cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25493/mvwp-azr
title: Anterograde visualization of projections from lateral orbitofrontal cortex in rat (case: F19)

description: High-resolution bright-field microscopy images (44) 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 lateral orbitofrontal cortex (LOC). 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: 10.25493/57fa-vx6
title: Probabilistic cytoarchitectonic map of Area TI (STG) (v5.1)

description: This dataset contains the distinct architectonic Area TI (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 TI (STG). The probability map of Area TI (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. The most probable delineation of Area TI (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)
DOI: 10.25493/ztv5-m2h
title: Probability map of bundle rh_LOF-RMF_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 Lateral Orbitofrontal and Rostral Middle 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/v1qc-8a3
title: 3D cyto- and receptor architectonic map of macaque primary motor area F2v

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 F2v 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/xbn3-0s9
title: Probability map of bundle lh_SM-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 Supramarginal 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/at57-mnb
title: Probabilistic cytoarchitectonic map of Area TE 2.1 (STG) (v6.0)

description: This dataset contains the distinct architectonic Area TE 2.1 (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 TE 2.1 (STG). The probability map of Area TE 2.1 (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 TE 2.1 (STG): Zachlod et al. (2019) [Data set, v5.1] [DOI: 10.25493/R28N-2TD](https://doi.org/10.25493%2FR28N-2TD) The most probable delineation of Area TE 2.1 (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)
DOI: 10.25493/r156-8ca
title: Dendritic morphologies of four groups of mouse hippocampal interneurons

description: Computational modelling of hippocampal network mechanisms requires real-life morphological features of the dendritic arbors of interneurons (INs) in the CA1 area. There are several different groups of hippocampal interneurons. We investigated four groups. Hippocampo-septal (HS) INs project both locally and to the medial septum. Oriens-lacunosum-moleculare (OLM) INs are typical local feedback inhibitory neurons. Parvalbumin (PV)- and calretinin (CR)-containing INs represent two different groups of local INs. Here, using viral tracing and immunohistochemistry, we labeled these classes of INs and using scanning electron microscopy (SEM), we measured their dendritic cross-sectional areas and perimeters along the dendritic segments of these neurons. We estimated their volumes with and without mitochondria and estimated their dendritic surface areas as well. We measured and corrected all changes during tissue processing, therefore, all physical parameters represent the real life parameters of these dendrites.
DOI: 10.25493/kfq2-msa
title: Density measurements of different receptors for Area ifs4 (IFS) [human, v1.0]

description: This dataset contains the densities (in fmol/mg protein) of 17 receptors for classical neurotransmitters in Area ifs4 (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/ckyk-2ve
title: Density measurements of different receptors for CA, stratum moleculare (Hippocampus) [rat, v2.0]

description: This dataset contains the densities (in fmol/mg protein) of receptors for classical neurotransmitters of CA, stratum moleculare (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_ **muscarinic M<sub>1</sub>** \| **_acetylcholine_** \| _[<sup>3</sup>H]pirenzepine_ **muscarinic M<sub>2</sub>** \| **_acetylcholine_** \| _[<sup>3</sup>H]oxotremorine-M_ **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_ 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/c21w-ady
title: Left PMd subregions defined across CBP modalities

description: Despite the common conception of the dorsal premotor cortex (PMd) as a single brain region, its diverse connectivity profiles and behavioral heterogeneity argue for a differentiated organization of the PMd. In this study, the organization of PMd in the left hemisphere were defined by examining convergence across parcellations based on task-based functional connectivity, resting-state functional connectivity, and anatomical connectivity. The resulting PMd modules were then characterized based on multimodal functional connectivity and a quantitative analysis of associated behavioral functions. Analyzing the clusters consistent across all modalities revealed an organization of the left PMd that mirrored its right counterpart to a large degree. Caudal, central and rostral modules reflected a cognitive-motor gradient and a premotor eye-field was found in the ventral part of the left PMd. In addition, a distinct module linked to abstract cognitive functions was observed in the rostro-ventral left PMd across all CBP modalities, implying greater differentiation of higher cognitive functions for the left than the right PMd.
DOI: 10.25493/dj7v-ekb
title: 3-D point data representing the spatial distribution of corticopontine projections originating in the visual cortex of transgenic mice

