cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25493/kgj3-xc6
title: Probabilistic cytoarchitectonic map of Area Id5 (Insula) (v5.1)

description: This dataset contains the distinct architectonic Area Id5 (Insula) in the MNI Colin 27 and MNI ICBM 152 reference spaces. As part of the Julich-Brain 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. Subsequently the results of the cytoarchitectonic analysis are mapped to the MNI Colin 27 and MNI ICBM 152 reference spaces where each voxel is assigned with the probability to belong to Area Id5 (Insula). The probability map of Area Id5 (Insula) are 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 Id5 (Insula): Quabs et al. (2019) [Data set, v3.1] [DOI: 10.25493/5CK1-B1G]()https://doi.org/10.25493%2F5CK1-B1G Quabs et al. (2020) [Data set, v4.0] [DOI: 10.25493/VPM3-405](https://doi.org/10.25493%2FVPM3-405) The most probable delineation of Area Id5 (Insula) 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/10.25493/8EGG-ZAR) Amunts et al. (2020) [Data set, v2.2] [DOI: 10.25493/TAKY-64D](https://doi.org/10.25493/TAKY-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)
DOI: 10.25493/hnzp-56m
title: Probabilistic cytoarchitectonic map of Area ifs1 (IFS) (v3.2)

description: This dataset contains the distinct architectonic Area ifs1 (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 ifs1 (IFS). The probability map of Area ifs1 (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 ifs1 (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)
DOI: 10.25493/67r5-xke
title: Probabilistic cytoarchitectonic map of Area hIP1 (IPS) (v7.2)

description: This dataset contains the distinct architectonic Area hIP1 (IPS) 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 hIP1 (IPS). The probability map of Area hIP1 (IPS) are 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 hIP1 (IPS): Choi et al. (2018) [Data set, v6.0] [DOI: 10.25493/VWV1-FYY](https://doi.org/10.25493%2FVWV1-FYY) Choi et al. (2019) [Data set, v6.1] [DOI: 10.25493/92FE-7S6](https://doi.org/10.25493%2F92FE-7S6) Choi et al. (2021) [Data set, v7.0] [DOI: 10.25493/A04Z-E42] The most probable delineation of Area hIP1 (IPS) 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) 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)
DOI: 10.6084/m9.figshare.15085749
title: Realistic motion avatars are the future for social interaction in virtual reality

description: Raw data files for the article:Rogers, S. L., Broadbent, R., Brown, J., Fraser, A., & Speelman, C. (2021). Realistic motion avatars are the future for social interaction in virtual reality. https://doi.org/10.31234/osf.io/gcakv<br>
DOI: 10.25493/qa38-e2x
title: Probabilistic cytoarchitectonic map of Area hOc4lp (LOC) (v5.2)

description: This dataset contains the distinct architectonic Area hOc4lp (LOC) 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 hOc4lp (LOC). The probability map of Area hOc4lp (LOC) 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 hOc4lp (LOC): Malikovic et al. (2018) [Data set, v3.2] [DOI: 10.25493/W4H2-WTM](https://doi.org/10.25493%2FW4H2-WTM) Malikovic et al. (2019) [Data set, v3.4] [DOI: 10.25493/4B87-Q8X](https://doi.org/10.25493%2F4B87-Q8X) Malikovic et al. (2020) [Data set, v5.0] [DOI: 10.25493/YHZN-VMV](https://doi.org/10.25493%2FYHZN-VMV) The most probable delineation of Area hOc4lp (LOC) 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) Amunts et al. (2021) [Data set, v2.6] [DOI: 10.25493/KJQN-AM0](https://doi.org/10.25493%2FKJQN-AM0) Nexus ID: minds/core/dataset/v1.0.0/e13a1f52-453c-4a50-a7ea-3c0cd0475e70
DOI: 10.25493/m046-9dj
title: Probabilistic cytoarchitectonic map of CA2 (Hippocampus) (v13.2)

description: This dataset contains the distinct probabilistic cytoarchitectonic map of CA2 (Hippocampus) in the individual, single subject template of the MNI Colin 27 reference space. As part of the Julich-Brain cytoarchitectonic atlas, the area was identified using classical histological criteria and quantitative 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 the reference space, where each voxel was assigned the probability to belong to CA2 (Hippocampus). The probability map of CA2 (Hippocampus) is provided in NifTi format for each hemisphere in the reference space. 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 updated probability estimates for new brain structures may in some cases lead to measurable but negligible deviations of existing probability maps, as compared to earlier released datasets. Other available data versions of CA2 (Hippocampus): Amunts et al. (2018) [Data set, v11b.0] [DOI: 10.25493/K236-R0V](https://doi.org/10.25493/K236-R0V) Palomero-Gallagher et al. (2020) [Data set, v11.1][DOI: 10.25493/46G6-T33](https://doi.org/10.25493%2F46G6-T33) Palomero-Gallagher et al. (2020) [Data set, v13.0] [DOI: 10.25493/RNG0-92J](https://doi.org/10.25493%2FRNG0-92J) The most probable delineation of CA2 (Hippocampus) 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. (2020) [Data set, v2.2] [DOI: 10.25493/TAKY-64D](https://doi.org/10.25493/TAKY-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)
DOI: 10.25493/5e3r-s51
title: Probabilistic cytoarchitectonic map of HC-Presubiculum (Hippocampus) (v13.2)

