cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25493/2g11-1wa
title: Probabilistic cytoarchitectonic map of Area STS1 (STS) (v3.0)

description: This dataset contains the distinct probabilistic cytoarchitectonic map of Area STS1 (STS) 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 STS1 (STS). The probability map of Area STS1 (STS) 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 STS1 (STS): Zachlod et al. (2019) [Data set, v3.1] [DOI: 10.25493/F6DF-H8P](https://doi.org/10.25493%2FF6DF-H8P) The most probable delineation of Area STS1 (STS) 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)
DOI: 10.25493/6hre-f2y
title: Densities and 3D distributions of synapses using FIB/SEM imaging in the human hippocampus (CA1)

description: Synapses have been identified, segmented and quantified in the CA1 field of the human hippocampus with 3D electron microscopy (FIB-SEM). Pyramidal layer and stratum radiatum have been studied. 3 cases have been used (AB1, AB2, AB3) to achieve a total of 18 valid images stacks. Data include the number of asymmetric and symmetric synapses, their sizes and their spatial distribution.
DOI: 10.25493/vp8c-5f1
title: Interpolated 3D map of Area hIP7 (IPS) in the BigBrain

description: This dataset contains cytoarchitectonic maps of Area hIP7 (IPS) in the Big Brain dataset [Amunts et al. 2013]. The mappings were created using the semi-automatic method presented in Schleicher et al. 1999, based on coronal histological sections on 1 micron resolution. Mappings are available on approximately every 15-60th section of this region. They were then aligned to the corresponding sections of the 3D reconstructed Big Brain space, using the transformations used in Amunts et al. 2013, kindly provided by Claude Lepage (McGill University). From these delineations, a preliminary 3D map of Area hIP7 (IPS) has been created by simple interpolation of the coronal contours in the 3D anatomical space of the Big Brain. This map gives a first impression of the location of this area in the Big Brain, and can be viewed in the atlas viewer using the URL below. A full mapping of this area in every histological section using a Deep Learning approach is in progress. **Additional information:** The reference delineations used for this map are part of the work for the corresponding probabilistic map of Area hIP7 (IPS) of the JuBrain Cytoarchitectonic Atlas, published in: Richter et al.(2019) [Data set, v7.0] [DOI: 10.25493/QN1F-WAF](https://doi.org/10.25493%2FQN1F-WAF) Richter et al. (2019) [Data set, v7.1] [DOI: 10.25493/WRCY-8Z1](https://doi.org/10.25493%2FWRCY-8Z1) In addition, the dataset of the probabilistic cytoarchitectonic map of Area hIP7 (IPS) is part of the following research publication: Richter, M., Amunts, K., Mohlberg, H., Bludau, S., Eickhoff, S. B., Zilles, K., Caspers, S. (2018). Cytoarchitectonic segregation of human posterior intraparietal and adjacent parieto-occipital sulcus and its relation to visuomotor and cognitive functions. Cerebral Cortex, 29(3), 1305-1327 [DOI: 10.1093/cercor/bhy245](https://doi.org/10.1093%2Fcercor%2Fbhy245%20)
DOI: 10.25493/pf48-73b
title: Probabilistic cytoarchitectonic map of Area Fo2 (OFC) (v5.0)

description: This dataset contains the distinct architectonic Area Fo2 (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 Fo2 (OFC). The probability map of Area Fo2 (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 Fo2 (OFC): Henssen et al. (2018) [Data set, v3.2] [DOI: 110.25493/N14D-JQT](https://doi.org/10.25493%2FN14D-JQT) Henssen et al. (2019) [Data set, v3.4] [DOI: 10.25493/3JB9-2V2](https://doi.org/10.25493%2F3JB9-2V2) The most probable delineation of Area Fo2 (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/a0xn-xc1
title: Whole-brain images of different neuronal markers

description: Whole-brain datasets obtained by using light-sheet microscopy in combination with tissue clearing. Each sample comes from a transgenic animal where interneurons of a selected type – parvalbumin (PV), somatostatin (SST), or vasoactive-intestinal peptide (VIP) – express the fluorescent protein tdTomato. Native resolution of data is 0.65x0.65x2 microns; downloadable data are downscaled to 10x10x10 microns to keep data size reasonable. Data are all from male animals, age P56.
DOI: 10.25493/6c7v-hkw
title: Laminar recordings from V1 of monkeys performing a figure-ground segregation task

