2016 Glasser MMP1.0 Cortical Atlases

The Glasser et al. group level MMP parcellation map projected into volumetric space using registration fusion. Volumetric space is available for two different standard templates.<br>MNI152NLin6Asym - FSL/HCP "standard" space<br>MNI152NLin2009cAsym - fmriprep's default space.glasser_MNI152NLin[2009c|6]Asym_atlas.nii.gz - probabilistic maps projected to two templates' spaces<br>glasser_atlas_labels.txt - labels of parcels above, line order corresponds to volume order.<br>[lr]h_[bmrk5|paingen]_MNI152NLin[2009c|6]Asym.nii.gz - subject specific parcellations projected in templates' space. One per hemisphere<br>[rl]h.HCP.MMP1 - glasser atlas resampled to fsaverage surfaces<br>methods - informal methods description (but still pretty formal)<br>glasser_MNI152NLin[2009cAsym|6Asym]_labeled_p20.nii.gz - convenience file, thresholded versions of glasser_*_atlas.nii.gz with connectome workbench compatible colors specified in the header.<br><br>The group MMP surface parcellation was resampled from fs_LR to fsaverage space. Surface to volume mappings were then used to transform the group MMP parcellation from fsaverage space into native T1 space. Finally, transformations from native T1 space to the desired template space were applied to transform parcellations into the desired spaces. Individual participant's projections were used to estimate probability maps for each study separately. The resultant study specific probability maps were averaged. Data from two different studies (N=88 and N=241), are incorporated. fmriprep 20.2.3 was run with the --recon-all flag to produce all necessary spatial transformations.Refer to methods.txt for scanning protocols and participant details.

本数据集包含Glasser等人的组水平多模态分区图谱（Multi-Modal Parcellation, MMP），该图谱通过配准融合（registration fusion）技术被投影至体积空间。该体积空间适配两种不同的标准模板：<br>MNI152NLin6Asym：即FSL/HCP的“标准”空间<br>MNI152NLin2009cAsym：即fmriprep的默认空间<br><br>相关文件说明如下：<br>glasser_MNI152NLin[2009c|6]Asym_atlas.nii.gz：投影至两种标准模板空间的概率图谱文件<br>glasser_atlas_labels.txt：上述分区的标签文件，行顺序与体积文件中的分区顺序一一对应<br>[lr]h_[bmrk5|paingen]_MNI152NLin[2009c|6]Asym.nii.gz：适配单个被试的分区图谱，已投影至标准模板空间，每个文件对应单侧大脑半球<br>[rl]h.HCP.MMP1：重采样至fsaverage表面空间的Glasser图谱<br>methods：方法说明文件（虽为非正式表述，但仍具备较强专业性）<br>glasser_MNI152NLin[2009cAsym|6Asym]_labeled_p20.nii.gz：便捷式阈值化图谱文件，为glasser_*_atlas.nii.gz的阈值化版本，其文件头中指定了兼容Connectome Workbench的配色方案<br><br>数据处理流程如下：组水平MMP表面分区图谱首先从fs_LR空间重采样至fsaverage表面空间。随后通过表面-体积映射，将组水平MMP分区图谱从fsaverage空间转换至个体原生T1空间。最后，通过原生T1空间至目标标准模板空间的空间变换，将分区图谱投影至目标空间。本研究针对每项独立数据集，利用单个被试的投影结果估算其专属概率图谱，随后对所有研究的专属概率图谱进行平均整合。本数据集纳入了两项独立研究的影像数据（样本量分别为N=88与N=241）。处理流程中使用fmriprep 20.2.3并添加--recon-all参数，以生成所有必要的空间变换矩阵。扫描协议与被试详细信息请参阅methods.txt文件。

搜集汇总

背景与挑战

背景概述

该数据集是2016年Glasser MMP1.0皮层图谱，将组水平MMP分区图通过配准融合投影到体积空间，支持两个标准模板（MNI152NLin6Asym和MNI152NLin2009cAsym）。它包含概率图谱、标签文件和半球特定分区数据，基于两个研究（共329名参与者）的数据生成，适用于认知神经科学和计算神经科学等领域的研究。