cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25493/dt51-fsr
title: Density measurements of different receptors for Area ifs3 (IFS) [human, v1.0]

description: This dataset contains the densities (in fmol/mg protein) of 17 receptors for classical neurotransmitters in Area ifs3 (IFS) 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. For exemplary samples, we also provide color-coded laminar autoradiography images (ar). 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 and autoradiographs as well as a list of analyzed receptors accompanies the provided dataset.
DOI: 10.25493/1pep-k9f
title: Multi-area recordings from visual and somatosensory cortices, perirhinal cortex and hippocampal CA1

description: The dataset includes spiking data from four areas (V2m, S1bf, perirhinal cortex, and hippocampal CA1) recorded simultaneously in freely moving rats during a spatial navigation task with visual discrimination and memory components. Position data of the animals during the task obtained from video tracking is also provided. A more detailed overview of the experimental design and data collection process can be found in [1].
DOI: 10.25493/taky-64d
title: Whole-brain parcellation of the Julich-Brain Cytoarchitectonic Atlas (v2.2)

description: This dataset contains the whole-brain parcellation of the Julich-Brain Cytoarchitectonic Atlas in the MNI Colin 27 as well as the MNI ICBM 152 2009c nonlinear asymmetric reference space ([Evans et al., 2012](https://www.sciencedirect.com/science/article/pii/S1053811912000419?via%3Dihub)). The parcellation is derived from the individual probability maps (PMs) of the cytoarchitectonic regions released in the Julich-Brain Cytoarchitectonic Atlas, that are further combined into a Maximum Probability Map (MPM). The MPM is calculated by considering for each voxel the probability of all cytoarchitectonic areas released in the atlas, and determining the most probable assignment ([Eickhoff 2005](https://www.sciencedirect.com/science/article/pii/S105381190400792X?via%3Dihub)). Gap maps complement cortical maps to achieve full cortical coverage. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets.
DOI: 10.25493/tffw-t6c
title: Regional and laminar distribution of receptors for acetylcholine in the rat brain

description: The present dataset provides the quantitative regional and laminar distribution of key molecules in signal transfer, namely the muscarinic acetylcholine M<sub>1</sub>, M<sub>2</sub> and M<sub>3</sub> receptors as well as the nicotinic acetylcholine α<sub>4</sub>β<sub>2</sub> receptor, in five selected rostrocaudal levels of the rat brain. The receptors were visualized by means of quantitative *in vitro* receptor autoradiography and the selective tritiated ligands pirenzepine, oxotremorine-M, 4-DAMP and epibatidine. The high spatial resolution of this method enables quantification of receptor densities in anatomically identifiable cortical structures as detailed as the hippocampal regions and layers, or subcortical structures such as amygdalar nuclei.
DOI: 10.34810/data72/380
title: 01CO_1.MR.0004.0143.2016.02.04.15.44.11.109375.67139625.IMA
DOI: 10.25493/g2re-7ph
title: Probabilistic cytoarchitectonic map of Dorsal Dentate Nucleus (Cerebellum) (v6.0)

description: This dataset contains the distinct probabilistic cytoarchitectonic map of Dorsal Dentate Nucleus (Cerebellum) 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 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 Dorsal Dentate Nucleus (Cerebellum). The probability map of Dorsal Dentate Nucleus (Cerebellum) 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 Dorsal Dentate Nucleus (Cerebellum): Tellmann et al. (2019) [Data set, v6.2] [DOI: 10.25493/M5QG-SHH](https://doi.org/10.25493%2FM5QG-SHH) The most probable delineation of Dorsal Dentate 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)
DOI: 10.25493/jg1k-5d5
title: Probability map of bundle rh_SP-SM_0 (atlas of superficial white matter fibre bundles, version 2018)

description: This data contains the probability map of a short fibre bundle connecting the right hemisphere Superior Parietal and Supramarginal 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: 10.25493/1exr-288
title: Morphological reconstructions and electrophysiological data from mouse hippocampal neurons

