What are neural networks doing when the brain is at rest? It turns out that in primates, even under conditions of deep anaesthesia, some of these networks undergo highly organized patterns of activity.
Our brains use up enormous amounts of energy, even when we are daydreaming with our eyes closed and not performing any demanding mental operations1. In fact, intensive cognitive operations — arithmetic calculations, for example — increase the brain's energy consumption only minimally.
When subjects are in a resting state, spontaneous brain activity is not as chaotic as one might expect. Instead, that activity correlates systematically across anatomically and functionally connected areas that are normally used when performing tasks such as reading this article2. The significance of this correlated activity during states of rest has remained unclear. Vincent and colleagues (page 83 of this issue)3 shed light on the matter by showing that organized activity patterns in neural networks are similar across primate species, and are not tied to a conscious state of mind.
Vincent et al. used functional magnetic resonance imaging (fMRI) to investigate spontaneous fluctuations of neural activity in the monkey brain during anaesthesia. The fMRI signals are indirect measures of neural activity, and determine spatially specific changes in blood oxygenation levels across the brain (referred to as the BOLD signal). The authors chose a starting point, or 'seed' region, in the frontal cortex known as the frontal eye field, and looked at how spontaneous fluctuations of fMRI signals in this region correlated over time with signals in the rest of the brain.
The frontal eye field is part of the oculomotor system, a network of brain areas that subserves the planning and execution of eye movements, and it is well understood in both monkeys and humans4. Only a few other discrete regions in the frontal and parietal cortex showed temporally coherent correlations with the spontaneous signal fluctuations in the frontal eye field. These brain regions are known to be interconnected, and are all part of the oculomotor system. When a different seed region in the oculomotor system was chosen, the same discrete network was revealed.
How do the activations across the oculomotor network, under conditions of deep anaesthesia, compare with those observed in awake monkeys performing eye movements? Strikingly, the authors found activations in the same brain regions in monkeys trained to perform eye movements in fMRI experiments5. Thus, the same network that is used during performance of the task maintains a state of correlated activity in the resting, and even unconscious, brain.
The oculomotor system is not the only brain network that shows organized patterns of signal fluctuations in anaesthetized monkeys. Vincent et al. observed correlated signal fluctuations in two other systems — the somatosensory/motor (somatomotor) system, which is involved in movement and touch, and the visual system.
When the authors used the somatomotor cortex in one brain hemisphere as a seed region, they found that its BOLD signals correlated highly only with the somatomotor cortex in the opposite hemisphere. Interestingly, this region did not show high signal correlations with nearby frontal regions of the oculomotor system. This suggests that these correlations are network specific, and do not spread into neighbouring, but functionally distinct, regions of the cortex. In the visual system, a seed region in the primary visual cortex was chosen that represents a specific part of visual space. Remarkably, the fluctuations in BOLD signals correlated only with signals of subregions within other visual areas that represent the same part of visual space. Together, these findings show that the spontaneous signal correlations in the anaesthetized monkey are highly specific, both across functionally defined networks and within topographically defined subregions of a network.
Previous studies have shown that the main human cortical networks exhibit correlated spontaneous activity while subjects are at rest2,6,7. Vincent and colleagues provide the first evidence that such activity is neither restricted to the human brain nor tied to a conscious state. Their findings suggest that fluctuations of spontaneous activity across anatomically interconnected brain regions constitute a fundamental principle of brain organization. Such an interpretation is supported by the fact that organized patterns of brain activity are present in both humans and non-human primates.
As to the functional significance of correlated signal fluctuations, it may be that they maintain the integrity of the networks by reinforcing the synaptic connections between neurons that are essential for network operations in the awake state. Indeed, in stroke patients, the functional connectivity of a brain network has been found to break down when one of its parts is damaged8. This loss of connectivity seemed to be correlated with the patients' behavioural impairments. Thus, the new findings3 may help in understanding both normal and pathological brain function.
Vincent et al.3 also investigated a possible monkey homologue of a cortical network that thus far has been studied only in humans. This human 'default' network exhibits BOLD activations when subjects are not performing any particular task, and is thought to support uniquely human functions — for example, thinking about ourselves and others, imagining the future, and daydreaming9,10,11. The authors chose to study a seed region in the posterior cingulate cortex of the monkey brain; this brain region is anatomically similar in both species and is part of the human default network. They identified correlated activity in discrete regions of the frontal, parietal and temporal cortex, which may thus form an analogous default network in the monkey brain.
These findings challenge the view that the default network is uniquely human and is tied to human mental capabilities. But that challenge depends on the assumption that the posterior cingulate cortex is analogous in both species: despite the anatomical similarities, it is not known whether this area serves similar brain functions in the two species. Furthermore, the human default network has been defined in the awake state, whereas this possible monkey homologue was investigated under deep anaesthesia. Further investigations of this network in the monkey brain, under conditions similar to those used in the human studies, will be necessary to clarify its relation to the human default network.
Vincent and colleagues' results3 raise other fascinating issues. How many brain networks can be discovered by identifying correlations between spontaneous signals? Also, what are the physiological criteria that define such networks? Arguably, the brain regions that form a network have to be interconnected. But as Vincent et al. show, network activations extend beyond those expected simply from connections between single synapses. Furthermore, are these organized patterns of activity unique to primates? The authors' approach may prove promising in revealing similarities between brain regions in different species, especially when combined with task-induced brain activations that are related to sensory or cognitive functions.
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