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皮质微结构的神经生理学特征。

Neurophysiological signatures of cortical micro-architecture.

机构信息

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.

出版信息

Nat Commun. 2023 Sep 26;14(1):6000. doi: 10.1038/s41467-023-41689-6.

Abstract

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 6800 time-series 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 co-localized with multiple micro-architectural features, including gene expression 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.

摘要

皮质中观察到微观结构的系统空间变化。这些微观结构梯度反映在神经活动中,可以通过神经生理时间序列来捕获。自发神经生理动力学如何在皮质中组织,以及它们如何从异质的皮质微观结构中产生,目前尚不清楚。在这里,我们通过从静息状态脑磁图(MEG)信号中估计超过 6800 个时间序列特征,广泛分析了人类大脑的区域神经生理动力学。然后,我们将区域时间序列图谱映射到皮质微观结构的综合多模态、多尺度图谱上,包括微观结构、代谢、神经递质受体、细胞类型和分层分化。我们发现,神经生理动力学的主导轴反映了信号的功率谱密度和线性相关结构的特征,强调了电磁动力学的传统特征的重要性,同时确定了传统上较少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,包括基因表达梯度、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的途径。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/904f/10522715/b3dd94f13534/41467_2023_41689_Fig1_HTML.jpg

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