with stronger premotor-parietal FC during processing of near space, while the across-trial variability of premotor-parietal and premotor-frontal FC was higher during the processing of far space. Notably, only across-trial FC variability captured the near-far modulation of space processing. Our findings indicate that PM connectivity with task-relevant frontal and parietal regions and its dynamic changes participate in the mechanisms that enable PPS representation, in agreement with the idea that neural variability plays a crucial role in plastic and dynamic sensorimotor representations.
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