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  The influence of circadian rhythm and sleep on brain microstructure

Brodt, S., Schönauer, M., Erb, M., Scheffler, K., & Gais, S. (2019). The influence of circadian rhythm and sleep on brain microstructure. Poster presented at 25th Annual Meeting of the Organization for Human Brain Mapping (OHBM 2019), Roma, Italy.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0003-C5D0-3 Version Permalink: http://hdl.handle.net/21.11116/0000-0004-3FF3-4
Genre: Poster

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Brodt, S, Author              
Schönauer, M, Author
Erb, M1, 2, Author              
Scheffler, K1, 2, Author              
Gais, S, Author
Affiliations:
1Department High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497796              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794              

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 Abstract: Introduction: Circadian rhythms are a governing principle of many biological processes. Sleep, which is inherently linked to the circadian rhythm, is an important process regulating brain homeostasis, e.g. by metabolite clearance (Xie 2013) and by synaptic downscaling, which regulates plasticity (Tononi 2014). Indices derived from diffusion-weighted MRI are sensitive to changes in tissue microstructure, and specifically mean diffusivity (MD) has been shown to reflect plasticity-dependent processes occurring after learning (Sagi 2012, Brodt 2018). Here, we aimed to assess circadian rhythmicity of and elaborate on the role of sleep for brain diffusivity, particularly in relation to learning. Methods: Diffusion-weighted MR images of healthy volunteers were acquired at three different time points (0 h, 3 h and 13 h). Participants in the wake group (n=18) were imaged twice in the morning, allowed to leave the lab during the day and returned in the evening for the third scan. The sleep group (n=17) was scanned twice in the evening, went home to sleep with a mobile EEG device and returned the following morning. Every participant completed two conditions: In the learning condition, they underwent an object-location learning task between the first and the second scan. During the learning task, functional activity was recorded via fMRI. In the control condition, they also spent this period in the laboratory, but without a learning task. Results: Both groups showed similar overall circadian effects on MD in both conditions. Diffusivity of the total brain tissue (grey and white matter) was lower in the evening than in the morning, reflecting a denser brain tissue in the evening. Correspondingly, there was a significant negative correlation between MD and time spent awake. The wake group showed a linear decrease in overall MD over the three time points for both conditions. The sleep group's MD pattern showed a significant quadratic trend, displaying a decrease in MD from the first to the second time point and an increase occurring over sleep. The correlation between the MD change before sleep and the MD change over the sleep period, calculated over all gray and white matter voxels, revealed that voxels with a higher decrease before sleep also show a higher increase over following sleep. Importantly, this relationship was significantly stronger in the control condition than in the learning condition. When additionally considering learning-related functional activity, a similar whole-brain correlation indicated that voxels with higher task-related activation during learning also showed a higher sleep-related increase after learning than in the control condition. Conclusions: First, our analyses confirm an influence of the circadian rhythm on brain diffusivity, with a decrease over the day and a subsequent increase over sleep. This result demonstrates an important potential confound and should always be considered in experiments comparing MD measurements from different times of day. Second, our data support the idea of sleep as a homeostatic process, which reverts the changes in MD that accumulate over the day. Our finding could reflect the removal of excess synaptic connectivity, which is consistent with the idea of synaptic downscaling during sleep (Tononi 2014, Bernardi 2016). The results also provide a first indication that these sleep-regulated effects on brain microstructure can differ depending on whether learning occurred prior to sleep.

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 Dates: 2019-06
 Publication Status: Published online
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Title: 25th Annual Meeting of the Organization for Human Brain Mapping (OHBM 2019)
Place of Event: Roma, Italy
Start-/End Date: 2019-06-09 - 2019-06-13

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Title: 25th Annual Meeting of the Organization for Human Brain Mapping (OHBM 2019)
Source Genre: Proceedings
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Pages: - Volume / Issue: - Sequence Number: T211 Start / End Page: - Identifier: -