The traditional approach to studying brain function is to measure physiological responses to controlled sensory, motor and cognitive paradigms. However, most of the brain's energy consumption is devoted to ongoing metabolic activity not clearly associated with any particular stimulus or behaviour. Functional magnetic resonance imaging studies in humans aimed at understanding this ongoing activity have shown that spontaneous fluctuations of the blood-oxygen-level-dependent signal occur continuously in the resting state. In humans, these fluctuations are temporally coherent within widely distributed cortical systems that recapitulate the functional architecture of responses evoked by experimentally administered tasks. Here, we show that the same phenomenon is present in anaesthetized monkeys even at anaesthetic levels known to induce profound loss of consciousness. We specifically demonstrate coherent spontaneous fluctuations within three well known systems (oculomotor, somatomotor and visual) and the 'default' system, a set of brain regions thought by some to support uniquely human capabilities. Our results indicate that coherent system fluctuations probably reflect an evolutionarily conserved aspect of brain functional organization that transcends levels of consciousness.

SUMMARY Scale-free dynamics, with a power spectrum following P ∝ f-β, are an intrinsic feature of many complex processes in nature. In neural systems, scale-free activity is often neglected in electrophysiological research. Here, we investigate scale-free dynamics in human brain and show that it contains extensive nested frequencies, with the phase of lower frequencies modulating the amplitude of higher frequencies in an upward progression across the frequency spectrum. The functional significance of scale-free brain activity is indicated by task performance modulation and regional variation, with β being larger in default network and visual cortex and smaller in hippocampus and cerebellum. The precise patterns of nested frequencies in the brain differ from other scale-free dynamics in nature, such as earth seismic waves and stock market fluctuations, suggesting system-specific generative mechanisms. Our findings reveal robust temporal structures and behavioral significance of scale-free brain activity and should motivate future study on its physiological mechanisms and cognitive implications.

Spontaneous fluctuations in the blood-oxygen-level-dependent (BOLD) signals demonstrate consistent temporal correlations within large-scale brain networks associated with different functions. The neurophysiological correlates of this phenomenon remain elusive. Here, we show in humans that the slow cortical potentials recorded by electrocorticography demonstrate a correlation structure similar to that of spontaneous BOLD fluctuations across wakefulness, slow-wave sleep, and rapid-eye-movement sleep. Gamma frequency power also showed a similar correlation structure but only during wakefulness and rapid-eye-movement sleep. Our results provide an important bridge between the largescale brain networks readily revealed by spontaneous BOLD signals and their underlying neurophysiology.electrocorticography ͉ fMRI ͉ functional connectivity ͉ human ͉ sleep S pontaneous slow (Ͻ0.1 Hz) fluctuations in the blood-oxygenlevel-dependent (BOLD) signals of functional magnetic resonance imaging (fMRI) appear to reflect a fundamental aspect of the brain's organization (1, 2). These fluctuations are temporally covariant within large-scale functional brain networks, such as those associated with sensorimotor (1), language (3), attention (4), and executive (5) functions as well as the ''default network'' (6). These covariant relations (i.e., correlation structures) of spontaneous BOLD signals exist during restful waking (1, 3-6), task performance (3, 7), sleep (8), and even general anesthesia (2). Furthermore, their integrity appears to be essential to normal brain function (7). However, in contrast to evoked BOLD responses (9-12), the electrophysiological basis of these spontaneous covariant BOLD fluctuations is unknown. Here, we investigated this question in five patients with intractable epilepsy undergoing evaluation with surgically implanted grids of subdural electrodes. Each patient underwent about a week of continuous videomonitored electrocorticography (ECoG) for the purpose of determining the epileptic focus before surgical resection.The present analyses were based on ECoG data recorded in three distinct arousal states: (i) extended awake periods during which patients were in bed or seated, typically watching TV, eating, or engaged in social interactions; (ii) slow-wave sleep (SWS); and (iii) rapid-eye-movement (REM) sleep. Representative ECoG data are shown in supporting information (SI) Fig. S1. Resting-state (maintaining visual fixation) BOLD fMRI was acquired in a separate session either before or after surgical intervention. Patient information and data details are included in Table S1. In what follows, we present analyses using four different strategies to compare the correlation structures of BOLD and ECoG signals. Results Correlation Structures of Spontaneous BOLD Signal and Slow CorticalPotential. In the first three analyses, we focused on the sensorimotor network, because the ECoG electrodes provided adequate coverage of the sensorimotor network in all presently studied patients but much poorer coverage of the other ...