description: The 3-D point coordinate data represent the spatial distribution of mouse brain subcortical projections from different parts of the visual cortex to the caudoputamen, thalamus, superior colliculus and pontine nuclei. The point data are derived from segmented images series programmatically downloaded from the Allen Brain Atlas Data Portal. The data are suited for 3-D visualization and comparison the spatial arrangement of visual corticostriatal, corticothalamic, corticocollicular, and corticopontine projections.
DOI: 10.25493/b87n-zdx
title: Interpolated 3D map of Area 6d3 (SFS) in the BigBrain

description: This dataset contains cytoarchitectonic maps of Area 6d3 (SFS) 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 6d3 (SFS) 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 6d3 (SFS) of the JuBrain Cytoarchitectonic Atlas, published in: Sigl et al. (2019) [Data set, v4.0] [DOI: 10.25493/40J8-TAK](https://doi.org/10.25493%2F40J8-TAK) Sigl et al. (2019) [Data set, v4.1] [DOI: 10.25493/NVJ5-JJ](https://doi.org/10.25493%2FNVJ5-JJ)
DOI: 10.25493/3445-ms1
title: Probability map of bundle rh_MT-ST_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 Middle Temporal and Superior 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.
DOI: 10.25493/w4wk-qsk
title: Probabilistic cytoarchitectonic map of CA1 (Hippocampus) (v11b.0)

description: This dataset contains the distinct probabilistic cytoarchitectonic map of CA1 (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 CA1 (Hippocampus). The probability map of CA1 (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 CA1 (Hippocampus): Palomero-Gallagher et al. (2020) [Data set, v11.1] [DOI: 10.25493/4A6X-6F0](https://doi.org/10.25493%2F4A6X-6F0) The most probable delineation of CA1 (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/x4ek-6wv
title: Probabilistic cytoarchitectonic map of Area PFcm (IPL) (v11.0)

description: This dataset contains the distinct architectonic Area PFcm (IPL) 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 PFcm (IPL). The probability map of Area PFcm (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 PFcm (IPL): Caspers et al. (2018) [Data set, v9.2] [DOI: 10.25493/G279-H6V](https://doi.org/10.25493%2FG279-H6V) Caspers et al. (2019) [Data set, v9.4] [DOI: 10.25493/8DP8-8HE](https://doi.org/10.25493%2F8DP8-8HE) The most probable delineation of Area PFcm (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/hj9m-8x2
title: Probability map of bundle lh_IP-LO_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 Inferior Parietal and Lateral Occipital 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/fhbk-r1v
title: Anterograde visualization of projections from ventral orbitofrontal cortex in rat (case: F23)

description: High-resolution bright-field microscopy images (43) 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 ventral orbitofrontal cortex (VOC). 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: 10.25493/3gmj-fez
title: 3D ultrastructural study of synapses using FIB/SEM in the human Entorhinal Cortex

description: We used Focused Ion Beam/Scanning Electron Microscopy (FIB/SEM) to perform a three-dimensional analysis of the synapses in the neuropil in different layers of the medial Entorhinal Cortex (EC) from human brain autopsies. Specifically, we studied synaptic structural parameters of synapses, which were fully reconstructed in 3D. We analyzed the synaptic density, 3D spatial distribution, and type (excitatory and inhibitory), as well as the shape and size of each synaptic junction. Moreover, the postsynaptic targets of synapses could be clearly determined. The present work constitutes a detailed description of the synaptic organization of the human EC, which is a necessary step to better understand the functional organization of this region in both health and disease.
DOI: 10.25493/h9a3-gft
title: E11.5 3D Edge-Aware Refined Atlas Derived from the Allen Developing Mouse Brain Atlas

description: 3D imaging necessitates corresponding 3D anatomical atlases, but generating such atlases is time consuming and challenging. Substantial efforts have generated such atlases including the Allen Developing Mouse Brain Atlas (ADMBA) but are typically limited by the process of serial 2D annotation for 3D reconstruction leading to artifacts. We have developed an automated, edge-aware atlas refinement method to curate existing atlases in a topologically consistent, 3D manner. Applying this approach to the E11.5 atlas in the ADMBA, we smoothed the labels in 3D and realigned labels to the underlying anatomical edges. We also rotated images in 3D and straightened a caudal kink in the spinal cord for midline symmetry, and we used the completed labels to strip regions outside of the central nervous system.
DOI: 10.34810/data72/368
title: 01CO_1.MR.0004.0086.2016.02.04.15.44.11.109375.67137340.IMA