Low frequency BOLD fluctuations during resting wakefulness and light sleep: A simultaneous EEG-fMRI study. Human Brain Mapping, 29(6), 671-682

Advanced MRI Section, LFMI, NINDS, National Institutes of Health, Bethesda, Maryland, USA.
Human Brain Mapping (Impact Factor: 5.97). 06/2008; 29(6):671-82. DOI: 10.1002/hbm.20428
Source: PubMed


Recent blood oxygenation level dependent functional MRI (BOLD fMRI) studies of the human brain have shown that in the absence of external stimuli, activity persists in the form of distinct patterns of temporally correlated signal fluctuations. In this work, we investigated the spontaneous BOLD signal fluctuations during states of reduced consciousness such as drowsiness and sleep. For this purpose, we performed BOLD fMRI on normal subjects during varying levels of consciousness, from resting wakefulness to light (non-slow wave) sleep. Depth of sleep was determined based on concurrently acquired EEG data. During light sleep, significant increases in the fluctuation level of the BOLD signal were observed in several cortical areas, among which visual cortex was the most significant. Correlations among brain regions involved with the default-mode network persisted during light sleep. These results suggest that activity in areas such as the default-mode network and primary sensory cortex, as measured from BOLD fMRI fluctuations, does not require a level of consciousness typical of wakefulness.

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Available from: Silvina Horovitz, Apr 07, 2015
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    • "On the basis of prior sleep and AVA work, we hypothesized that progression to deep sleep would be associated with a reduction in the robust AVA signatures found in sensory systems during wakeful rest. In contrast, on the basis of prior work we also expected that functional connectivity among sensory regions would largely maintain its topological structure during NREM sleep, potentially accompanied by an increase in BOLD variance (Horovitz et al., 2008; Tagliazucchi et al., 2013C). Finding such a pattern would indicate (1) that sleep is specifically linked to reduction in AVA even though it is linked to increased overall variance, and (2) that functional connectivity patterns and AVA are dissociable and therefore driven by different factors. "
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    ABSTRACT: Sleep has been shown to subtly disrupt the spatial organization of functional connectivity networks in the brain, but in a way that largely preserves the connectivity within sensory cortices. Here we evaluated the hypothesis that sleeps does impact sensory cortices, but through alteration of activity dynamics. We therefore examined the impact of sleep on hemodynamics using a method for quantifying non-random, high frequency signatures of the Blood-Oxygen-Level dependent (BOLD) signal (amplitude variance asymmetry; AVA). We found that sleep was associated with the elimination of these dynamics in a manner that is restricted to auditory, motor and visual cortices. This elimination was concurrent with increased variance of activity in these regions. Functional connectivity between regions showing AVA during wakefulness maintained a relatively consistent hierarchical structure during wakefulness and N1 and N2 sleep, despite a gradual reduction of connectivity strength as sleep progressed. Thus, sleep is related to elimination of high frequency non-random activity signatures in sensory cortices that are robust during wakefulness. The elimination of these AVA signatures conjointly with preservation of the structure of functional connectivity patterns may be linked to the need to suppress sensory inputs during sleep while still maintaining the capacity to react quickly to complex multimodal inputs.
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    • "The presence of an increase of fronto-parietal network is an important feature which allows the distinction between microsleeps and all the other levels of sleep. In fact, several neuroimaging studies have demonstrated the reduction of fronto-parietal connections, until their complete disruption, in accordance with the level of sleep depth (Horovitz et al., 2008; Sämann et al., 2011; Spoormaker et al., 2012). Network modularity (a measure of functional segregation) has been found to increase during deeper sleep stages highlighting the interruption of communication between frontal and parietal areas (Tagliazucchi et al., 2013). "
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    ABSTRACT: An episode of complete failure to respond during an attentive task accompanied by behavioural signs of sleep is called a behavioural microsleep. We proposed a combination of high-resolution EEG and an advanced method for time-varying effective connectivity estimation for reconstructing the temporal evolution of the causal relations between cortical regions when microsleeps occur during a continuous visuomotor task. We found connectivity patterns involving left-right frontal, left-right parietal, and left-frontal/right-parietal connections commencing in the interval [-500;-250] ms prior to the onset of microsleeps and disappearing at the end of the microsleeps. Our results from global graph indices derived from effective connectivity analysis have revealed EEG-based biomarkers of all stages of microsleeps (preceding, onset, pre-recovery, recovery). In particular, this raises the possibility of being able to predict microsleeps in real-world tasks and initiate a 'wake-up' intervention to avert the microsleeps and, hence, prevent injurious and even multi-fatality accidents.
    Full-text · Article · Aug 2015 · NeuroImage
    • "It is interesting that the component explaining most variance in our PCA was shared among all visual areas in our analysis, indicative of the presence of global modulations affecting the whole visual cortex at once. One candidate for such a global factor might be modulations in wakefulness; sleep is known to increase BOLD signal fluctuations (Fukunaga et al. 2006; Horovitz et al. 2008) and is common in resting-state measurements (Tagliazucchi and Laufs, 2014). Simultaneous fMRI and skin conductance measurements show a tight relationship between the skin conductance response (a measure of autonomic arousal) and brain activity in several resting-state networks (Fan et al. 2012), also suggesting global modulatory effects. "
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    ABSTRACT: The brain is continuously active, even without external input or task demands. This so-called resting-state activity exhibits a highly specific spatio-temporal organization. However, how exactly these activity patterns map onto the anatomical and functional architecture of the brain is still unclear. We addressed this question in the human visual cortex. We determined the representation of the visual field in visual cortical areas of 44 subjects using fMRI and examined resting-state correlations between these areas along the visual hierarchy, their dorsal and ventral segments, and between subregions representing foveal versus peripheral parts of the visual field. We found that retinotopically corresponding regions, particularly those representing peripheral visual fields, exhibit strong correlations. V1 displayed strong internal correlations between its dorsal and ventral segments and the highest correlation with LGN compared with other visual areas. In contrast, V2 and V3 showed weaker correlations with LGN and stronger between-area correlations, as well as with V4 and hMT+. Interhemispheric correlations between homologous areas were especially strong. These correlation patterns were robust over time and only marginally altered under task conditions. These results indicate that resting-state fMRI activity closely reflects the anatomical organization of the visual cortex both with respect to retinotopy and hierarchy. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail:
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