Schabus M, ng-Vu TT, Albouy G, Balteau E, Boly M, Carrier J et al. Hemodynamic cerebral correlates of sleep spindles during human non-rapid eye movement sleep. Proc Natl Acad Sci USA 104: 13164-13169

Cyclotron Research Centre, University of Liège, B-4000 Liège, and Department of Psychiatry, Centre Hospitalier Universitaire de Liège, Belgium.
Proceedings of the National Academy of Sciences (Impact Factor: 9.67). 09/2007; 104(32):13164-9. DOI: 10.1073/pnas.0703084104
Source: PubMed


In humans, some evidence suggests that there are two different types of spindles during sleep, which differ by their scalp topography and possibly some aspects of their regulation. To test for the existence of two different spindle types, we characterized the activity associated with slow (11-13 Hz) and fast (13-15 Hz) spindles, identified as discrete events during non-rapid eye movement sleep, in non-sleep-deprived human volunteers, using simultaneous electroencephalography and functional MRI. An activation pattern common to both spindle types involved the thalami, paralimbic areas (anterior cingulate and insular cortices), and superior temporal gyri. No thalamic difference was detected in the direct comparison between slow and fast spindles although some thalamic areas were preferentially activated in relation to either spindle type. Beyond the common activation pattern, the increases in cortical activity differed significantly between the two spindle types. Slow spindles were associated with increased activity in the superior frontal gyrus. In contrast, fast spindles recruited a set of cortical regions involved in sensorimotor processing, as well as the mesial frontal cortex and hippocampus. The recruitment of partially segregated cortical networks for slow and fast spindles further supports the existence of two spindle types during human non-rapid eye movement sleep, with potentially different functional significance.

