cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25493/8j4n-704
title: Probabilistic cytoarchitectonic map of Area Fo1 (OFC) (v5.0)

description: This dataset contains the distinct architectonic Area Fo1 (OFC) 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 Fo1 (OFC). The probability map of Area Fo1 (OFC) 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 Fo1 (OFC): Henssen et al. (2018) [Data set, v3.2] [DOI: 10.25493/2NSZ-PGW](https://doi.org/10.25493%2F2NSZ-PGW) Henssen et al. (2019) [Data set, v3.4] [DOI: 10.25493/H2N2-6J2](https://doi.org/10.25493%2FH2N2-6J2) The most probable delineation of Area Fo1 (OFC) 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)
DOI: 10.25493/qg9c-thd
title: Probabilistic cytoarchitectonic map of Area hOc2 (V2, 18) (v2.4)

description: This dataset contains the distinct architectonic Area hOc2 (V2, 18) 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 hOc2 (V2, 18). The probability map of Area hOc2 (V2, 18) 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 hOc2 (V2, 18): Amunts et al. (2018) [Data set, v2.2] [DOI: 10.25493/FKMC-ZX7](https://doi.org/10.25493%2FFKMC-ZX7) The most probable delineation of Area hOc2 (V2, 18) 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)
DOI: 10.25493/ajge-pnh
title: Probabilistic cytoarchitectonic map of Area PFm (IPL) (v9.2)

description: This dataset contains the distinct probabilistic cytoarchitectonic map of Area PFm (IPL) 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 Area PFm (IPL). The probability map of Area PFm (IPL) 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 Area PFm (IPL): Caspers et al. (2019) [Data set, v9.4] [DOI: 10.25493/TB94-HRK](https://doi.org/10.25493%2FTB94-HRK) The most probable delineation of Area PFm (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)
DOI: 10.34810/data72/381
title: 01CO_1.MR.0004.0031.2016.02.04.15.44.11.109375.67135133.IMA
DOI: 10.25493/x4s6-e64
title: Reference delineations of Subiculum (Hippocampus) in individual sections of the BigBrain

description: This dataset contains cytoarchitectonic delineations of the Subicular Complex including the prosubiculum (ProS), subiculum proper (Sub), presubiculum (PreS) and parasubiculum (PaS) in the BigBrain dataset [Amunts et al. 2013]. The delineations were created after identification of the areas in the histological, cell-stained sections based on the cytoarchitectonic criteria. Mappings of ProS, Sub, PreS and PaS are available on every 15th to 60th section in both hemispheres. They were then transformed to the sections of the 3D reconstructed BigBrain space using the transformations used in Amunts et al. 2013, which were provided by Claude Lepage (McGill).
DOI: 10.25493/nwpm-4pn
title: Probability map of bundle lh_Tr-SF_0 (atlas of superficial white matter fibre bundles, version 2018)

description: This data contains the probability map of a short fibre bundle connecting the left hemisphere Pars Triangularis and Superior Frontal regions of the Desikan-Killiany atlas, in the MNI ICBM152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fibre shape (fibre clustering), from the tractography datasets of 78 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fibre belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibres going through.
DOI: 10.25493/3248-7v
title: 3D imaging of the vascular system of the mouse brain.

description: The goal of the study is to produce the first high resolution, 3D reconstruction of the entire macrostructure and vascular system of the mouse brain. To that end previously synchrotron radiation-based X-ray microscopy images were collected. Recently two-photon microscopy images were collected to that end. And we are looking for additional alternative imaging sources. Then this data is translated into 3D mesh and volumetric models (graph). This dataset contains tiff image array of part of cortical vasculature of the mouse brain. This dataset is used as an input to computational methods that results in the dataset “3D reconstruction of the vascular system of the mouse brain” ([doi: 10.25493/47H2-1HR](https://doi.org/10.25493/47H2-1HR)).
DOI: 10.25493/1z8f-px4
title: Probabilistic cytoarchitectonic map of Area OP3 (POperc) (v9.4)

