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婴儿睡眠脑电图丘脑皮质连接标志物可预测婴儿晚期行为结局。

An infant sleep electroencephalographic marker of thalamocortical connectivity predicts behavioral outcome in late infancy.

机构信息

Department of Pulmonology, University Hospital Zurich, Zurich, CH; Surrey Sleep Research Centre, Faculty of Health and Medical Sciences, University of Surrey, Guildford, United Kingdom; Neuromodulation Laboratory, School of Psychology, University of Surrey, Guildford, United Kingdom.

Department of Pulmonology, University Hospital Zurich, Zurich, CH; Center of Competence Sleep & Health Zurich, University of Zurich, Zurich, CH; Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, Nijmegen, NL.

出版信息

Neuroimage. 2023 Apr 1;269:119924. doi: 10.1016/j.neuroimage.2023.119924. Epub 2023 Feb 3.

Abstract

Infancy represents a critical period during which thalamocortical brain connections develop and mature. Deviations in the maturation of thalamocortical connectivity are linked to neurodevelopmental disorders. There is a lack of early biomarkers to detect and localize neuromaturational deviations, which can be overcome with mapping through high-density electroencephalography (hdEEG) assessed in sleep. Specifically, slow waves and spindles in non-rapid eye movement (NREM) sleep are generated by the thalamocortical system, and their characteristics, slow wave slope and spindle density, are closely related to neuroplasticity and learning. Spindles are often subdivided into slow (11.0-13.0 Hz) and fast (13.5-16.0 Hz) frequencies, for which not only different functions have been proposed, but for which also distinctive developmental trajectories have been reported across the first years of life. Recent studies further suggest that information processing during sleep underlying sleep-dependent learning is promoted by the temporal coupling of slow waves and spindles, yet slow wave-spindle coupling remains unexplored in infancy. Thus, we evaluated three potential biomarkers: 1) slow wave slope, 2) spindle density, and 3) the temporal coupling of slow waves with spindles. We use hdEEG to first examine the occurrence and spatial distribution of these three EEG features in healthy infants and second to evaluate a predictive relationship with later behavioral outcomes. We report four key findings: First, infants' EEG features appear locally: slow wave slope is maximal in occipital and frontal areas, whereas slow and fast spindle density is most pronounced frontocentrally. Second, slow waves and spindles are temporally coupled in infancy, with maximal coupling strength in the occipital areas of the brain. Third, slow wave slope, fast spindle density, and slow wave-spindle coupling are not associated with concurrent behavioral status (6 months). Fourth, fast spindle density in central and frontocentral regions at age 6 months predicts overall developmental status at age 12 months, and motor skills at age 12 and 24 months. Neither slow wave slope nor slow wave-spindle coupling predict later behavioral development. We further identified spindle frequency as a determinant of slow and fast spindle density, which accordingly, also predicts motor skills at 24 months. Our results propose fast spindle density, or alternatively spindle frequency, as early EEG biomarker for identifying thalamocortical maturation, which can potentially be used for early diagnosis of neurodevelopmental disorders in infants. These findings are in support of a role of sleep spindles in sensorimotor microcircuitry development. A crucial next step will be to evaluate whether early therapeutic interventions may be effective to reverse deviations in identified individuals at risk.

摘要

婴儿期是大脑丘脑皮质连接发育和成熟的关键时期。丘脑皮质连接成熟的偏差与神经发育障碍有关。目前缺乏早期生物标志物来检测和定位神经成熟偏差,可以通过睡眠中评估的高密度脑电图(hdEEG)进行映射来克服。具体来说,非快速眼动(NREM)睡眠中的慢波和纺锤波由丘脑皮质系统产生,其特征,即慢波斜率和纺锤波密度,与神经可塑性和学习密切相关。纺锤波通常细分为慢(11.0-13.0 Hz)和快(13.5-16.0 Hz)频率,不仅提出了不同的功能,而且据报道在生命的头几年也有不同的发展轨迹。最近的研究还表明,睡眠中依赖于睡眠的学习的信息处理是由慢波和纺锤波的时间耦合促进的,然而,慢波-纺锤波耦合在婴儿期仍未得到探索。因此,我们评估了三个潜在的生物标志物:1)慢波斜率,2)纺锤波密度,3)慢波与纺锤波的时间耦合。我们使用 hdEEG 首先检查这三个 EEG 特征在健康婴儿中的发生和空间分布,其次评估与后期行为结果的预测关系。我们报告了四个关键发现:第一,婴儿的 EEG 特征在局部出现:在枕部和额部区域,慢波斜率最大,而慢和快纺锤波密度最显著地位于额中部。第二,在婴儿期,慢波和纺锤波在时间上是耦合的,在大脑的枕部区域耦合强度最大。第三,慢波斜率、快纺锤波密度和慢波-纺锤波耦合与同期的行为状态(6 个月)无关。第四,6 个月时中央和额中部的快纺锤波密度预测 12 个月时的整体发育状态,以及 12 个月和 24 个月时的运动技能。慢波斜率和慢波-纺锤波耦合均不能预测后期的行为发育。我们进一步确定了纺锤波频率是慢和快纺锤波密度的决定因素,相应地,它也可以预测 24 个月时的运动技能。我们的研究结果提出了快纺锤波密度或纺锤波频率作为识别丘脑皮质成熟的早期 EEG 生物标志物,这可能有助于对婴儿神经发育障碍的早期诊断。这些发现支持了睡眠纺锤波在感觉运动微电路发育中的作用。下一步的关键是评估早期的治疗干预措施是否可以有效逆转风险个体的偏差。

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