description: Understanding cortical circuits requires the characterization of their constituent neurons. Using whole-cell recordings in acute hippocampal slices, followed by confocal imaging and 3D reconstruction, a database of the morphological and physiological properties of hippocampal neurons in the adult mouse has been constructed. The database currently contains approximately 200 morphological reconstructions and 500 recordings from partially overlapping cell populations.
DOI: 10.25493/96j9-bvv
title: GapMap Temporal to Parietal (v9.0)

description: This dataset contains the “GapMap Temporal to Parietal" in the individual, single subject template of the MNI Colin 27 as well as the MNI ICBM 152 2009c nonlinear asymmetric reference space. In order to provide whole-brain coverage for the cortex within the Julich-Brain Atlas, yet uncharted parts of the frontal cortex have been combined to the brain region “GapMap Temporal to Parietal”. The distributions were modeled so that probabilistic gap maps were computed in analogy to other maps of the Julich-Brain Atlas. The probabilistic map of “GapMap Temporal to Parietal” 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. New maps are continuously replacing parts of “GapMap Temporal to Parietal” with progress in mapping. The most probable delineation of GapMap Temporal to Parietal 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)
DOI: 10.25493/hzr9-ckv
title: Anterograde visualization of projections from medial orbitofrontal cortex in rat (case: F3)

description: High-resolution bright-field microscopy images (42) of serial coronal brain sections showing anterogradely labeled axons in orbitofrontal cortex (OFC) in a female adult Sprague Dawley rat. The anterograde tracer Phaseolus vulgaris-leucoagglutinin (PHA-L) was injected into the medial orbitofrontal cortex (MOC). Brain sections are 300 µm apart and 50 µm thick. The dataset contains a complete series throughout the anterior-posterior extent of the brain, contributing to visualization of a topographically organized connectivity from OFC throughout the brain, including the published data on a topographically organized projection to the parahippocampal areas.
DOI: 10.25493/w8e5-k1y
title: Probabilistic cytoarchitectonic map of Area 4p (PreCG) (v11.0)

description: This dataset contains the distinct architectonic Area 4p (PreCG) 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 4p (PreCG). The probability map of Area 4p (PreCG) 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 4p (PreCG): Geyer et al. (2018) [Data set, v9.2] [DOI: 10.25493/ECYA-0D1](https://doi.org/10.25493%2FECYA-0D1) Geyer et al. (2019) [Data set, v9.4] [DOI: 10.25493/5HSF-81J](https://doi.org/10.25493%2F5HSF-81J) The most probable delineation of Area 4p (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)
DOI: 10.25493/ym3r-9sp
title: Reference delineations of Area ifs1 (IFS) in individual sections of the BigBrain

description: This dataset contains cytoarchitectonic maps of Area ifs1 (IFS) in the BigBrain. The mappings were created using cytoarchitectonic criteria applied on digitized histological sections of 1 µm resolution, cut in coronal plane. Areal borders have been detected by an oberserver-independent border definition (Schleicher 2000). Mappings are available on sections of the BigBrain and have been transformed to the 3D reconstructed BigBrain space using the transformations used in Amunts et al. 2013. From these delineations, a preliminary 3D map of Area ifs1 (IFS) 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.
DOI: 10.25493/p9ew-e2t
title: Probability map of bundle lh_PoC-SM_1 (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 Postcetnral and Supramarginal 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: 10.25493/38an-nz6
title: Probability map of bundle lh_RMF-SF_1 (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 Rostral Middle Frontal 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/p8xr-f6f
title: Quantitative ultrastructural analysis of the synapses established by thalamocortical axons in the sensorimotor cortex

description: We analyzed and quantified different parameters from the synapses established by thalamocortical axons coming from two thalamic nuclei (ventral posteromedial and posterior nuclei) in the somatosensory and motor cortex. This dataset contains pictures from two types of ultrastructural analysis: serial transmission and focused ion beam milling scanning electron microscopy. Thalamocortical axons analyzed in the dataset were labeled with ionthophoretic injections of biotinylated 10 K dextran amine (anterograde tracer) in a small number of neurons and revealed with the glucose oxidase-diaminobenzidine method. Experiments were conducted in vivo in wildtype C57BL/6 adult animals.
DOI: 10.25493/yjfw-hpy
title: Excitability profile of CA1 pyramidal neurons in APPPS1 Alzheimer disease mice and control littermates