description: This dataset contains the distinct architectonic Area OP3 (POperc) in the MNI Colin 27 and MNI ICBM 152 reference spaces. As part of the Julich-Brain 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. 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 OP3 (POperc). The probability map of Area OP3 (POperc) 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 OP3 (POperc): Eickhoff et al. (2018) [Data set, v9.2] [DOI: 10.25493/6PRT-2PS](https://doi.org/10.25493%2F6PRT-2PS) Eickhoff et al. (2019) [Data set, v11.0] [DOI: 10.25493/V715-BQU](https://doi.org/10.25493%2FV715-BQU) The most probable delineation of Area OP3 (POperc) 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)
DOI: 10.25493/qa8f-dd2
title: Probabilistic cytoarchitectonic map of Area 2 (PostCS) (v3.4)

description: This dataset contains the distinct architectonic Area 2 (PostCS) 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 2 (PostCS). The probability map of Area 2 (PostCS) 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 2 (PostCS): Grefkes et al. (2018) [Data set, v3.2] [DOI: 10.25493/JZP0-Q97](https://doi.org/10.25493%2FJZP0-Q97) The most probable delineation of Area 2 (PostCS) 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)
DOI: 10.25493/cp2t-fyt
title: Probabilistic cytoarchitectonic map of Area TE 1.0 (HESCHL) (v5.0)

description: This dataset contains the distinct probabilistic cytoarchitectonic map of Area TE 1.0 (HESCHL) 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 Area TE 1.0 (HESCHL). The probability map of Area TE 1.0 (HESCHL) 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 Area TE 1.0 (HESCHL): Morosan et al. (2019) [Data set, v5.1] [DOI: 10.25493/MV3G-RET](https://doi.org/10.25493%2FMV3G-RET) The most probable delineation of Area TE 1.0 (HESCHL) 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)
DOI: 10.25493/k236-r0v
title: Probabilistic cytoarchitectonic map of CA2 (Hippocampus) (v11b.0)

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): Morosan et al. (2020) [Data set, v11.1] [DOI: 10.25493/46G6-T33](https://doi.org/10.25493%2F46G6-T33) 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%2FTAKY-64D)
DOI: 10.25493/5gxc-z2u
title: Probabilistic cytoarchitectonic map of Area 4a (PreCG) (v9.2)

description: This dataset contains the distinct probabilistic cytoarchitectonic map of Area 4a (PreCG) 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 Area 4a (PreCG). The probability map of Area 4a (PreCG) 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 Area 4a (PreCG): Geyer et al. (2019) [Data set, v9.4] [DOI: 10.25493/PVPP-P3Q](https://doi.org/10.25493%2FPVPP-P3Q) The most probable delineation of Area 4a (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)
DOI: 10.25493/e0mf-gfe
title: Probabilistic cytoarchitectonic map of Area OP6 (Frontal Operculum) (v3.0)

description: This dataset contains the distinct probabilistic cytoarchitectonic map of Area OP6 (Frontal Operculum) 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 Area OP6 (Frontal Operculum). The probability map of Area OP6 (Frontal Operculum) 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 Area OP6 (Frontal Operculum): Unger et al. (2019) [Data set, v1.0] DOI: 10.25493/TYC2-JAH Unger et al. (2020) [Data set, v2.0] [DOI: 10.25493/41KE-8HT](https://doi.org/10.25493%2F41KE-8HT) The most probable delineation of Area OP6 (Frontal Operculum) 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, v2.2] [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)
DOI: 10.25493/377r-t96
title: Probabilistic cytoarchitectonic map of Area Id2 (Insula) (v7.1)

description: This dataset contains the distinct probabilistic cytoarchitectonic map of Area Id2 (Insula) 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 Id2 (Insula). The probability map of Area Id2 (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 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. The most probable delineation of Area Id2 (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)
DOI: 10.25493/2wsh-mct
title: Probabilistic cytoarchitectonic map of Area hOc5 (LOC) (v2.4)

description: This dataset contains the distinct architectonic Area hOc5 (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 hOc5 (LOC). The probability map of Area hOc5 (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 hOc5 (LOC): Malikovic et al. (2018) [Data set, v2.2] [DOI: 10.25493/BPG7-360](https://doi.org/10.25493%2FBPG7-360) The most probable delineation of Area hOc5 (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)