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.
Head motion systematically alters correlations in resting state functional connectivity fMRI (RSFC). In this report we examine impact of motion on signal intensity and RSFC correlations. We find that ...motion-induced signal changes (1) are often complex and variable waveforms, (2) are often shared across nearly all brain voxels, and (3) often persist more than 10s after motion ceases. These signal changes, both during and after motion, increase observed RSFC correlations in a distance-dependent manner. Motion-related signal changes are not removed by a variety of motion-based regressors, but are effectively reduced by global signal regression. We link several measures of data quality to motion, changes in signal intensity, and changes in RSFC correlations. We demonstrate that improvements in data quality measures during processing may represent cosmetic improvements rather than true correction of the data. We demonstrate a within-subject, censoring-based artifact removal strategy based on volume censoring that reduces group differences due to motion to chance levels. We note conditions under which group-level regressions do and do not correct motion-related effects.
•Motion-related signal changes are varied and can persist >10s after motion ceases.•Such signal changes are often shared across almost all brain voxels.•Within-subject correction strategies can eliminate motion-related group differences.•Examines the linearity of motion's influence on resting state correlations
Resting state functional MRI (fMRI) has enabled description of group-level functional brain organization at multiple spatial scales. However, cross-subject averaging may obscure patterns of brain ...organization specific to each individual. Here, we characterized the brain organization of a single individual repeatedly measured over more than a year. We report a reproducible and internally valid subject-specific areal-level parcellation that corresponds with subject-specific task activations. Highly convergent correlation network estimates can be derived from this parcellation if sufficient data are collected—considerably more than typically acquired. Notably, within-subject correlation variability across sessions exhibited a heterogeneous distribution across the cortex concentrated in visual and somato-motor regions, distinct from the pattern of intersubject variability. Further, although the individual’s systems-level organization is broadly similar to the group, it demonstrates distinct topological features. These results provide a foundation for studies of individual differences in cortical organization and function, especially for special or rare individuals.
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•Single-subject areal parcellation is reproducible, valid, and convergent with task•Highly reliable correlation estimates require considerable data•Within-subject correlation is most variable in visual and somatosensory cortex•Individuals exhibit topological features distinct from group system organization
Resting state functional MRI allows non-invasive analysis of functional brain organization at multiple spatial scales. Laumann et al. report areal and system organization in a highly sampled human and demonstrate that an individual exhibits topological features distinct from group-level system organization.
Multimodal evidence suggests that brain regions accumulate information over timescales that vary according to anatomical hierarchy. Thus, these experimentally defined “temporal receptive windows” are ...longest in cortical regions that are distant from sensory input. Interestingly, spontaneous activity in these regions also plays out over relatively slow timescales (i.e., exhibits slower temporal autocorrelation decay). These findings raise the possibility that hierarchical timescales represent an intrinsic organizing principle of brain function. Here, using resting-state functional MRI, we show that the timescale of ongoing dynamics follows hierarchical spatial gradients throughout human cerebral cortex. These intrinsic timescale gradients give rise to systematic frequency differences among large-scale cortical networks and predict individual-specific features of functional connectivity. Whole-brain coverage permitted us to further investigate the large-scale organization of subcortical dynamics. We show that cortical timescale gradients are topographically mirrored in striatum, thalamus, and cerebellum. Finally, timescales in the hippocampus followed a posterior-to-anterior gradient, corresponding to the longitudinal axis of increasing representational scale. Thus, hierarchical dynamics emerge as a global organizing principle of mammalian brains.
We present a history of the concepts and developments that have led us to focus on the resting state as an object of study. We then discuss resting state research performed in our laboratory since ...2005 with an emphasis on papers of particular interest.
Systems-level organization in spontaneous infra-slow (<0.1Hz) brain activity, measured using blood oxygen signals in fMRI and optical imaging, has become a major theme in the study of neural function ...in both humans and animal models. Yet the neurophysiological basis of infra-slow activity (ISA) remains unresolved. In particular, is ISA a distinct physiological process, or is it a low-frequency analog of faster neural activity? Here, using whole-cortex calcium/hemoglobin imaging in mice, we show that ISA in each of these modalities travels through the cortex along stereotypical spatiotemporal trajectories that are state dependent (wake versus anesthesia) and distinct from trajectories in delta (1–4 Hz) activity. Moreover, mouse laminar electrophysiology reveals that ISA travels through specific cortical layers and is organized into unique cross-laminar temporal dynamics that are different from higher frequency local field potential activity. These findings suggest that ISA is a distinct neurophysiological process that is reflected in fMRI blood oxygen signals.
