Dynamic reorganization of human resting-state networks during visuospatial attention

Abstract

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 DAN→VIS 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 "idling" 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 "prior" for attention selection.functional connectivity | directional connectivity | resting-state networks | attention networks | task-evoked activity T he function of the brain has been traditionally studied in response to controlled stimuli at the level of single neurons, cortical circuits, or systems, and spontaneous activity has been modeled as stochastic noise, with its variability randomly affecting the threshold of postsynaptic firing (hence, the forward transmission of information through cortical circuits) (1). However, in the last two decades, it has become apparent that spontaneous activity is far from random but organized in space and time at the level of micro-and macrocircuitries (2) as well as at the level of large-scale distributed neuroanatomical systems (3). The large-scale organization of spontaneous activity has been most effectively studied by computing the temporal correlation of the blood oxygenation level-dependent (BOLD) signal (or functional connectivity) measured at rest with functional magnetic resonance imaging (fMRI) in the absence of any task or stimulus. The whole cerebral cortex has been subdivided in a relatively small number of networks formed by regions that show correlated activity over long periods of time [resting-state networks (RSNs)] (4, 5). The relatively small number of R...

Evidence for Two Independent Factors that Modify Brain Networks to Meet Task Goals

“…Visual regions had decreased visual correlations, but increased correlations to other (especially control) systems, as in previous reports (Betti et al, 2013; Spadone et al, 2015). DMN regions, instead, had decreased correlations with other, especially control, systems (as in (Bluhm et al, 2011; Kelly et al, 2008; Newton et al, 2011; Wang et al, 2012)) and increased within system correlations during tasks.…”

“…The logic is that regions specialized for individual cognitive operations are both simultaneously activated and need to interact to complete a complex task. For example, in visual attention tasks, changes in FC have been recorded between activated visual regions and activated attentional-control regions (e.g., (Gazzaley et al, 2007; Spadone et al, 2015)), presumably reflecting the need for control regions to communicate with visual regions. This view proposes that interactions among brain regions are altered in different contexts primarily due to the specialized functions of the individual brain regions.…”

The modular and integrative functional architecture of the human brain

“…Moreover, an fMRI study of learning across time showed that, although connectivity between motor and visual modules is broadly evident in all nodes within those modules (not just at connector nodes), motor and visual modules become less connected (i.e., more modular) to each other during learning, and this process appears to be driven by the temporo-parietal junction, entorhinal cortex, and a fronto-cingulate network, all of which contain connector nodes in our analysis (28). Finally, an fMRI study of a visual attention task found that connectivity changes in visual cortex that led to smaller local modules were associated with stronger top-down directional influence from, and stronger connectivity between, the dorsal frontal eye field, the intraparietal sulcus, and the superior parietal lobule, which are all connector nodes in our analysis (32). Together, these studies suggest that the connectivity of connector nodes allows for effective integration across modules and the coordination of between-module connectivity to maintain modularity, which improves performance.…”

“…Importantly, the brain's network architecture during task performance is shaped primarily by the network architecture present during resting state (i.e., spontaneous neural activity), as spontaneous neural activity is likely a prior or constraint on task activity (31,32). This has been demonstrated in humans using fMRI (33)(34)(35)(36)(37), in monkeys using multielectrode recordings (38), and in zebrafish using two-photon Ca 2+ imaging (39).…”

Spectral properties of the temporal evolution of brain network structure

“…6 Furthermore, the coordination of brain activity between disparate brain subnetworks is a dynamic and taskdependent process. [7][8][9][10] Temporal dynamic interactions within brain subnetworks play an important role in supporting brain information processing. 11,12 Fluctuations in brain systems involve a wide range of spatial and temporal scales.…”