description: This dataset contains electrophysiological data (Multi-unit activity and current-source density) from the different layers of V1 of macaque monkey during a figure-ground segregation task.
DOI: 10.25493/jq30-e08
title: Fiber structures of a human hippocampus based on joint DMRI, 3D-PLI, and TPFM acquisitions

description: The collected datasets provide real multimodal, multiscale structural connectivity insights into the human hippocampus. One post mortem hippocampus was scanned with Anatomical and Diffusion MRI (dMRI) [1], 3D Polarized Light Imaging (3D-PLI) [2], and Two-Photon Fluorescence Microscopy (TPFM) [3] using protocols specifically developed during SGA1 and SGA2, rendering joint tissue imaging possible. MRI scanning was performed with a 11.7 T Preclinical MRI system (gradients: 760 mT/m, slew rate: 9500 T/m/s) yielding T1-w and T2-w maps at 200 µm and dMRI-based maps at 300 µm resolution. During tissue sectioning (60 µm thickness) blockface (en-face) images were acquired from the surface of the frozen brain block, serving as reference for data integration/co-alignment. 530 brain sections were scanned with 3D-PLI. HPC-based image analysis provided transmittance, retardation, and fiber orientation maps at 1.3 µm in-plane resolution. TPFM was finally applied to selected brain sections utilizing autofluorescence properties of the fibrous tissue which appears after PBS washing (MAGIC protocol). The TPFM measurements provide a resolution of 0.44 µm x 0.44 µm x 1 µm. <br> [1] Beaujoin J, Palomero-Gallagher N, Boumezbeur F, Axer M, Bernard J, Poupon F, Schmitz D, Mangin JF, et al. (2018), **Post-mortem inference of the human hippocampal connectivity and microstructure using ultra-high field diffusion MRI at 11.7 T.** Brain Struct Funct 223:2157-2179. [DOI: 10.1007/s00429-018-1617-1](https://www.ncbi.nlm.nih.gov/pubmed/29387938) [2] Zeineh, M.M., Palomero-Gallagher, N., Axer, M., Gräβel, D., Goubran, M., Wree, A., Woods, R., Amunts, K., and Zilles, K. (2017). **Direct Visualization and Mapping of the Spatial Course of Fiber Tracts at Microscopic Resolution in the Human Hippocampus.** Cerebral Cortex 27, 1779-1794. [DOI: 10.1093/cercor/bhw010](https://www.ncbi.nlm.nih.gov/pubmed/?term=Cerebral+Cortex+27%2C+1779-1794.) [3] Costantini I, Menzel M, Silvestri L, Schubert N, Axer M, Amunts K, Pavone FS (2017). **Polarized Light Imaging and Two-Photon Fluorescence Microscopy correlative approach for 3D reconstruction of the orientation of myelinated fibers.** Optics in the Life Sciences Congress, Optical Society of America, San Diego, California. [DOI: 10.1364/BRAIN.2017.BrW4B.5](https://www.osapublishing.org/abstract.cfm?uri=BRAIN-2017-BrW4B.5)
DOI: 10.25493/7hx2-ajh
title: Probabilistic cytoarchitectonic map of Area 7A (SPL) (v8.4)

description: This dataset contains the distinct architectonic Area 7A (SPL) 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 7A (SPL). The probability map of Area 7A (SPL) 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 7A (SPL): Scheperjans et al. (2018) [Data set, v8.2] [DOI: 10.25493/MQ4V-YRR](https://doi.org/10.25493%2FMQ4V-YRR) The most probable delineation of Area 7A (SPL) 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/q1w6-t1b
title: Probabilistic map of the right inferior fronto-occipital fasciculus (atlas of deep white matter fibre bundles, version 2018)

description: This data contains the probability map of the right inferior fronto-occipital fasciculus (atlas of deep white matter fibre bundles, version 2018), in the MNI ICBM152 reference brain. This bundle was identified by fibre clustering, from the tractography datasets of 78 subjects in 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/yqcr-1dq
title: Density measurements of different receptors for dorsal part of Area 44 (IFG) [human, v1.0]

