Probabilistic cytoarchitectonic map of Area ifs4 (IFS) (v3.2)

This dataset contains the distinct architectonic Area ifs4 (IFS) 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 post mortem 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 of Area ifs4 (IFS). The probability map of Area ifs4 (IFS) 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. The most probable delineation of Area ifs4 (IFS) derived from the calculation of a maximum probability map of all currently released Julich-Brain brain structures can be found here: Amunts et al. (2021) [Data set, v2.9] [DOI: 10.25493/VSMK-H94](https://doi.org/10.25493/VSMK-H94)

这个数据集包含MNI Colin 27个体单被试模板以及MNI ICBM 152 2009c非线性非对称参考空间中的独特结构区域ifs4（IFS）。作为Julich-Brain细胞结构图谱的一部分，该区域是通过对10例来自杜塞尔多夫大学遗体捐赠项目的人类死后大脑的细胞体染色组织切片进行细胞结构分析而确定的。细胞结构分析的结果随后被映射到这两个参考空间，其中每个体素（voxel）被赋予ifs4区域（IFS）的概率值。ifs4区域（IFS）的概率图以NifTi格式提供，涵盖每个大脑参考空间和半球。Julich-Brain图谱依赖于一个模块化、灵活且自适应的框架，该框架包含用于创建这些结构概率脑图的工作流程。请注意，方法学的改进和新脑结构的整合可能会导致早期发布数据集出现微小偏差。ifs4区域（IFS）最可能的轮廓线源自所有当前发布的Julich-Brain脑结构最大概率图的计算，可参见此处：Amunts et al. (2021) [数据集，v2.9] [DOI: 10.25493/VSMK-H94](https://doi.org/10.25493/VSMK-H94)