Descent into sleep is accompanied by disengagement of the conscious brain from the external world. It follows that this process should be associated with reduced neural activity in regions of the brain known to mediate interaction with the environment. We examined blood oxygen dependent (BOLD) signal functional connectivity using conventional seed-based analyses in 3 primary sensory and 3 association networks as normal young adults transitioned from wakefulness to light sleep while lying immobile in the bore of a magnetic resonance imaging scanner. Functional connectivity was maintained in each network throughout all examined states of arousal. Indeed, correlations within the dorsal attention network modestly but significantly increased during light sleep compared to wakefulness. Moreover, our data suggest that neuronally mediated BOLD signal variance generally increases in light sleep. These results do not support the view that ongoing BOLD fluctuations primarily reflect unconstrained cognition. Rather, accumulating evidence supports the hypothesis that spontaneous BOLD fluctuations reflect processes that maintain the integrity of functional systems in the brain.default network ͉ fMRI ͉ neuroimaging ͉ non-rapid eye movement sleep T here is a physiologically distinct change in the state of the brain during sleep in comparison to wakefulness that is manifest subjectively as altered awareness and objectively as reduced responsiveness to environmental stimuli. The electrophysiological correlates of sleep are sufficiently pronounced and characteristic as to be defining (1, 2). Thus, natural sleep is characterized by a sequence of electroencephalographically defined stages that may be broadly divided into nonrapid eye movement (NREM) and rapid eye movement (REM) that cyclically alternate throughout the sleep period.Over the past decade, PET studies have shown that throughout NREM sleep cerebral blood flow and metabolism are reduced in cortical association areas (3-7), as well as in the brainstem, thalamus, basal ganglia, and basal forebrain (3, 4, 7). NREM sleep is accompanied by reduced responsiveness to stimuli in regions involved in executive function, attention, and perceptual processing (5,7,8). The deepest NREM sleep states are characterized by low frequency oscillations in the EEG during which cognition is thought to be greatly reduced (9-13). During REM, cerebral blood flow and metabolism remain decreased in prefrontal and parietal regions but are increased in paralimbic areas, anterior cingulate, and thalamus (3,7,14), a pattern consistent with the emotionality and reduced logicality notable in during dreaming (7,15,16). REM sleep is also marked by atonia in skeletal muscles, reducing the ability to overtly respond to external stimulation. Thus, the transitions from wakefulness to successively deeper stages of NREM and then REM sleep progressively disengage the self from the environment.It is now well-established that slow (Ͻ0.1 Hz) spontaneous fluctuations of the blood oxygen dependent (BOLD) signal show ph...

See Mander et al. (doi:10.1093/awx174) for a scientific commentary on this article.Sleep deprivation increases amyloid-β, suggesting that chronically disrupted sleep may promote amyloid plaques and other downstream Alzheimer's disease pathologies including tauopathy or inflammation. To date, studies have not examined which aspect of sleep modulates amyloid-β or other Alzheimer's disease biomarkers. Seventeen healthy adults (age 35-65 years) without sleep disorders underwent 5-14 days of actigraphy, followed by slow wave activity disruption during polysomnogram, and cerebrospinal fluid collection the following morning for measurement of amyloid-β, tau, total protein, YKL-40, and hypocretin. Data were compared to an identical protocol, with a sham condition during polysomnogram. Specific disruption of slow wave activity correlated with an increase in amyloid-β40 (r = 0.610, P = 0.009). This effect was specific for slow wave activity, and not for sleep duration or efficiency. This effect was also specific to amyloid-β, and not total protein, tau, YKL-40, or hypocretin. Additionally, worse home sleep quality, as measured by sleep efficiency by actigraphy in the six nights preceding lumbar punctures, was associated with higher tau (r = 0.543, P = 0.045). Slow wave activity disruption increases amyloid-β levels acutely, and poorer sleep quality over several days increases tau. These effects are specific to neuronally-derived proteins, which suggests they are likely driven by changes in neuronal activity during disrupted sleep.