Probabilistic cytoarchitectonic map of Area p24ab (pACC) (v20.1)

This dataset contains the distinct architectonic areas p24a and p24b (combined to a single probability map named Area p24ab (pACC)) 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 p24ab (pACC). The probability map of Area p24ab (pACC) 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 p24ab (pACC): Palomero-Gallagher et al. (2019) [Data set, v16.0] [DOI: 10.25493/80YK-SN0](https://doi.org/10.25493%2F80YK-SN0) Palomero-Gallagher et al. (2019) [Data set, v16.1] [DOI:10.25493/DHXC-2KN](https://doi.org/10.25493%2FDHXC-2KN) Palomero-Gallagher et al. (2020) [Data set, v18.0] [DOI: 10.25493/NJYW-9R](https://doi.org/10.25493%2FNJYW-9R) The most probable delineation of Area p24ab (pACC) 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, v1.18] [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) Amunts et al. (2021) [Data set, v2.6] [DOI: 10.25493/KJQN-AM0](https://doi.org/10.25493%2FKJQN-AM0) Amunts et al. (2021) [Data set, v2.9] [DOI: 10.25493/VSMK-H94](https://doi.org/10.25493/VSMK-H94)

本数据集包含MNI Colin 27单被试个体模板，以及MNI ICBM 152 2009c非线性不对称参考空间中的两个独立细胞构筑区p24a与p24b，二者被合并为名为p24ab（pACC）的单一概率图谱。作为于利希脑（Julich-Brain）细胞构筑图谱（cytoarchitectonic atlas）的组成部分，该脑区通过对10例取自杜塞尔多夫大学（University of Düsseldorf）遗体捐赠项目的人类死后脑组织（human postmortem brains）的胞体染色组织学切片（cell-body-stained histological sections）开展细胞构筑分析（cytoarchitectonic analysis）得以识别。随后将细胞构筑分析的结果映射至上述两个参考空间，其中每个体素（voxel）均被赋予属于p24ab（pACC）脑区的概率。针对每个脑参考空间与大脑半球，p24ab（pACC）脑区的概率图谱均以NIfTI（NIfTI）格式提供。于利希脑（Julich-Brain）图谱依托一套模块化、灵活且可适配的框架构建，该框架包含用于生成上述脑区概率脑图谱的工作流。请注意，方法学改进与新脑结构的整合可能会导致早期发布的数据集出现细微偏差。p24ab（pACC）脑区的其他可用数据版本如下：
Palomero-Gallagher等人（2019）[数据集，v16.0] [DOI: 10.25493/80YK-SN0]
Palomero-Gallagher等人（2019）[数据集，v16.1] [DOI:10.25493/DHXC-2KN]
Palomero-Gallagher等人（2020）[数据集，v18.0] [DOI: 10.25493/NJYW-9R]
通过计算当前已发布的全部于利希脑结构的最大概率图谱得到的p24ab（pACC）脑区最可靠轮廓，可通过以下数据集获取：
Amunts等人（2019）[数据集，v1.18] [DOI: 10.25493/8EGG-ZAR]
Amunts等人（2020）[数据集，v2.2] [DOI: 10.25493/TAKY-64D]
Amunts等人（2020）[数据集，v2.4] [DOI: 10.25493/A7Y0-NX9]
Amunts等人（2020）[数据集，v2.5] [DOI: 10.25493/8JKE-M53]
Amunts等人（2021）[数据集，v2.6] [DOI: 10.25493/KJQN-AM0]
Amunts等人（2021）[数据集，v2.9] [DOI: 10.25493/VSMK-H94]