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人类电磁和血液动力学网络在单模态皮质中系统地汇聚,在跨模态皮质中发散。

Human electromagnetic and haemodynamic networks systematically converge in unimodal cortex and diverge in transmodal cortex.

机构信息

McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, Canada.

出版信息

PLoS Biol. 2022 Aug 1;20(8):e3001735. doi: 10.1371/journal.pbio.3001735. eCollection 2022 Aug.

Abstract

Whole-brain neural communication is typically estimated from statistical associations among electromagnetic or haemodynamic time-series. The relationship between functional network architectures recovered from these 2 types of neural activity remains unknown. Here, we map electromagnetic networks (measured using magnetoencephalography (MEG)) to haemodynamic networks (measured using functional magnetic resonance imaging (fMRI)). We find that the relationship between the 2 modalities is regionally heterogeneous and systematically follows the cortical hierarchy, with close correspondence in unimodal cortex and poor correspondence in transmodal cortex. Comparison with the BigBrain histological atlas reveals that electromagnetic-haemodynamic coupling is driven by laminar differentiation and neuron density, suggesting that the mapping between the 2 modalities can be explained by cytoarchitectural variation. Importantly, haemodynamic connectivity cannot be explained by electromagnetic activity in a single frequency band, but rather arises from the mixing of multiple neurophysiological rhythms. Correspondence between the two is largely driven by MEG functional connectivity at the beta (15 to 29 Hz) frequency band. Collectively, these findings demonstrate highly organized but only partly overlapping patterns of connectivity in MEG and fMRI functional networks, opening fundamentally new avenues for studying the relationship between cortical microarchitecture and multimodal connectivity patterns.

摘要

全脑神经通讯通常是通过电磁或血液动力学时间序列之间的统计关联来估计的。从这 2 种神经活动中恢复的功能网络结构之间的关系尚不清楚。在这里,我们将电磁网络(使用脑磁图(MEG)测量)映射到血液动力学网络(使用功能磁共振成像(fMRI)测量)。我们发现,这两种模态之间的关系在区域上是不均匀的,并且系统地遵循皮质层次结构,在单模态皮质中具有紧密的对应关系,而在跨模态皮质中对应关系较差。与 BigBrain 组织学图谱的比较表明,电磁-血液动力学耦合是由分层分化和神经元密度驱动的,这表明这两种模态之间的映射可以用细胞构筑变化来解释。重要的是,血液动力学连通性不能用单一频带中的电磁活动来解释,而是来自多个神经生理节律的混合。这两个的对应主要由 beta(15 到 29 赫兹)频段的 MEG 功能连接驱动。总的来说,这些发现表明 MEG 和 fMRI 功能网络中的连接具有高度组织化但只有部分重叠的模式,为研究皮质微结构和多模态连接模式之间的关系开辟了根本的新途径。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/04d9/9371256/e83adbf07d1d/pbio.3001735.g001.jpg

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