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•Wide-field Ca/hemoglobin imaging reveals infra-slow spatiotemporal trajectories•Infra-slow activity (ISA) has distinct dynamics compared to higher frequencies•The direction of ISA trajectories depends on state of consciousness•Laminar electrophysiology shows that ISA travels through distinct cortical layers
Mitra et al. measure spontaneous infra-slow activity (ISA; <0.1 Hz) in mouse cortex using wide-field optical calcium/hemoglobin imaging and laminar electrophysiology. They find wide-scale cortical spatiotemporal trajectories in ISA that are state-dependent and distinct from higher frequency neural activity.
Here, we demonstrate that subject motion produces substantial changes in the timecourses of resting state functional connectivity MRI (rs-fcMRI) data despite compensatory spatial registration and ...regression of motion estimates from the data. These changes cause systematic but spurious correlation structures throughout the brain. Specifically, many long-distance correlations are decreased by subject motion, whereas many short-distance correlations are increased. These changes in rs-fcMRI correlations do not arise from, nor are they adequately countered by, some common functional connectivity processing steps. Two indices of data quality are proposed, and a simple method to reduce motion-related effects in rs-fcMRI analyses is demonstrated that should be flexibly implementable across a variety of software platforms. We demonstrate how application of this technique impacts our own data, modifying previous conclusions about brain development. These results suggest the need for greater care in dealing with subject motion, and the need to critically revisit previous rs-fcMRI work that may not have adequately controlled for effects of transient subject movements.
► Large changes in rs-fcMRI timecourses coincide with motion despite motion regression. ► Motion increases short-distance correlations and decreases long-distance correlations. ► Motion artifacts do not arise from, and are not fully countered by, motion regressions. ► Framewise indices of data quality and methods to remove motion artifact are proposed.
The concept of a default mode of brain function arose out of a focused need to explain the appearance of activity decreases in functional neuroimaging data when the control state was passive visual ...fixation or eyes closed resting. The problem was particularly compelling because these activity decreases were remarkably consistent across a wide variety of task conditions. Using PET, we determined that these activity decreases did not arise from activations in the resting state. Hence, their presence implied the existence of a
default mode. While the unique constellation of brain areas provoking this analysis has come to be known as the
default system, all areas of the brain have a high level of organized default functional activity. Most critically, this work has called attention to the importance of
intrinsic functional activity in assessing brain behavior relationships.
Lag threads organize the brain’s intrinsic activity Mitra, Anish; Snyder, Abraham Z.; Blazey, Tyler ...
Proceedings of the National Academy of Sciences - PNAS,
04/2015, Letnik:
112, Številka:
17
Journal Article
Recenzirano
Odprti dostop
It has been widely reported that intrinsic brain activity, in a variety of animals including humans, is spatiotemporally structured. Specifically, propagated slow activity has been repeatedly ...demonstrated in animals. In human resting-state fMRI, spontaneous activity has been understood predominantly in terms of zero-lag temporal synchrony within widely distributed functional systems (resting-state networks). Here, we use resting-state fMRI from 1,376 normal, young adults to demonstrate that multiple, highly reproducible, temporal sequences of propagated activity, which we term “lag threads,” are present in the brain. Moreover, this propagated activity is largely unidirectional within conventionally understood resting-state networks. Modeling experiments show that resting-state networks naturally emerge as a consequence of shared patterns of propagation. An implication of these results is that common physiologic mechanisms may underlie spontaneous activity as imaged with fMRI in humans and slowly propagated activity as studied in animals.
Significance It is well known that slow intrinsic activity, as measured by resting-state fMRI in a variety of animals including humans, is organized into temporally synchronous networks. The question of whether intrinsic activity contains reproducible temporal sequences has received far less attention. We have previously shown that human resting-state fMRI contains a highly reproducible lag structure. Here, we demonstrate that this lag structure is of high dimensionality and consists of multiple highly reproducible temporal sequences, which we term “lag threads.” Moreover, we demonstrate that the well-known zero-lag temporal correlation structure of intrinsic activity emerges as a consequence of lag structure. Thus, lag threads may represent a fundamental and previously unsuspected level of organization in resting-state activity.
Deficits following stroke are classically attributed to focal damage, but recent evidence suggests a key role of distributed brain network disruption. We measured resting functional connectivity ...(FC), lesion topography, and behavior in multiple domains (attention, visual memory, verbal memory, language, motor, and visual) in a cohort of 132 stroke patients, and used machine-learning models to predict neurological impairment in individual subjects. We found that visual memory and verbal memory were better predicted by FC, whereas visual and motor impairments were better predicted by lesion topography. Attention and language deficits were well predicted by both. Next,we identified a general pattern of physiological network dysfunction consisting of decrease of interhemispheric integration and intrahemispheric segregation, which strongly related to behavioral impairment in multiple domains. Network-specific patterns of dysfunction predicted specific behavioral deficits, and loss of interhemispheric communication across a set of regions was associated with impairment across multiple behavioral domains. These results link key organizational features of brain networks to brain–behavior relationships in stroke.
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