Consistent resting-state networks across healthy subjects
12 Sep 2006-Proceedings of the National Academy of Sciences of the United States of America (National Academy of Sciences)-Vol. 103, Iss: 37, pp 13848-13853
TL;DR: Findings show that the baseline activity of the brain is consistent across subjects exhibiting significant temporal dynamics, with percentage BOLD signal change comparable with the signal changes found in task-related experiments.
Abstract: Functional MRI (fMRI) can be applied to study the functional connectivity of the human brain. It has been suggested that fluctuations in the blood oxygenation level-dependent (BOLD) signal during rest reflect the neuronal baseline activity of the brain, representing the state of the human brain in the absence of goal-directed neuronal action and external input, and that these slow fluctuations correspond to functionally relevant resting-state networks. Several studies on resting fMRI have been conducted, reporting an apparent similarity between the identified patterns. The spatial consistency of these resting patterns, however, has not yet been evaluated and quantified. In this study, we apply a data analysis approach called tensor probabilistic independent component analysis to resting-state fMRI data to find coherencies that are consistent across subjects and sessions. We characterize and quantify the consistency of these effects by using a bootstrapping approach, and we estimate the BOLD amplitude modulation as well as the voxel-wise cross-subject variation. The analysis found 10 patterns with potential functional relevance, consisting of regions known to be involved in motor function, visual processing, executive functioning, auditory processing, memory, and the so-called default-mode network, each with BOLD signal changes up to 3%. In general, areas with a high mean percentage BOLD signal are consistent and show the least variation around the mean. These findings show that the baseline activity of the brain is consistent across subjects exhibiting significant temporal dynamics, with percentage BOLD signal change comparable with the signal changes found in task-related experiments.
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TL;DR: Past observations are synthesized to provide strong evidence that the default network is a specific, anatomically defined brain system preferentially active when individuals are not focused on the external environment, and for understanding mental disorders including autism, schizophrenia, and Alzheimer's disease.
Abstract: Thirty years of brain imaging research has converged to define the brain’s default network—a novel and only recently appreciated brain system that participates in internal modes of cognition Here we synthesize past observations to provide strong evidence that the default network is a specific, anatomically defined brain system preferentially active when individuals are not focused on the external environment Analysis of connectional anatomy in the monkey supports the presence of an interconnected brain system Providing insight into function, the default network is active when individuals are engaged in internally focused tasks including autobiographical memory retrieval, envisioning the future, and conceiving the perspectives of others Probing the functional anatomy of the network in detail reveals that it is best understood as multiple interacting subsystems The medial temporal lobe subsystem provides information from prior experiences in the form of memories and associations that are the building blocks of mental simulation The medial prefrontal subsystem facilitates the flexible use of this information during the construction of self-relevant mental simulations These two subsystems converge on important nodes of integration including the posterior cingulate cortex The implications of these functional and anatomical observations are discussed in relation to possible adaptive roles of the default network for using past experiences to plan for the future, navigate social interactions, and maximize the utility of moments when we are not otherwise engaged by the external world We conclude by discussing the relevance of the default network for understanding mental disorders including autism, schizophrenia, and Alzheimer’s disease
8,448 citations
Cites background or methods from "Consistent resting-state networks a..."
...The default network spontaneously exhibits slow waxing and waning of activity during rest that is correlated across its distributed regions (Greicius et al. 2003, Fox et al. 2005, Fransson 2005, Damoiseaux et al. 2006, Vincent et al. 2006)....
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...Greicius and colleagues (2003, 2004) used such an analysis to map the brain’s default network (see also Fox et al. 2005, Fransson 2005, Damoiseaux et al. 2006, Vincent et al. 2006)....
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TL;DR: In this paper, the organization of networks in the human cerebrum was explored using resting-state functional connectivity MRI data from 1,000 subjects and a clustering approach was employed to identify and replicate networks of functionally coupled regions across the cerebral cortex.
Abstract: Information processing in the cerebral cortex involves interactions among distributed areas. Anatomical connectivity suggests that certain areas form local hierarchical relations such as within the visual system. Other connectivity patterns, particularly among association areas, suggest the presence of large-scale circuits without clear hierarchical relations. In this study the organization of networks in the human cerebrum was explored using resting-state functional connectivity MRI. Data from 1,000 subjects were registered using surface-based alignment. A clustering approach was employed to identify and replicate networks of functionally coupled regions across the cerebral cortex. The results revealed local networks confined to sensory and motor cortices as well as distributed networks of association regions. Within the sensory and motor cortices, functional connectivity followed topographic representations across adjacent areas. In association cortex, the connectivity patterns often showed abrupt transitions between network boundaries. Focused analyses were performed to better understand properties of network connectivity. A canonical sensory-motor pathway involving primary visual area, putative middle temporal area complex (MT+), lateral intraparietal area, and frontal eye field was analyzed to explore how interactions might arise within and between networks. Results showed that adjacent regions of the MT+ complex demonstrate differential connectivity consistent with a hierarchical pathway that spans networks. The functional connectivity of parietal and prefrontal association cortices was next explored. Distinct connectivity profiles of neighboring regions suggest they participate in distributed networks that, while showing evidence for interactions, are embedded within largely parallel, interdigitated circuits. We conclude by discussing the organization of these large-scale cerebral networks in relation to monkey anatomy and their potential evolutionary expansion in humans to support cognition.
6,284 citations
TL;DR: Recent studies examining spontaneous fluctuations in the blood oxygen level dependent (BOLD) signal of functional magnetic resonance imaging as a potentially important and revealing manifestation of spontaneous neuronal activity are reviewed.
