cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25493/zgm0-4he
title: Probability map of bundle lh_LOF-Or_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 Lateral Orbitofrontal and Pars Orbitalis 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/mze0-bh5
title: Electrophysiological recordings of striatal projection neurons

description: Membrane voltage traces recorded from somata of striatal projection neurons in response to the square-pulse current injections.
DOI: 10.25493/k5hn-tfe
title: Widefield imaging of combined rehabilitation after stroke

description: We recorded time series of calcium activity of cortical pyramidal neurons with wide-field fluorescence microscopy. Increase in GCaMP6f fluorescence was indicative of an increase in neuronal activity. The mice were head restrained during the recording session. We recorded the activity in the right hemisphere while the mouse was performing a passive extension-active retraction of the left forelimb in a robotic device. The forces applied and the position of the forelimb is also recorded simultaneously. Subjects in "CTRL"-group are healthy animals, "STROKE" encloses injured animals, and "REHAB" encloses injured animals with received treatment. Recordings are made in the ipsilesional cortex (right hemisphere) during at least one week (5 sessions) of daily motor training, starting 26 days after injury for Stroke mice, 5 days after stroke for Rehab group and 5 days after the surgery for Ctrl animals. The subject "ChR2-17" is also described in: Conti, E., Sacconi, L., Pavone, F., & Allegra Mascaro, A. (2019). _Fluorescence cortical recording of mouse activity after stroke_ [Data set]. Human Brain Project Neuroinformatics Platform. DOI: 10.25493/Z9J0-ZZQ
DOI: 10.25493/necx-22s
title: Three-dimensional somatotopic organization of corticopontine projections from whisker representations in the rat primary somatosensory (barrel) cortex

description: 3D reconstructed point coordinate data representing the spatial relationships of rat corticopontine projections from different whisker representations in the barrel cortex, anterogradely labelled after dual tracer injections into electrophysiologically defined whisker barrels in the rat primary somatosensory cortex. The data demonstrate a 3D lamellar topographical pattern of corticopontine axonal clusters the pontine nuclei, and show that projections from whisker barrel in the same row overlap more than projections from different whisker barrel rows.
DOI: 10.25493/ewkv-ena
title: Regional and laminar distribution of receptors for norepinephrine in the rat brain

description: The present dataset provides the quantitative regional and laminar distribution of key molecules in signal transfer, namely the noradrenergic receptors α<sub>1</sub> and α<sub>2h</sub>, 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 prazosin and UK-14,304. 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: 10.25493/m6hx-ds9
title: 3D cyto- and receptor architectonic map of macaque area PFop of the inferior parietal lobe

description: A multimodal analysis of the macaque inferior parietal lobule 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 inferior parietal lobe, in combination with an in vitro quantitative receptor autoradiographic analysis of the regional and laminar distribution patterns of 15 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 area PFop 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/m1v0-we3
title: Whole cell patch-clamp recordings of cerebellar basket cells

description: This dataset provides a characterization of the electrophysiological properties of the cerebellar basket cells and investigation of their functions. Basket cells are inhibitory interneurons that receive excitatory input from parallel fibers and make synaptic inhibitory contacts with Purkinje cells. Whole-cell patch-clamp recordings were performed in order to reproduce the input/output relationships and to study the specific properties of the cells firing rate. The passive properties of the cells were extracted by analyzing current relaxation induced by step voltage changes (IV protocol), while the cellular spontaneous firing and the cellular responses to positive and negative current injections were acquired through gap free and CC step protocols, respectively. The experimental recordings provided data for the reconstruction of a biophysically realistic model of the basket cell.
DOI: 10.25493/fvby-84c
title: Ultrahigh resolution 3D cytoarchitectonic map of Area hOc2 (V2, 18) created by a Deep-Learning assisted workflow

description: This dataset contains automatically created cytoarchitectonic maps of Area hOc2 (V2, 18) in the BigBrain dataset [Amunts et al. 2013]. The mappings were created using Deep Convolutional Neural networks based on the idea presented in Spitzer et al. 2017 and Spitzer et al. 2018, which were trained on delineations on every 120th section created using the semi-automatic method presented in Schleicher et al. 1999. Mappings are available on every section. Their quality was observed by a trained neuroscientist to exclude sections with low quality results from further processing. Automatic mappings were then transformed to the 3D reconstructed BigBrain space using transformations used in Amunts et al. 2013, which were provided by Claude Lepage (McGill). Individual sections were used to assemble a 3D volume of the area, low quality results were replaced by interpolations between nearest neighboring sections. The volume was then smoothed using an 11³ median filter and largest connected components were identified to remove false positive results of the classification algorithm. The dataset consists of a single HDF5 file containing the volume in RAS dimension ordering and 20 micron isotropic resolution in the dataset “volume” and affine transformation matrix in the dataset “affine”. An additional dataset “interpolation_info” contains a vector with an integer value for each section which indicates if a section was interpolated due to low quality results (value 2) or not (value 1). Due to the large size of the volume, it’s recommended to view the data online using the provided viewer link.
DOI: 10.25493/r382-617
title: Probabilistic cytoarchitectonic map of Area TE 1.2 (HESCHL) (v5.1)