description: This dataset contains the densities (in fmol/mg protein) of receptors for classical neurotransmitters in dorsal part of Area 44 (IFG) obtained by means of quantitative _in vitro_ autoradiography. The receptor densities are visualized as _fingerprints_ (**fp**), which provide the mean density and standard deviation for each of the analyzed receptor types, averaged across samples. Overview of available measurements [ **receptor** \| **_neurotransmitter_** \| _labeling agent_ ]: **AMPA** \| **_glutamate_** \| _[<sup>3</sup>H]AMPA_ **kainate** \| **_glutamate_** \| _[<sup>3</sup>H]kainate_ **NMDA** \| **_glutamate_** \| _[<sup>3</sup>H]MK-801_ **mGluR2/3** \| **_glutamate_** \| _[<sup>3</sup>H]LY341495_ **GABA<sub>A</sub>** \| **_GABA_** \| _[<sup>3</sup>H]muscimol_ **GABA<sub>B</sub>** \| **_GABA_** \| _[<sup>3</sup>H]CGP54626_ **GABA<sub>A</sub>/BZ** \| **_GABA_** \| _[<sup>3</sup>H]flumazenil_ **muscarinic M<sub>1</sub>** \| **_acetylcholine_** \| _[<sup>3</sup>H]pirenzepine_ **muscarinic M<sub>2</sub>** \| **_acetylcholine_** \| _[<sup>3</sup>H]oxotremorine-M_ **muscarinic M<sub>3</sub>** \| **_acetylcholine_** \| _[<sup>3</sup>H]4-DAMP_ **nicotinic α<sub>4</sub>β<sub>2</sub>** \| **_acetylcholine_** \| _[<sup>3</sup>H]epibatidine_ **α<sub>1</sub>** \| **_noradrenalin/norepinephrine_** \| _[<sup>3</sup>H]prazosin_ **α<sub>2</sub>** \| **_noradrenalin/norepinephrine_** \| _[<sup>3</sup>H]UK-14,304_ **5-HT<sub>1A</sub>** \| **_serotonin_** \| _[<sup>3</sup>H]8-OH-DPAT_ **5-HT<sub>2</sub>** \| **_serotonin_** \| _[<sup>3</sup>H]ketanserin_ **D<sub>1</sub>** \| **_dopamine_** \| _[<sup>3</sup>H]SCH23390_ For exemplary samples, we also provide laminar _profiles_ (**pr**) and/or color-coded laminar _autoradiography_ images (**ar**). The density profiles provide, for a single tissue sample, an exemplary density distribution for a single receptor from the pial surface to the border between layer VI and the white matter. The autoradiography images show an exemplary density distribution of a single receptor for one laminar cross-section in a single tissue sample. Information on the used tissue samples and corresponding subjects for the receptor fingerprints, profiles and autoradiographs as well as a list of analyzed receptors accompanies the provided dataset. **For methodological details, see:** Zilles, K. et al. (2002). Quantitative analysis of cyto- and receptorarchitecture of the human brain, pp. 573-602. In: Brain Mapping: The Methods, 2nd edition (A.W. Toga and J.C. Mazziotta, eds.). San Diego, Academic Press. Palomero-Gallagher N, Zilles K. (2018) Cyto- and receptorarchitectonic mapping of the human brain. In: Handbook of Clinical Neurology 150: 355-387
DOI: 10.25493/jha2-acg
title: Density measurements of different receptors for Area 46 [human, v1.0]

description: This dataset contains the densities (in fmol/mg protein) of receptors for classical neurotransmitters in Area 46 obtained by means of quantitative _in vitro_ autoradiography. The receptor densities are visualized as _fingerprints_ (**fp**), which provide the mean density and standard deviation for each of the analyzed receptor types, averaged across samples. Overview of available measurements [ **receptor** \| **_neurotransmitter_** \| _labeling agent_ ]: **AMPA** \| **_glutamate_** \| _[<sup>3</sup>H]AMPA_ **kainate** \| **_glutamate_** \| _[<sup>3</sup>H]kainate_ **NMDA** \| **_glutamate_** \| _[<sup>3</sup>H]MK-801_ **mGluR2/3** \| **_glutamate_** \| _[<sup>3</sup>H]LY341495_ **GABA<sub>A</sub>** \| **_GABA_** \| _[<sup>3</sup>H]muscimol_ **GABA<sub>B</sub>** \| **_GABA_** \| _[<sup>3</sup>H]CGP54626_ **GABA<sub>A</sub>/BZ** \| **_GABA_** \| _[<sup>3</sup>H]flumazenil_ **muscarinic M<sub>1</sub>** \| **_acetylcholine_** \| _[<sup>3</sup>H]pirenzepine_ **muscarinic M<sub>2</sub>** \| **_acetylcholine_** \| _[<sup>3</sup>H]oxotremorine-M_ **muscarinic M<sub>3</sub>** \| **_acetylcholine_** \| _[<sup>3</sup>H]4-DAMP_ **nicotinic α<sub>4</sub>β<sub>2</sub>** \| **_acetylcholine_** \| _[<sup>3</sup>H]epibatidine_ **α<sub>1</sub>** \| **_noradrenalin/norepinephrine_** \| _[<sup>3</sup>H]prazosin_ **α<sub>2</sub>** \| **_noradrenalin/norepinephrine_** \| _[<sup>3</sup>H]UK-14,304_ **5-HT<sub>1A</sub>** \| **_serotonin_** \| _[<sup>3</sup>H]8-OH-DPAT_ **5-HT<sub>2</sub>** \| **_serotonin_** \| _[<sup>3</sup>H]ketanserin_ **D<sub>1</sub>** \| **_dopamine_** \| _[<sup>3</sup>H]SCH23390_ Information on the used tissue samples and corresponding subjects for the receptor fingerprints, profiles and autoradiographs as well as a list of analyzed receptors accompanies the provided dataset. **For methodological details, see:** Zilles, K. et al. (2002). Quantitative analysis of cyto- and receptorarchitecture of the human brain, pp. 573-602. In: Brain Mapping: The Methods, 2nd edition (A.W. Toga and J.C. Mazziotta, eds.). San Diego, Academic Press. Palomero-Gallagher N, Zilles K. (2018) Cyto- and receptorarchitectonic mapping of the human brain. In: Handbook of Clinical Neurology 150: 355-387
DOI: 10.25493/wbjx-2m0
title: From focal stroke to cortical islands: the impact of lesions on brain complexity and consciousness

