Probabilistic cytoarchitectonic map of Area PGa (IPL) (v11.0)

This dataset contains the distinct architectonic Area PGa (IPL) in the individual, single subject template of the MNI Colin 27 as well as the MNI ICBM 152 2009c nonlinear asymmetric reference space. As part of the Julich-Brain cytoarchitectonic atlas, the area was identified using cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. The results of the cytoarchitectonic analysis were then mapped to both reference spaces, where each voxel was assigned the probability to belong to Area PGa (IPL). The probability map of Area PGa (IPL) is provided in the NifTi format for each brain reference space and hemisphere. The Julich-Brain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets. Other available data versions of Area PGa (IPL): Caspers et al. (2018) [Data set, v9.2] [DOI: 10.25493/T96P-05Y](https://doi.org/10.25493%2FT96P-05Y) Caspers et al. (2019) [Data set, v9.4] [DOI: 10.25493/V5HY-XTS](https://doi.org/10.25493%2FV5HY-XTS) The most probable delineation of Area PGa (IPL) derived from the calculation of a maximum probability map of all currently released Julich-Brain brain structures can be found here: Amunts et al. (2019) [Data set, v1.13] [DOI: 10.25493/Q3ZS-NV6](https://doi.org/10.25493%2FQ3ZS-NV6) Amunts et al. (2019) [Data set, v1.18] [DOI: 10.25493/8EGG-ZAR](https://doi.org/10.25493%2F8EGG-ZAR) Amunts et al. (2020) [Data set, v2.2] [DOI: 10.25493/TAKY-64D](https://doi.org/10.25493%2FTAKY-64D) Amunts et al. (2020) [Data set, v2.4] [DOI: 10.25493/A7Y0-NX9](https://doi.org/10.25493%2FA7Y0-NX9) Amunts et al. (2020) [Data set, v2.5] [DOI: 10.25493/8JKE-M53](https://doi.org/10.25493/8JKE-M53)

该数据集包含MNI Colin 27单被试个体模板以及MNI ICBM 152 2009c非线性非对称参考空间中独特的构筑区域PGa（IPL）。作为朱利希脑细胞构筑图谱（Julich-Brain cytoarchitectonic atlas）的一部分，该区域通过对10例来自杜塞尔多夫大学遗体捐赠项目的人类尸检脑的胞体染色组织切片进行细胞构筑分析而确定。细胞构筑分析结果随后被映射到两个参考空间中，每个体素被赋予属于PGa区域（IPL）的概率。PGa区域（IPL）的概率图以NifTi格式提供，涵盖每个脑参考空间和半球。朱利希脑图谱依赖于模块化、灵活且自适应的框架，该框架包含生成这些结构概率脑图的工作流程。请注意，方法学改进和新脑结构的整合可能导致早期发布数据集出现微小偏差。PGa区域（IPL）的其他可用数据版本：Caspers等（2018）[数据集，v9.2] [DOI: 10.25493/T96P-05Y]（https://doi.org/10.25493%2FT96P-05Y）；Caspers等（2019）[数据集，v9.4] [DOI: 10.25493/V5HY-XTS]（https://doi.org/10.25493%2FV5HY-XTS）；由所有当前发布的朱利希脑结构最大概率图计算得出的PGa区域（IPL）最可能划分可参考以下版本：Amunts等（2019）[数据集，v1.13] [DOI: 10.25493/Q3ZS-NV6]（https://doi.org/10.25493%2FQ3ZS-NV6）；Amunts等（2019）[数据集，v1.18] [DOI: 10.25493/8EGG-ZAR]（https://doi.org/10.25493%2F8EGG-ZAR）；Amunts等（2020）[数据集，v2.2] [DOI: 10.25493/TAKY-64D]（https://doi.org/10.25493%2FTAKY-64D）；Amunts等（2020）[数据集，v2.4] [DOI: 10.25493/A7Y0-NX9]（https://doi.org/10.25493%2FA7Y0-NX9）；Amunts等（2020）[数据集，v2.5] [DOI: 10.25493/8JKE-M53]（https://doi.org/10.25493/8JKE-M53）