description: This dataset contains the distinct architectonic HC-Presubiculum (Hippocampus) 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 HC-Presubiculum (Hippocampus). The probability map of HC-Presubiculum (Hippocampus) are 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 HC-Presubiculum (Hippocampus): Palomero-Gallagher et al. (2020) [Data set, v13.0] [DOI: 10.25493/TD8X-VS9](https://doi.org/10.25493%2FTD8X-VS9) The most probable delineation of Entorhinal Cortex derived from the calculation of a maximum probability map of all currently released Julich-Brain brain structures can be found here: 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)
DOI: 10.25493/ct6w-gbh
title: Probabilistic cytoarchitectonic map of Area Id7 (Insula) (v8.1)

description: This dataset contains the distinct architectonic Area Id7 (Insula) in the MNI Colin 27 and MNI ICBM 152 reference spaces. As part of the Julich-Brain 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. Subsequently, the results of the cytoarchitectonic analysis are mapped to the MNI Colin 27 and MNI ICBM 152 reference spaces, where each voxel is assigned with the probability to belong to Area Id7 (Insula). The probability map of Area Id7 (Insula) 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 Id7 (Insula): Amunts et al. (2019) [Data set, v6.0] [DOI: 10.25493/B2E3-JQR](https://doi.org/10.25493%2FB2E3-JQR) Amunts et al. (2019) [Data set, v6.1] [DOI: 10.25493/88QG-JMS](https://doi.org/10.25493%2F88QG-JMS) Amunts et al. (2020) [Data set, v7.0] [DOI: 10.25493/AFP6-CQ](https://doi.org/10.25493%2FAFP6-CQ) The most probable delineation of Area Id7 (Insula) 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)
DOI: 10.25493/kqax-adp
title: Probabilistic cytoarchitectonic map of Ch 4 (Basal Forebrain) (v4.3)

description: This dataset contains the distinct architectonic Ch 4 (Basal Forebrain) 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 Ch 4 (Basal Forebrain). The probability map of Ch 4 (Basal Forebrain) 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 Ch 4 (Basal Forebrain): Zaborszky et al. (2018) [Data set, v4.0] [DOI: 10.25493/BWZ1-5MV](https://doi.org/10.25493%2FBWZ1-5MV) Zaborszky et al. (2019) [Data set, v4.2] [DOI: 10.25493/VZJ5-8WJ](https://doi.org/10.25493%2FVZJ5-8WJ) The most probable delineation of Ch 4 (Basal Forebrain) 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) 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)
DOI: 10.25493/90wb-0au
title: Probabilistic cytoarchitectonic map of Interposed Nucleus (Cerebellum) (v6.3)

description: This dataset contains the distinct architectonic Interposed Nucleus (Cerebellum) 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 classical histological criteria and quantitative 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 Interposed Nucleus (Cerebellum). The probability map of Interposed Nucleus (Cerebellum) 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 Interposed Nucleus (Cerebellum): Tellmann et al. (2018) [Data set, v6.0] [DOI: 10.25493/8MRR-JHC](https://doi.org/10.25493%2F8MRR-JHC) Tellmann et al. (2019) [Data set, v6.2] [DOI: 10.25493/8PTB-JDH](https://doi.org/10.25493%2F8PTB-JDH) The most probable delineation of Interposed Nucleus (Cerebellum) 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) 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)
DOI: 10.25493/wjq5-hwc
title: Probabilistic cytoarchitectonic map of Area 6d2 (PreCG) (v7.1)

description: This dataset contains the distinct architectonic Area 6d2 (PreG) 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 6d2 (PreG). The probability map of Area 6d2 (PreG) are 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 6d2 (PreCG): Sigl et al. (2019) [Data set, v4.0] [DOI: 10.25493/4MMD-HEB](https://doi.org/10.25493%2F4MMD-HEB) Sigl et al. (2019) [Data set, v4.1] [DOI: 10.25493/KXHS-N90](https://doi.org/10.25493%2FKXHS-N90) Sigl et al. (2020) [Data set, v5.0] [DOI: 10.25493/KVX1-XEK](https://doi.org/10.25493%2FKVX1-XEK) The most probable delineation of Area 6d2 (PreCG) 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) 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)
DOI: 10.25493/jnts-337
title: Probabilistic cytoarchitectonic map of HC-Parasubiculum (Hippocampus) (v13.2)

description: This dataset contains the distinct architectonic HC-Parasubiculum (Hippocampus) 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 HC-Parasubiculum (Hippocampus). The probability map of HC-Parasubiculum (Hippocampus) are 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 HC-Parasubiculum (Hippocampus): Palomero-Gallagher et al. (2020) [Data set, v13.0] [DOI: 10.25493/5E7R-RB](https://doi.org/10.25493%2F5E7R-RB) The most probable delineation of Entorhinal Cortex derived from the calculation of a maximum probability map of all currently released Julich-Brain brain structures can be found here: 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)