description: In this study we analyzed the intrinsic electrophysiological properties of CA1 excitatory hippocampal neurons in a mouse model of Alzheimer’s Disease (AD) at two age points: a presymptomatic age (3-4 months) and a symptomatic age: (9-10 months). At this latter age, this APPPS1 model harbors amyloid plaques and hippocampus-dependent cognitive alterations. Little is known about the excitability alterations in the hippocampus that correlate to these cognitive deficits. Using patch clamp electrophysiology we recorded CA1 pyramidal neurons from control littermates (Wild types) and APPPS1 slices of hippocampus at these two age points. We provide these data for HBP users.
DOI: 10.25493/tfy5-0r4
title: Density measurements of different receptors for CA2 (Hippocampus) [human, v1.0]

description: This dataset contains the densities (in fmol/mg protein) of receptors for classical neurotransmitters in CA2 (Hippocampus) 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_ **GABA<sub>A</sub>** \| **_GABA_** \| _[<sup>3</sup>H]muscimol_ **GABA<sub>B</sub>** \| **_GABA_** \| _[<sup>3</sup>H]CGP54626_ Information on the used tissue samples and corresponding subjects, as well as 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: 10.25493/9nh1-5pw
title: Probability map of bundle lh_CMF-PrC_1 (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 Caudal Middle Frontal and Precentral 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: 10.25493/4n6f-vcg
title: Probabilistic cytoarchitectonic map of Area PFt (IPL) (v11.0)

description: This dataset contains the distinct architectonic Area PFt (IPL) 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 PFt (IPL). The probability map of Area PFt (IPL) 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 PFt (IPL): Caspers et al. (2018) [Data set, v9.2] [DOI: 10.25493/2PNK-M62](https://doi.org/10.25493%2F2PNK-M62) Caspers et al. (2019) [Data set, v9.4] [DOI: 10.25493/JGM9-ZET](https://doi.org/10.25493%2FJGM9-ZET) The most probable delineation of Area PFt (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) 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/m4bv-2ah
title: Anterograde visualization of projections from ventrolateral orbitofrontal cortex in rat (case: F33)

description: High-resolution bright-field microscopy images (41) of serial coronal brain sections showing anterogradely labeled axons in orbitofrontal cortex (OFC) in a female adult Sprague Dawley rat. The anterograde tracer biotinylated dextran amine (BDA) was injected into the ventrolateral orbitofrontal cortex (VLOC). Brain sections are 300 µm apart and 50 µm thick. The dataset contains a complete series throughout the anterior-posterior extent of the brain, contributing to visualization of a topographically organized connectivity from OFC throughout the brain, including the published data on a topographically organized projection to the parahippocampal areas.
DOI: 10.25493/f8w5-hnb
title: Probabilistic cytoarchitectonic map of Area OP2 (POperc) (v9.2)

description: This dataset contains the distinct probabilistic cytoarchitectonic map of Area OP2 (POperc) 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 OP2 (POperc). The probability map of Area OP2 (POperc) 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 OP2 (POperc): Eickhoff et al. (2019) [Data set, v9.4] [DOI: 10.25493/5KBV-36J](https://doi.org/10.25493%2F5KBV-36J) Eickhoff et al. (2020) [Data set, v11.0] [DOI: 10.25493/SDW0-YEZ](https://doi.org/10.25493%2FSDW0-YEZ) The most probable delineation of Area OP2 (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: 10.25493/6rwd-6km
title: Maps of neurons stained with anti-NeuN antibody

description: This dataset is about 3D-imaging at high resolution of NeuN expressing neurons of selected regions (area 17 of visual cortex) of human brain. The dataset contains the final fused volume in tiff and MP4 format, the originally acquired 3D stacks, as well as the stitching file generated by ZetaStitcher.
DOI: 10.25493/mef4-c1v
title: Probability map of bundle rh_IT-MT_1 (atlas of superficial white matter fibre bundles, version 2018)

description: This data contains the probability map of a short fibre bundle connecting the right hemisphere Inferior Temporal and Middle Temporal 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.