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Available from: Thien Thanh Dang-Vu, Oct 05, 2015
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    • "Topographic analysis of spectral power in this band demonstrated no significant differences between conditions (Figure 3). Topographic data demonstrated these faster spindles were more common in central midline derivations for both conditions, consistent with prior literature (Figure 3) (Andrillon et al., 2011; Peter-Derex et al., 2012; Schabus et al., 2007). Notably, topographic analysis also demonstrated a decrease in spindle density and a concurrent increase in spindle amplitude in frontal and central midline derivations in TMZ relative to PLC (Figure 3). "
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    ABSTRACT: Benzodiazepines are commonly used medications that alter sleep spindles during non-rapid eye movement (NREM) sleep, however the topographic changes to these functionally significant waveforms have yet to be fully elucidated. This study utilized high-density electroencephalography (hdEEG) to investigate topographic changes in sleep spindles and spindle-range activity caused by temazepam during NREM sleep in 18 healthy adults. After an accommodation night, sleep for all participants was recorded on two separate nights after taking either placebo or oral temazepam 15mg. Sleep was monitored using 256-channel hdEEG. Spectral analysis and spindle waveform detection of sleep EEG data were performed for each participant night. Global and topographic data were subsequently compared between temazepam and placebo conditions. Temazepam was associated with significant increases in spectral power from 10.33 to 13.83Hz. Within this frequency band, temazepam broadly increased sleep spindle duration, and topographically increased spindle amplitude and density in frontal and central-posterior regions, respectively. Higher frequency sleep spindles demonstrated increased spindle amplitude and a paradoxical decrease in spindle density in frontal and centroparietal regions. Further analysis demonstrated temazepam both slowed the average frequency of spindle waveforms and increased the relative proportion of spindles at peak frequencies in frontal and centroparietal regions. These findings suggest that benzodiazepines have diverse effects on sleep spindles that vary by frequency and cortical topography. Further research that explores the relationships between topographic and frequency-dependent changes in pharmacologically-induced sleep spindles and the functional effects of these waveforms is indicated. Copyright © 2015 Elsevier B.V. and ECNP. All rights reserved.
    European neuropsychopharmacology: the journal of the European College of Neuropsychopharmacology 07/2015; DOI:10.1016/j.euroneuro.2015.06.005 · 4.37 Impact Factor
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    • "Four spindle characteristics were calculated; these were density (number of spindles/min); amplitude (peak-to-peak difference in voltage, expressed in μV); duration (s), and frequency (number of cycles/s, in Hz). The same procedure was followed for detecting fast spindles, using a band pass filter of 13–15 Hz (Schabus et al., 2007; Gruber et al., 2013). "
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    ABSTRACT: Sleep spindles are frequently studied for their relationship with state and trait cognitive variables, and they are thought to play an important role in sleep-related memory consolidation. Due to their frequent occurrence in NREM sleep, the detection of sleep spindles is only feasible using automatic algorithms, of which a large number is available. We compared subject averages of the spindle parameters computed by a fixed frequency (FixF) (11–13 Hz for slow spindles, 13–15 Hz for fast spindles) automatic detection algorithm and the individual adjustment method (IAM), which uses individual frequency bands for sleep spindle detection. Fast spindle duration and amplitude are strongly correlated in the two algorithms, but there is little overlap in fast spindle density and slow spindle parameters in general. The agreement between fixed and manually determined sleep spindle frequencies is limited, especially in case of slow spindles. This is the most likely reason for the poor agreement between the two detection methods in case of slow spindle parameters. Our results suggest that while various algorithms may reliably detect fast spindles, a more sophisticated algorithm primed to individual spindle frequencies is necessary for the detection of slow spindles as well as individual variations in the number of spindles in general.
    Frontiers in Human Neuroscience 02/2015; 9. DOI:10.3389/fnhum.2015.00052 · 2.99 Impact Factor
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    • "Spindles are defined as waxing-and-waning electroencephalography (EEG) waves oscillating at a frequency of 11–16 Hz and predominant over central EEG derivations; spindles characterize stage N2 of non-rapid-eye-movement (NREM) sleep but can also be found during stage N3 (De Gennaro et al., 2000; Iber et al., 2007). Animal and human studies converge to demonstrate that sleep spindles are generated through the interplay between specific populations of thalamic (particularly thalamic reticular) and cortical neurons (Steriade and McCarley, 2005; Schabus et al., 2007). While the density of sleep spindles varies considerably between individuals, it has been shown that spindle density remains remarkably stable within a same individual across different nights, thus constituting an individual trait (Gaillard and Blois, 1981; De Gennaro et al., 2005). "
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    ABSTRACT: Predisposing factors place certain individuals at higher risk for insomnia, especially in the presence of precipitating conditions such as stressful life events. Sleep spindles have been shown to play an important role in the preservation of sleep continuity. Lower spindle density might thus constitute an objective predisposing factor for sleep reactivity to stress. The aim of this study was therefore to evaluate the relationship between baseline sleep spindle density and the prospective change in insomnia symptoms in response to a standardized academic stressor. Twelve healthy students had a polysomnography recording during a period of lower stress at the beginning of the academic semester, along with an assessment of insomnia complaints using the insomnia severity index (ISI). They completed a second ISI assessment at the end of the semester, a period coinciding with the week prior to final examinations and thus higher stress. Spindle density, amplitude, duration, and frequency, as well as sigma power were computed from C4-O2 electroencephalography derivation during stages N2-N3 of non-rapid-eye-movement (NREM) sleep, across the whole night and for each NREM sleep period. To test for the relationship between spindle density and changes in insomnia symptoms in response to academic stress, spindle measurements at baseline were correlated with changes in ISI across the academic semester. Spindle density (as well as spindle amplitude and sigma power), particularly during the first NREM sleep period, negatively correlated with changes in ISI (p < 0.05). Lower spindle activity, especially at the beginning of the night, prospectively predicted larger increases in insomnia symptoms in response to stress. This result indicates that individual differences in sleep spindle activity contribute to the differential vulnerability to sleep disturbances in the face of precipitating factors.
    Frontiers in Human Neuroscience 02/2015; 9:68. DOI:10.3389/fnhum.2015.00068 · 2.99 Impact Factor
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