Abstract: The majority of functional neuroscience studies have focused on the brain's response to a task or stimulus. However, the brain is very active even in the absence of explicit input or output. In this Article we review recent studies examining spontaneous fluctuations in the blood oxygen level dependent (BOLD) signal of functional magnetic resonance imaging as a potentially important and revealing manifestation of spontaneous neuronal activity. Although several challenges remain, these studies have provided insight into the intrinsic functional architecture of the brain, variability in behaviour and potential physiological correlates of neurological and psychiatric disease.
6,135 citations
TL;DR: Two distinct networks typically coactivated during functional MRI tasks are identified, anchored by dorsal anterior cingulate and orbital frontoinsular cortices with robust connectivity to subcortical and limbic structures, and an “executive-control network” that links dorsolateral frontal and parietal neocortices.
Abstract: Variations in neural circuitry, inherited or acquired, may underlie important individual differences in thought, feeling, and action patterns. Here, we used task-free connectivity analyses to isolate and characterize two distinct networks typically coactivated during functional MRI tasks. We identified a "salience network," anchored by dorsal anterior cingulate (dACC) and orbital frontoinsular cortices with robust connectivity to subcortical and limbic structures, and an "executive-control network" that links dorsolateral frontal and parietal neocortices. These intrinsic connectivity networks showed dissociable correlations with functions measured outside the scanner. Prescan anxiety ratings correlated with intrinsic functional connectivity of the dACC node of the salience network, but with no region in the executive-control network, whereas executive task performance correlated with lateral parietal nodes of the executive-control network, but with no region in the salience network. Our findings suggest that task-free analysis of intrinsic connectivity networks may help elucidate the neural architectures that support fundamental aspects of human behavior.
6,049 citations
Cites background or methods from "Consistent resting-state networks a..."
..., 2002) and ICA (Beckmann et al., 2005; Damoiseaux et al., 2006; De Luca et al., 2006), multiple labs have demonstrated separate ICNs corresponding to the sensorimotor cortex, primary auditory and visual areas, and language centers....
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...Using both ROI-based methods (Biswal et al., 1995; Cordes et al., 2000; Hampson et al., 2002) and ICA (Beckmann et al., 2005; Damoiseaux et al., 2006; De Luca et al., 2006), multiple labs have demonstrated separate ICNs corresponding to the sensorimotor cortex, primary auditory and visual areas,…...
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...…analyses (Greicius et al., 2003; Fox et al., 2005; Fransson, 2005; Vincent et al., 2006) and ICA (Greicius and Menon, 2004; Beckmann et al., 2005; Damoiseaux et al., 2006; De Luca et al., 2006) has focused on the ICN known as the default mode network: a set of consistently “deactivated” brain…...
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...The single task-positive network reported in these two papers has consistently been divided into separate networks when ICA is used (Beckmann et al., 2005; Damoiseaux et al., 2006; De Luca et al., 2006)....
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...…years, ICNs featuring typically activated brain regions (e.g., DLPFC, lateral parietal cortex, anterior cingulate, anterior insula) have also been reported with both ROI-based methods (Fox et al., 2005; Fransson, 2005) and ICA (Beckmann et al., 2005; Damoiseaux et al., 2006; De Luca et al., 2006)....
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TL;DR: It is concluded that the full repertoire of functional networks utilized by the brain in action is continuously and dynamically “active” even when at “rest.”
Abstract: Neural connections, providing the substrate for functional networks, exist whether or not they are functionally active at any given moment. However, it is not known to what extent brain regions are continuously interacting when the brain is “at rest.” In this work, we identify the major explicit activation networks by carrying out an image-based activation network analysis of thousands of separate activation maps derived from the BrainMap database of functional imaging studies, involving nearly 30,000 human subjects. Independently, we extract the major covarying networks in the resting brain, as imaged with functional magnetic resonance imaging in 36 subjects at rest. The sets of major brain networks, and their decompositions into subnetworks, show close correspondence between the independent analyses of resting and activation brain dynamics. We conclude that the full repertoire of functional networks utilized by the brain in action is continuously and dynamically “active” even when at “rest.”
4,768 citations
Cites background or methods or result from "Consistent resting-state networks a..."
...Our primary results stem from ICA decompositions of BrainMap and (independently) of the resting FMRI data, at an ICA dimensionality of 20 components; this matches a common degree of clustering/splitting previously applied via ICA to resting FMRI data (4, 7)....
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...Furthermore, several networks have been found to be spatially consistent across different subjects (7)....
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...With an ICA dimensionality of 20, the RSN components found are almost identical to those found previously with ICA on different resting FMRI datasets (4, 7)....
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...Although we may not be surprised to see temporal coherence across functional networks when at rest, we might expect such coherent fluctuations to have minimal amplitude, whereas the amplitudes seen are of the same order as found under explicit activation (7)....
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References
More filters
TL;DR: A review of the research carried out by the Analysis Group at the Oxford Centre for Functional MRI of the Brain (FMRIB) on the development of new methodologies for the analysis of both structural and functional magnetic resonance imaging data.
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Abstract: ▪ Abstract The prefrontal cortex has long been suspected to play an important role in cognitive control, in the ability to orchestrate thought and action in accordance with internal goals. Its neural basis, however, has remained a mystery. Here, we propose that cognitive control stems from the active maintenance of patterns of activity in the prefrontal cortex that represent goals and the means to achieve them. They provide bias signals to other brain structures whose net effect is to guide the flow of activity along neural pathways that establish the proper mappings between inputs, internal states, and outputs needed to perform a given task. We review neurophysiological, neurobiological, neuroimaging, and computational studies that support this theory and discuss its implications as well as further issues to be addressed
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TL;DR: A baseline state of the normal adult human brain in terms of the brain oxygen extraction fraction or OEF is identified, suggesting the existence of an organized, baseline default mode of brain function that is suspended during specific goal-directed behaviors.
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