Rattray Gregory F, Jourde Hugo R, Baillet Sylvain, Coffey Emily B J
Department of Psychology, Concordia University, Quebec, Canada.
Montreal Neurological Institute, McGill University, Quebec, Canada.
Hum Brain Mapp. 2025 Oct 1;46(14):e70354. doi: 10.1002/hbm.70354.
Subcortical brain regions like the thalamus are integral to numerous sensory and cognitive functions. Magnetoencephalography (MEG) enables the study of widespread brain networks with high temporal resolution, but the degree to which deep sources like the thalamus can be resolved remains unclear. Functional connectivity methods may enhance differentiation, yet few studies have extended them beyond the cortex. We investigated the possibility of resolving deep sources via connectivity patterns during thalamo-cortical sleep spindles to leverage their well-characterized circuitry, and during spindle-free periods of non-rapid eye movement sleep to explore neural recordings that lack such high-amplitude bursts of activity. MEG and electroencephalography (EEG) were recorded in 19 participants during a 2-h nap. Spindle and non-spindle periods were identified, and connectivity was assessed using coherence and imaginary coherence within a spindle-related network. Graph theory was also applied to identify network hubs. As expected, functional connectivity increased during spindles within a distributed thalamo-cortical-hippocampal network. Cortical connectivity patterns allowed differentiation among small thalamic nuclei, but metric choice and contrast use influenced topography and distance effects. Graph theory revealed distinct cortical, thalamic, and hippocampal contributions to fast (13-16 Hz) and slow (10-13 Hz) sigma-band connectivity. These findings demonstrate that MEG functional connectivity can resolve deep brain networks during NREM sleep and during spindles, and demonstrate how it can be used to study the functional roles of subcortical regions non-invasively in healthy humans. By clarifying methodological influences, we aim to guide future research design and interpretation.
像丘脑这样的大脑皮层下区域对于众多感觉和认知功能至关重要。脑磁图（MEG）能够以高时间分辨率研究广泛的脑网络，但像丘脑这样的深部源能够被分辨的程度仍不清楚。功能连接方法可能会增强区分能力，然而很少有研究将其应用范围扩展到皮层之外。我们研究了在丘脑 - 皮层睡眠纺锤波期间通过连接模式分辨深部源的可能性，以利用其特征明确的神经回路，并且在非快速眼动睡眠的无纺锤波期探索缺乏这种高振幅活动爆发的神经记录。在19名参与者午睡2小时期间记录了MEG和脑电图（EEG）。识别出纺锤波期和非纺锤波期，并使用与纺锤波相关网络内的相干性和虚相干性评估连接性。还应用图论来识别网络枢纽。正如预期的那样，在分布式丘脑 - 皮层 - 海马网络内的纺锤波期间功能连接性增加。皮层连接模式允许区分小的丘脑核团，但度量选择和对比使用会影响拓扑结构和距离效应。图论揭示了皮层、丘脑和海马对快速（13 - 16赫兹）和慢速（10 - 13赫兹）西格玛波段连接性的不同贡献。这些发现表明，MEG功能连接性能够在非快速眼动睡眠期间和纺锤波期间分辨深部脑网络，并展示了如何在健康人类中无创地用于研究皮层下区域的功能作用。通过阐明方法学影响，我们旨在指导未来的研究设计和解释。
