Resting brains never rest: computational insights into potential cognitive architectures
TL;DR: A new theoretical framework for RSNs is proposed that can serve as a fertile ground for empirical testing and reflects the dynamical capabilities of the brain, which emphasizes the vital interplay of time and space.
About: This article is published in Trends in Neurosciences.The article was published on 2013-05-01 and is currently open access. It has received 327 citations till now. The article focuses on the topics: Network dynamics & Resting state fMRI.
Citations
More filters
TL;DR: It is demonstrated that brain activity between multiple pairs of spatially distributed regions spontaneously fluctuates in and out of correlation over time in a globally coordinated manner, giving rise to sporadic intervals during which information can be efficiently exchanged between neuronal populations.
Abstract: Neuronal dynamics display a complex spatiotemporal structure involving the precise, context-dependent coordination of activation patterns across a large number of spatially distributed regions. Functional magnetic resonance imaging (fMRI) has played a central role in demonstrating the nontrivial spatial and topological structure of these interactions, but thus far has been limited in its capacity to study their temporal evolution. Here, using high-resolution resting-state fMRI data obtained from the Human Connectome Project, we mapped time-resolved functional connectivity across the entire brain at a subsecond resolution with the aim of understanding how nonstationary fluctuations in pairwise interactions between regions relate to large-scale topological properties of the human brain. We report evidence for a consistent set of functional connections that show pronounced fluctuations in their strength over time. The most dynamic connections are intermodular, linking elements from topologically separable subsystems, and localize to known hubs of default mode and fronto-parietal systems. We found that spatially distributed regions spontaneously increased, for brief intervals, the efficiency with which they can transfer information, producing temporary, globally efficient network states. Our findings suggest that brain dynamics give rise to variations in complex network properties over time, possibly achieving a balance between efficient information-processing and metabolic expenditure.
699 citations
Cites background from "Resting brains never rest: computat..."
...We hypothesize that these “transition epochs” mark changeover points between distinct metastates (33, 50)....
[...]
...Evidence for this hypothesis is provided by the coordinated fluctuations in network measures, such as hub centrality (31), that have been observed in simulated rsfMRI data (32, 33)....
[...]
TL;DR: These results reconcile theories of consciousness with observations of long-range correlation in the anesthetized brain and show that a rich functional dynamics might constitute a signature of consciousness, with potential clinical implications for the detection of awareness in anesthesia and brain-lesioned patients.
Abstract: At rest, the brain is traversed by spontaneous functional connectivity patterns. Two hypotheses have been proposed for their origins: they may reflect a continuous stream of ongoing cognitive processes as well as random fluctuations shaped by a fixed anatomical connectivity matrix. Here we show that both sources contribute to the shaping of resting-state networks, yet with distinct contributions during consciousness and anesthesia. We measured dynamical functional connectivity with functional MRI during the resting state in awake and anesthetized monkeys. Under anesthesia, the more frequent functional connectivity patterns inherit the structure of anatomical connectivity, exhibit fewer small-world properties, and lack negative correlations. Conversely, wakefulness is characterized by the sequential exploration of a richer repertoire of functional configurations, often dissimilar to anatomical structure, and comprising positive and negative correlations among brain regions. These results reconcile theories of consciousness with observations of long-range correlation in the anesthetized brain and show that a rich functional dynamics might constitute a signature of consciousness, with potential clinical implications for the detection of awareness in anesthesia and brain-lesioned patients.
553 citations
TL;DR: The brain regulates information flow by balancing the segregation and integration of incoming stimuli to facilitate flexible cognition and behaviour and recent whole-brain computational modelling approaches have enabled us to start assessing the effect of input perturbations on brain dynamics in silico.
Abstract: The brain regulates information flow by balancing the segregation and integration of incoming stimuli to facilitate flexible cognition and behaviour. The topological features of brain networks--in particular, network communities and hubs--support this segregation and integration but do not provide information about how external inputs are processed dynamically (that is, over time). Experiments in which the consequences of selective inputs on brain activity are controlled and traced with great precision could provide such information. However, such strategies have thus far had limited success. By contrast, recent whole-brain computational modelling approaches have enabled us to start assessing the effect of input perturbations on brain dynamics in silico.
503 citations
TL;DR: It is demonstrated that a slight enhancement of the non-linearity of the network nodes is sufficient to broaden the repertoire of possible network behaviors, leading to modes of fluctuations, reminiscent of some of the most frequently observed Resting State Networks.
479 citations
Cites background from "Resting brains never rest: computat..."
...Published by Elsevier Inc a b s t r a c t a r t i c l e i n f o...
[...]
TL;DR: The concepts of criticality and universality are discussed when applied to biological systems and it is suggested that in some cases these systems can extract functional advantages close to criticality.
Abstract: Close to a transition between different phases a substance can show universal behavior that is independent of the microscopic details and is characterized by power law correlations and critical exponents. In this Colloquium the concepts of criticality and universality are discussed when applied to biological systems and suggest that in some cases these systems can extract functional advantages close to criticality.
