How Old Is Your Brain? Slow-Wave Activity in Non-rapid-eye-movement Sleep as a Marker of Brain Rejuvenation After Long-Term Exercise in Mice
How Old Is Your Brain? Slow-Wave Activity in Non-rapid-eye-movement Sleep as a Marker of Brain Rejuvenation After Long-Term Exercise in Mice
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DOI：
10.3389/fnagi.2018.00233
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发表时间：
2018-08-07
影响因子：
4.8
通讯作者：
Deboer, Tom
中科院分区：
文献类型：
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作者：
Panagiotou, Maria;Papagiannopoulos, Kostas;Deboer, Tom
体力活动有益于健康。它已被证明可以改善大脑功能和认知，减轻情绪障碍的严重程度，并促进健康睡眠和健康衰老。对健康老年小鼠的睡眠进行了研究，非快速眼动睡眠 (NREM) 中的绝对慢波活动水平（SWA，脑电图功率在 0.75 至 4.0 Hz 之间）升高，表明大脑连接发生了变化。为了研究体力活动是否可以减弱这种衰老引起的影响，给三个年龄组的小鼠提供跑轮（RW）1-3个月（6个月大，n = 9；18个月大，n = 9；24个月大，n = 8），并与对照久坐小鼠（分别为n = 11、n = 8和n = 9）进行比较。在进行睡眠-觉醒记录之前两周，跑轮被移除。在不受干扰的24小时基线（BL）期间连续记录脑电图（EEG）和肌电图，并在第二天的前6小时进行睡眠剥夺。与年轻对照组相比，年轻 RW 小鼠的清醒时间增加，NREM 睡眠减少。这些影响在 18 个月和 24 个月大的小鼠中并不明显。与睡眠结构不同，我们发现 SWA 在整个年龄段都发生了变化。值得注意的是，SWA 随着年龄的增长而增加，并随着运动而减弱，在年轻的 RW 小鼠中表现出最低水平。为了利用SWA的跨年龄揭示特征，我们应用机器学习技术，发现SWA中包含了有关年龄和运动的特征信息。此外，通过聚类分析，我们可以仅根据 SWA 对不同群体进行分类和准确区分。因此，我们的研究包括三重贡献：(a) 运动对睡眠的影响在移除车轮后 2 周内持续存在，(b) 我们表明 EEG SWA 可以用作小鼠大脑年龄的生理标志，(c) 长期自愿定期的年龄匹配运动会导致更年轻的表型。
Physical activity is beneficial for health. It has been shown to improve brain functioning and cognition, reduce severity of mood disorders, as well as facilitate healthy sleep and healthy aging. Sleep has been studied in healthy aged mice and absolute slow-wave-activity levels (SWA, electroencephalogram power between 0.75 and 4.0 Hz) in non-rapid-eye-movement sleep (NREM) were elevated, suggesting changes in brain connectivity. To investigate whether physical activity can diminish this aging-induced effect, mice of three age groups were provided with a running wheel (RW) for 1-3 months (6-months-old, n = 9; 18-months-old, n = 9; 24-months-old, n = 8) and were compared with control sedentary mice (n = 11, n = 8 and n = 9 respectively). Two weeks before the sleep-wake recordings the running wheels were removed. The electroencephalogram (EEG) and electromyogram were continuously recorded during undisturbed 24 h baseline (BL) and a sleep-deprivation was conducted during the first 6 h of the second day. Increased waking and decreased NREM sleep was found in the young RW mice, compared to young controls. These effects were not evident in the 18 and 24 months old mice. Unlike sleep architecture, we found that SWA was altered throughout the whole age spectrum. Notably, SWA was increased with aging and attenuated with exercise, exhibiting the lowest levels in the young RW mice. To utilize the cross-age revealing features of SWA, we applied machine learning techniques and found that characteristic information regarding age and exercise was enclosed in SWA. In addition, with cluster analysis, we could classify and accurately distinguish the different groups based solely on their SWA. Therefore, our study comprises a three-fold contribution: (a) effects of exercise on sleep are sustained following 2 weeks after removal of the wheel, (b) we show that EEG SWA can be used as a physiological marker of brain age in the mouse, (c) long-term voluntary regular age-matched exercise leads to a younger phenotype.