Restoring the Molecular Clockwork Within the Suprachiasmatic Hypothalamus of an Otherwise Clockless Mouse Enables Circadian Phasing and Stabilization of Sleep-Wake Cycles and Reverses Memory Deficits
Journal of Neuroscience(2021)SCI 1区
Abstract
The timing and quality of sleep-wake cycles are regulated by interacting circadian and homeostatic mechanisms. Although the suprachiasmatic nucleus (SCN) is the principal clock, circadian clocks are active across the brain and the respective sleep-regulatory roles of SCN and local clocks are unclear. To determine the specific contribution(s) of the SCN, we used virally mediated genetic complementation, expressing Cryptochrome1 (Cry1) to establish circadian molecular competence in the suprachiasmatic hypothalamus of globally clockless, arrhythmic male Cry1/Cry2-null mice. Under free-running conditions, the rest/activity behavior of Cry1/Cry2-null controls expressing EGFP (SCNCon) was arrhythmic, whereas Cry1-complemented mice (SCNCry1) had coherent circadian behavior, comparable to that of Cry1,2-competent wild types (WTs). In SCNCon mice, sleep-wakefulness, assessed by electroencephalography (EEG)/electromyography (EMG), lacked circadian organization. In SCNCry1 mice, however, it matched WTs, with consolidated vigilance states [wake, rapid eye movement sleep (REMS) and non-REMS (NREMS)] and rhythms in NREMS δ power and expression of REMS within total sleep (TS). Wakefulness in SCNCon mice was more fragmented than in WTs, with more wake-NREMS-wake transitions. This disruption was reversed in SCNCry1 mice. Following sleep deprivation (SD), all mice showed a homeostatic increase in NREMS δ power, although the SCNCon mice had reduced NREMS during the inactive (light) phase of recovery. In contrast, the dynamics of homeostatic responses in the SCNCry1 mice were comparable to WTs. Finally, SCNCon mice exhibited poor sleep-dependent memory but this was corrected in SCNCry1mice. In clockless mice, circadian molecular competence focused solely on the SCN rescued the architecture and consolidation of sleep-wake and sleep-dependent memory, highlighting its dominant role in timing sleep.SIGNIFICANCE STATEMENT The circadian timing system regulates sleep-wake cycles. The hypothalamic suprachiasmatic nucleus (SCN) is the principal circadian clock, but the presence of multiple local brain and peripheral clocks mean the respective roles of SCN and other clocks in regulating sleep are unclear. We therefore used virally mediated genetic complementation to restore molecular circadian functions in the suprachiasmatic hypothalamus, focusing on the SCN, in otherwise genetically clockless, arrhythmic mice. This initiated circadian activity-rest cycles, and circadian sleep-wake cycles, circadian patterning to the intensity of non-rapid eye movement sleep (NREMS) and circadian control of REMS as a proportion of total sleep (TS). Consolidation of sleep-wake established normal dynamics of sleep homeostasis and enhanced sleep-dependent memory. Thus, the suprachiasmatic hypothalamus, alone, can direct circadian regulation of sleep-wake.
MoreTranslated text
Key words
circadian,clock,cryptochrome,hippocampus,NREM sleep,sleep homeostasis
求助PDF
上传PDF
View via Publisher
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
- Pretraining has recently greatly promoted the development of natural language processing (NLP)
- We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
- We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
- The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
- Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example

Generate MRT to find the research sequence of this paper
Related Papers
2008
被引用127 | 浏览
2003
被引用1392 | 浏览
2004
被引用126 | 浏览
2005
被引用242 | 浏览
2001
被引用1510 | 浏览
2010
被引用36 | 浏览
2002
被引用3345 | 浏览
2013
被引用64 | 浏览
2013
被引用79 | 浏览
2015
被引用211 | 浏览
2019
被引用51 | 浏览
2020
被引用42 | 浏览
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper