Linking the microarchitecture of neurotransmitter systems to large-scale MEG resting state networks

Information processing and communication in neuronal circuits is enabled by dynamic networks of inter-areal coupling of neuronal oscillations in which hubs play a central role for regulation of communication. Oscillations are shaped by interactions between pyramidal cells and interneurons and are locally influenced by neuromodulatory systems. Here, we set out to investigate how sparial variability in neurotransmitter receptor and transporter density influences frequency-specific large-scale networks of phase-synchrony (PS) and amplitude-correlation (AC) in human magnetoencephalography data. We found that node centrality - indexing which individual brain regions function as hubs - covaried positively with GABA, NMDA, dopaminergic, and most serotonergic receptor and transporter densities in lower frequency bands (delta to low-alpha for PS, and delta for AC) and in the gamma band, but negatively in between. These results establish how local microarchitecture influences large-scale connecti..., MEG data acquisition
Data from 67 healthy human volunteers (age 18 to 57 years old; mean age: 30.9 ± 8.3 years; 6 left-handed; 32 female, 35 male; 64 Caucasian, 2 South Asian, 1 East Asian) were collected for this study. The study was performed in accordance with the Declaration of Helsinki and with permission of the Ethical Committee of the hospital at which the recordings were carried out. All participants gave written informed consent prior to the recordings. 
MEG data was recorded with a 306-channel (204 planar gradiometers and 102 magnetometers) Triux MEG (Elekta-Neuromag/MEGIN, Helsinki, Finland). We recorded 10 minutes of eyes-open resting-state data from all participants. Bipolar horizontal and vertical EOG were recorded for the detection of ocular artifacts. MEG and EOG were recorded at a 1,000-Hz sampling rate.
T1-weighted anatomical MRI scans (MP-RAGE) were obtained for head models and cortical surface reconstruction at a resolution of 1 × 1 × 1 mm with a 1.5-Tesla MRI scanne..., , # Linking the microarchitecture of neurotransmitter systems to large-scale MEG resting state networks

[https://doi.org/10.5061/dryad.qz612jmq1](https://doi.org/10.5061/dryad.qz612jmq1)

This dataset provides functional connectivity data from source-reconstructed MEG, as well as receptor maps and other support files that can be used to reproduce the article's findings.

## Description of the data and file structure

**Functional connectivity files**:

*conn_iPLV_67.npy*: A numpy file containing a 4D numpy array containing phase synchrony values (estimated with iPLV) between 200 cortical parcels of the 17-network Schaefer atlas, for 41 narrowband frequencies and 67 subjects. The shape of the array is [subjects x frequencies x parcels x parcels].

*conn_oCC_67.npy*: A numpy file containing a 4D numpy array containing amplitude correlation values (estimated with oCC) between 200 cortical parcels of the 17-network Schaefer atlas, for 41 narrowband frequencies and 67 subjects. The shape of ...

神经元环路中的信息处理与通信依赖于神经元振荡脑区间耦合的动态网络，其中枢纽节点在通信调控中发挥核心作用。神经元振荡由锥体神经元与中间神经元的相互作用塑造，并受局部神经调节系统的影响。
本研究旨在探究人类脑磁图（magnetoencephalography, MEG）数据中，神经递质受体与转运体密度的空间异质性如何影响频率特异性的大规模相位同步（phase-synchrony, PS）与振幅相关（amplitude-correlation, AC）网络。

研究发现，表征单个脑区枢纽功能的节点中心性，在低频频段（相位同步对应δ频段至低α频段，振幅相关对应δ频段）及γ频段内，与γ-氨基丁酸（GABA）、N-甲基-D-天冬氨酸（NMDA）、多巴胺能及多数5-羟色胺能受体和转运体密度呈正相关，而在中间频段呈负相关。

### MEG数据采集
本研究共纳入67名健康人类志愿者（年龄18~57岁，平均年龄30.9±8.3岁；左利手6人，女性32人、男性35人；高加索裔64人、南亚裔2人、东亚裔1人）并采集其数据。本研究严格遵循《赫尔辛基宣言》开展，并获得数据采集所在医院伦理委员会的批准。所有参与者均在数据采集前签署了书面知情同意书。

采用306通道（204个平面梯度计与102个磁强计）Triux脑磁图系统（Elekta-Neuromag/MEGIN，芬兰赫尔辛基）采集MEG数据。为所有参与者记录10分钟睁眼静息态数据；同时记录双极水平与垂直眼电图（electrooculography, EOG）以检测眼动伪迹。MEG与EOG的采样率均为1000Hz。

采用1.5T磁共振扫描仪以1×1×1mm的分辨率采集T1加权解剖MRI扫描数据（MP-RAGE序列），用于构建头部模型与皮层表面重建。

# 将神经递质系统的微观结构与大规模脑磁图静息态网络相关联
https://doi.org/10.5061/dryad.qz612jmq1

本数据集包含源重构脑磁图的功能连接数据，以及可用于复现论文研究结果的受体图谱与其他辅助文件。

## 数据与文件结构说明
**功能连接文件**：
*conn_iPLV_67.npy*：该NumPy文件包含一个四维NumPy数组，存储了67名受试者在41个窄带频段下，17网络Schaefer图谱的200个皮层分区之间的相位同步值（采用iPLV方法估算）。数组维度为[受试者数 × 频段数 × 分区数 × 分区数]。
*conn_oCC_67.npy*：该NumPy文件包含一个四维NumPy数组，存储了67名受试者在41个窄带频段下，17网络Schaefer图谱的200个皮层分区之间的振幅相关值（采用oCC方法估算）。数组维度为……