description: The functional consequences of brain injury are known to depend on neuronal alterations extending beyond the area of structural damage. Although a lateralized EEG slowing over the injured hemisphere was known since the early days of clinical neurophysiology, its electrophysiological mechanisms were not systematically investigated. These EEG events reflect brief interruptions of neuronal firing (OFF-periods) that can occur locally and have prominent consequences on network and behavioral functions. Previous works, probing cortical circuits with transcranial magnetic stimulation coupled with EEG (TMS/EEG) proved as an effective way to reveal the tendency of cortical circuits to transiently plunge into silent OFF-periods. Here, using this approach, we show that the intact cortex surrounding focal brain injuries engages locally in pathological sleep-like dynamics. Specifically, we employed TMS/EEG in a cohort of ten conscious awake patients with chronic focal injuries of various etiologies. The data set consists of preprocessed TMS/EEG stimulus-responses (hundreds of trials per stimulus) and allows to perform complementary analysis with respect to the Perturbational Complexity Index used in this study.
DOI: 10.25493/568n-3ne
title: Probability map of bundle lh_Or-Ins_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 Orbitalis and Insula 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/kc38-ck5
title: 3D cyto- and receptor architectonic map of macaque primary motor area F2d

description: A multimodal analysis of the macaque motor cortex was carried out to create a 3D atlas integrating and reconciling discrepancies between previously published maps. This involved a quantitative and statistically testable approach to the analysis of cytoarchitecture in the macaque monkey frontal agranular cortex, in combination with an in vitro quantitative receptor autoradiographic analysis of the regional and laminar distribution patterns of 13 different neurotransmitter receptors. The borders of the identified areas were traced onto a reference macaque monkey brain in stereotaxic space. We provide here for the first time a map of lateral premotor area F2d of the macaque monkey brain integrating cyto- and receptor architectonic features in stereotaxic space. It constitutes a valuable resource for the analysis of functional experiments with non-human primates, and provides crucial data for modeling approaches with realistic synaptic dynamics.
DOI: 10.25493/40j8-tak
title: Probabilistic cytoarchitectonic map of Area 6d3 (SFS) (v4.0)

description: This dataset contains the distinct probabilistic cytoarchitectonic map of Area 6d3 (SFS) 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 6d3 (SFS). The probability map of Area 6d3 (SFS) 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 6d3 (SFS): Sigl et al. (2019) [Data set, v4.1] [DOI: 10.25493/NVJ5-JJ](https://doi.org/10.25493%2FNVJ5-JJ) The most probable delineation of Area 6d3 (SFS) 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/fa7b-666
title: Probabilistic cytoarchitectonic map of Area TeI (STG) (v6.0)

description: This dataset contains the distinct architectonic Area TeI (STG) 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 TeI (STG). The probability map of Area TeI (STG) 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 TeI (STG): Zachlod et al. (2019) [Data set, v5.1] [DOI: 10.25493/DTC3-EVM](https://doi.org/10.25493%2FDTC3-EVM) The most probable delineation of Area TeI (STG) 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) Amunts et al. (2021) [Data set, v2.6] [DOI: 10.25493/KJQN-AM0](https://doi.org/10.25493%2FKJQN-AM0)