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  • 1
    In: Brain, Oxford University Press (OUP), Vol. 142, No. 6 ( 2019-06-01), p. 1783-1796
    Type of Medium: Online Resource
    ISSN: 0006-8950 , 1460-2156
    RVK:
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2019
    detail.hit.zdb_id: 1474117-9
    detail.hit.zdb_id: 80072-7
    SSG: 12
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  • 2
    In: Sleep, Oxford University Press (OUP), Vol. 43, No. 8 ( 2020-08-12)
    Abstract: Suggested neural correlates of insomnia disorder have been hard to replicate. Even the most consistent finding, altered white matter microstructure in the anterior limb of the internal capsule, is based on handful studies. The urge for replicable targets to understand the underlying mechanisms of insomnia made us study white matter fractional anisotropy (FA) across three samples of cases and controls. Methods 3-Tesla MRI diffusion tensor imaging data of three independent samples were combined for analysis, resulting in n = 137 participants, of whom 73 were diagnosed with insomnia disorder and 64 were matched controls without sleep complaints. Insomnia severity was measured with the Insomnia Severity Index (ISI). White matter microstructure was assessed with FA. White matter tracts were skeletonized and analyzed using tract-based spatial statistics. We performed a region-of-interest analysis using linear mixed-effect models to evaluate case–control differences in internal capsule FA as well as associations between internal capsule FA and insomnia severity. Results FA in the right limb of the anterior internal capsule was lower in insomnia disorder than in controls (β = −9.76e−3; SE = 4.17e−3, p = .034). In the entire sample, a higher ISI score was associated with a lower FA value of the right internal capsule (β = −8.05e− 4 FA/ISI point, SE = 2.60e− 4, p = .008). Ancillary whole brain voxel-wise analyses showed no significant group difference or association with insomnia severity after correction for multiple comparisons. Conclusions The internal capsule shows small but consistent insomnia-related alterations. The findings support a circuit-based approach to underlying mechanisms since this tract connects many brain areas previously implicated in insomnia.
    Type of Medium: Online Resource
    ISSN: 0161-8105 , 1550-9109
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2020
    detail.hit.zdb_id: 424441-2
    detail.hit.zdb_id: 2056761-3
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  • 3
    In: Sleep, Oxford University Press (OUP), Vol. 43, No. 11 ( 2020-11-12)
    Abstract: Actigraphy is a useful tool for estimating sleep, but less accurately distinguishes sleep and wakefulness in patients with insomnia disorder (ID) than in good sleepers. Specific algorithm parameter settings have been suggested to improve the accuracy of actigraphic estimates of sleep onset or nocturnal sleep and wakefulness in ID. However, a direct comparison of how different algorithm parameter settings affect actigraphic estimates of sleep features has been lacking. This study aimed to define the optimal algorithm parameter settings for actigraphic estimates of polysomnographic sleep features in people suffering from ID and matched good sleepers. Methods We simultaneously recorded actigraphy and polysomnography without sleep diaries during 210 laboratory nights of people with ID (n = 58) and matched controls (CTRL) without sleep complaints (n = 56). We analyzed cross-validation errors using 150 algorithm parameter configurations and Bland–Altman plots of sleep features using the optimal settings. Results Optimal sleep onset latency and total sleep time (TST) errors were lower in CTRL (8.9 ± 2.1 and 16.5 ± 2.1 min, respectively) than in ID (11.7 ± 0.8 and 29.1 ± 3.4 min). The sleep–wake algorithm, a period duration of 5 min, and a wake sensitivity threshold of 40 achieved optimal results in ID and near-optimal results in CTRL. Bland–Altman plots were nearly identical for ID and controls for all common all-night sleep features except for TST. Conclusion This systematic evaluation shows that actigraphic sleep feature estimation can be improved by using uncommon parameter settings. One specific parameter setting provides (near-)optimal estimation of sleep onset and nocturnal sleep across ID and controls.
    Type of Medium: Online Resource
    ISSN: 0161-8105 , 1550-9109
    Language: English
    Publisher: Oxford University Press (OUP)
    Publication Date: 2020
    detail.hit.zdb_id: 424441-2
    detail.hit.zdb_id: 2056761-3
    Location Call Number Limitation Availability
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