Shafiei Golia, Fulcher Ben D, Voytek Bradley, Satterthwaite Theodore D, Baillet Sylvain, Misic Bratislav
McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, Canada.
Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
bioRxiv. 2023 Jan 23:2023.01.23.525101. doi: 10.1101/2023.01.23.525101.
Systematic spatial variation in micro-architecture is observed across the cortex. These micro-architectural gradients are reflected in neural activity, which can be captured by neurophysiological time-series. How spontaneous neurophysiological dynamics are organized across the cortex and how they arise from heterogeneous cortical micro-architecture remains unknown. Here we extensively profile regional neurophysiological dynamics across the human brain by estimating over 6 800 timeseries features from the resting state magnetoencephalography (MEG) signal. We then map regional time-series profiles to a comprehensive multi-modal, multi-scale atlas of cortical micro-architecture, including microstructure, metabolism, neurotransmitter receptors, cell types and laminar differentiation. We find that the dominant axis of neurophysiological dynamics reflects characteristics of power spectrum density and linear correlation structure of the signal, emphasizing the importance of conventional features of electromagnetic dynamics while identifying additional informative features that have traditionally received less attention. Moreover, spatial variation in neurophysiological dynamics is colocalized with multiple micro-architectural features, including genomic gradients, intracortical myelin, neurotransmitter receptors and transporters, and oxygen and glucose metabolism. Collectively, this work opens new avenues for studying the anatomical basis of neural activity.
在整个皮质中观察到微观结构的系统性空间变化。这些微观结构梯度反映在神经活动中,神经活动可通过神经生理时间序列来捕捉。自发神经生理动力学如何在整个皮质中组织起来以及它们如何从异质性皮质微观结构中产生仍然未知。在这里,我们通过从静息态脑磁图(MEG)信号中估计超过6800个时间序列特征,广泛描绘了整个人脑区域的神经生理动力学。然后,我们将区域时间序列概况映射到一个全面的多模态、多尺度皮质微观结构图谱,包括微观结构、代谢、神经递质受体、细胞类型和层状分化。我们发现,神经生理动力学的主导轴反映了信号功率谱密度和线性相关结构的特征,强调了电磁动力学传统特征的重要性,同时识别出了传统上较少受到关注的其他信息特征。此外,神经生理动力学的空间变化与多种微观结构特征共定位,包括基因组梯度、皮质内髓鞘、神经递质受体和转运体,以及氧和葡萄糖代谢。总的来说,这项工作为研究神经活动的解剖学基础开辟了新途径。