Beth Israel Deaconess Medical Center, Boston, MA, USA.
Harvard Medical School, Boston, MA, USA.
Nat Hum Behav. 2021 Jan;5(1):123-145. doi: 10.1038/s41562-020-00964-y. Epub 2020 Nov 16.
We sought to determine which facets of sleep neurophysiology were most strongly linked to cognitive performance in 3,819 older adults from two independent cohorts, using whole-night electroencephalography. From over 150 objective sleep metrics, we identified 23 that predicted cognitive performance, and processing speed in particular, with effects that were broadly independent of gross changes in sleep quality and quantity. These metrics included rapid eye movement duration, features of the electroencephalography power spectra derived from multivariate analysis, and spindle and slow oscillation morphology and coupling. These metrics were further embedded within broader associative networks linking sleep with aging and cardiometabolic disease: individuals who, compared with similarly aged peers, had better cognitive performance tended to have profiles of sleep metrics more often seen in younger, healthier individuals. Taken together, our results point to multiple facets of sleep neurophysiology that track coherently with underlying, age-dependent determinants of cognitive and physical health trajectories in older adults.
我们试图通过全夜脑电记录来确定在两个独立队列的 3819 名老年人中,哪些睡眠神经生理学特征与认知表现最密切相关,涉及超过 150 项客观睡眠指标,我们确定了 23 项指标可以预测认知表现,特别是处理速度,这些影响基本上独立于睡眠质量和数量的总体变化。这些指标包括快速眼动持续时间、多变量分析得出的脑电图频谱特征、纺锤波和慢波形态和耦合。这些指标进一步嵌入到将睡眠与衰老和心血管代谢疾病联系起来的更广泛的关联网络中:与同龄者相比,认知表现更好的个体往往具有更常见于年轻、健康个体的睡眠指标特征。总的来说,我们的研究结果表明,睡眠神经生理学的多个方面与老年人认知和身体健康轨迹的潜在、年龄相关决定因素密切相关。