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.

Download full-text


Available from: Silvina Horovitz, Apr 07, 2015
  • Source
    • "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). "
    [Show abstract] [Hide abstract]
    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.
    NeuroImage 08/2015; 124(Pt A). DOI:10.1016/j.neuroimage.2015.08.059 · 6.36 Impact Factor
    • "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. "
    [Show abstract] [Hide abstract]
    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: journals.permissions@oup.com.
    Cerebral Cortex 08/2015; DOI:10.1093/cercor/bhv175 · 8.67 Impact Factor
  • Source
    • "For example, degree of consciousness [Greicius et al., 2008; Horovitz et al., 2008], cognitive [Waites et al., 2005], emotional state [Harrison et al., 2008], and task [Cole et al., 2013; Krienen et al., 2014; Shirer et al., 2012] can modulate specific interregional functional connections. This variability is juxtaposed with stable functional connectivity properties that presumably reflect neuronal constraints of anatomical connectivity [Lu et al., 2011] and that persist during sleep [Horovitz et al., 2008], light sedation [Greicius et al., 2008], and even anesthesia [Vincent et al., 2007]. With these multiple biological and technical influences, drawing a clear picture of reliability of rs-fcMRI is challenging . "
    [Show abstract] [Hide abstract]
    ABSTRACT: Network properties can be estimated using functional connectivity MRI (fcMRI). However, regional variation of the fMRI signal causes systematic biases in network estimates including correlation attenuation in regions of low measurement reliability. Here we computed the spatial distribution of fcMRI reliability using longitudinal fcMRI datasets and demonstrated how pre-estimated reliability maps can correct for correlation attenuation. As a test case of reliability-based attenuation correction we estimated properties of the default network, where reliability was significantly lower than average in the medial temporal lobe and higher in the posterior medial cortex, heterogeneity that impacts estimation of the network. Accounting for this bias using attenuation correction revealed that the medial temporal lobe's contribution to the default network is typically underestimated. To render this approach useful to a greater number of datasets, we demonstrate that test-retest reliability maps derived from repeated runs within a single scanning session can be used as a surrogate for multi-session reliability mapping. Using data segments with different scan lengths between 1 and 30 min, we found that test-retest reliability of connectivity estimates increases with scan length while the spatial distribution of reliability is relatively stable even at short scan lengths. Finally, analyses of tertiary data revealed that reliability distribution is influenced by age, neuropsychiatric status and scanner type, suggesting that reliability correction may be especially important when studying between-group differences. Collectively, these results illustrate that reliability-based attenuation correction is an easily implemented strategy that mitigates certain features of fMRI signal nonuniformity. Hum Brain Mapp, 2015. © 2015 Wiley Periodicals, Inc.
    Human Brain Mapping 08/2015; DOI:10.1002/hbm.22947 · 5.97 Impact Factor
Show more