430 citations
Cites background from "Resting brains never rest: computat..."
...Understanding the genesis and functionality of spontaneous cortical activity – which accounts for about 20% of the total oxygen consumption of a person at rest– is key to shedding light onto how the cortex processes information and computes (Arieli et al., 1996; Deco et al., 2011, 2013a; He, 2014)....
[...]
References
More filters
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.
Abstract: A baseline or control state is fundamental to the understanding of most complex systems. Defining a baseline state in the human brain, arguably our most complex system, poses a particular challenge. Many suspect that left unconstrained, its activity will vary unpredictably. Despite this prediction we identify a baseline state of the normal adult human brain in terms of the brain oxygen extraction fraction or OEF. The OEF is defined as the ratio of oxygen used by the brain to oxygen delivered by flowing blood and is remarkably uniform in the awake but resting state (e.g., lying quietly with eyes closed). Local deviations in the OEF represent the physiological basis of signals of changes in neuronal activity obtained with functional MRI during a wide variety of human behaviors. We used quantitative metabolic and circulatory measurements from positron-emission tomography to obtain the OEF regionally throughout the brain. Areas of activation were conspicuous by their absence. All significant deviations from the mean hemisphere OEF were increases, signifying deactivations, and resided almost exclusively in the visual system. Defining the baseline state of an area in this manner attaches meaning to a group of areas that consistently exhibit decreases from this baseline, during a wide variety of goal-directed behaviors monitored with positron-emission tomography and functional MRI. These decreases suggest the existence of an organized, baseline default mode of brain function that is suspended during specific goal-directed behaviors.
10,708 citations
TL;DR: It is concluded that correlation of low frequency fluctuations, which may arise from fluctuations in blood oxygenation or flow, is a manifestation of functional connectivity of the brain.
Abstract: An MRI time course of 512 echo-planar images (EPI) in resting human brain obtained every 250 ms reveals fluctuations in signal intensity in each pixel that have a physiologic origin. Regions of the sensorimotor cortex that were activated secondary to hand movement were identified using functional MRI methodology (FMRI). Time courses of low frequency (< 0.1 Hz) fluctuations in resting brain were observed to have a high degree of temporal correlation (P < 10(-3)) within these regions and also with time courses in several other regions that can be associated with motor function. It is concluded that correlation of low frequency fluctuations, which may arise from fluctuations in blood oxygenation or flow, is a manifestation of functional connectivity of the brain.
8,766 citations
TL;DR: This study constitutes, to the knowledge, the first resting-state connectivity analysis of the default mode and provides the most compelling evidence to date for the existence of a cohesive default mode network.
Abstract: Functional imaging studies have shown that certain brain regions, including posterior cingulate cortex (PCC) and ventral anterior cingulate cortex (vACC), consistently show greater activity during resting states than during cognitive tasks. This finding led to the hypothesis that these regions constitute a network supporting a default mode of brain function. In this study, we investigate three questions pertaining to this hypothesis: Does such a resting-state network exist in the human brain? Is it modulated during simple sensory processing? How is it modulated during cognitive processing? To address these questions, we defined PCC and vACC regions that showed decreased activity during a cognitive (working memory) task, then examined their functional connectivity during rest. PCC was strongly coupled with vACC and several other brain regions implicated in the default mode network. Next, we examined the functional connectivity of PCC and vACC during a visual processing task and show that the resultant connectivity maps are virtually identical to those obtained during rest. Last, we defined three lateral prefrontal regions showing increased activity during the cognitive task and examined their resting-state connectivity. We report significant inverse correlations among all three lateral prefrontal regions and PCC, suggesting a mechanism for attenuation of default mode network activity during cognitive processing. This study constitutes, to our knowledge, the first resting-state connectivity analysis of the default mode and provides the most compelling evidence to date for the existence of a cohesive default mode network. Our findings also provide insight into how this network is modulated by task demands and what functions it might subserve.
6,025 citations
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.
4,135 citations
TL;DR: The spatial and topological centrality of the core within cortex suggests an important role in functional integration and a substantial correspondence between structural connectivity and resting-state functional connectivity measured in the same participants.
Abstract: Structurally segregated and functionally specialized regions of the human cerebral cortex are interconnected by a dense network of cortico-cortical axonal pathways. By using diffusion spectrum imaging, we noninvasively mapped these pathways within and across cortical hemispheres in individual human participants. An analysis of the resulting large-scale structural brain networks reveals a structural core within posterior medial and parietal cerebral cortex, as well as several distinct temporal and frontal modules. Brain regions within the structural core share high degree, strength, and betweenness centrality, and they constitute connector hubs that link all major structural modules. The structural core contains brain regions that form the posterior components of the human default network. Looking both within and outside of core regions, we observed a substantial correspondence between structural connectivity and resting-state functional connectivity measured in the same participants. The spatial and topological centrality of the core within cortex suggests an important role in functional integration.
4,035 citations