description: This dataset contains the distinct architectonic Area TE 1.2 (HESCHL) 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 1.2 (HESCHL). The probability map of Area TE 1.2 (HESCHL) 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 1.2 (HESCHL): Morosan et al. (2018) [Data set, v5.0] [DOI: 10.25493/T1WA-MBT](https://doi.org/10.25493%2FT1WA-MBT) The most probable delineation of Area TE 1.2 (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/k6ev-c42
title: GapMap Frontal I (v9.2)

description: This dataset contains the “Gap Map Frontal I” 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 “Gap Map Frontal I”. 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 “Gap Map Frontal I” 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 “Gap Map Frontal I” with progress in mapping. Other available data versions of Gap Map Frontal I: Amunts et al. (2020) [Data set, v9.0] [DOI: 10.25493/N6EZ-BRK](https://doi.org/10.25493%2FN6EZ-BRK) Amunts et al. (2020) [Data set, v9.1] [DOI: 10.25493/DQNE-MV3](https://doi.org/10.25493%2FDQNE-MV3) The most probable delineation of Gap Map Frontal I 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)
DOI: 10.25493/jhfd-863
title: Probabilistic cytoarchitectonic map of CA1 (Hippocampus) (v13.0)

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): Amunts et al. (2018) [Data set, v11b.0] [DOI: 10.25493/W4WK-QSK](https://doi.org/10.25493%2FW4WK-QSK) 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) 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/s4vd-n70
title: Probabilistic cytoarchitectonic map of CA3 (Hippocampus) (v13.0)

description: This dataset contains the distinct probabilistic cytoarchitectonic map of CA3 (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 CA3 (Hippocampus). The probability map of CA3 (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 CA3 (Hippocampus): Amunts et al. (2020) [Data set, v11b.0] [DOI: 10.25493/MQ0Y-22E](https://doi.org/10.25493/MQ0Y-22E) Palomero-Gallagher et al. (2020) [Data set, v13.0] [DOI: 10.25493/C546-GS0](https://doi.org/10.25493%2FC546-GS0) The most probable delineation of CA3 (Hippocampus) derived from the calculation of a maximum probability map of all currently released Julich-Brain brain structures can be found here: Amunts et al. (2019) [Data set, v1.13] [DOI: 10.25493/Q3ZS-NV6](https://doi.org/10.25493%2FQ3ZS-NV6) Amunts et al. (2020) [Data set, v2.2] [DOI: 10.25493/TAKY-64D](https://doi.org/10.25493/TAKY-64D) Amunts et al. (2020) [Data set, v2.4] [DOI: 10.25493/A7Y0-NX9](https://doi.org/10.25493%2FA7Y0-NX9) Amunts et al. (2020) [Data set, v2.5] [DOI: 10.25493/8JKE-M53](https://doi.org/10.25493/8JKE-M53)
DOI: 10.25493/bxgx-wm4
title: Distribution of parvalbumin-positive interneurons in the normal adult mouse brain

description: High-resolution bright-field microscopy images of horizontal brain sections showing parvalbumin positive neurons across the normal adult mouse brain. The dataset consists of image series covering the entire brain from four PVCre x Rosa26eYFP mice. For each brain, every fourth section was processed by diaminobenzidine (DAB) immunohistochemistry using a monoclonal parvalbumin (RRID:AB_2631173) antibody.
DOI: 10.25493/ejh3-xcq
title: Probabilistic cytoarchitectonic map of Area hOc4d (Cuneus) (v4.0)

description: This dataset contains the distinct architectonic Area hOc4d (Cuneus) 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 hOc4d (Cuneus). The probability map of Area hOc4d (Cuneus) 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 hOc4d (Cuneus): Kujovic et al. (2018) [Data set, v2.2] [DOI: 10.25493/KQ4Y-Q4M](https://doi.org/10.25493%2FKQ4Y-Q4M) Kujovic et al. (2019) [Data set, v2.4] [DOI: 10.25493/VSK5-DET](https://doi.org/10.25493%2FVSK5-DET) The most probable delineation of Area hOc4d (Cuneus) 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/vmwr-v5m
title: Anterograde visualization of projections from ventral orbitofrontal cortex in rat (case: F24)

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 Phaseolus vulgaris-leucoagglutinin (PHA-L) 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/xfhr-x41
title: Density measurements of different receptors for CA3 (Hippocampus) [human, v2.0]

description: This dataset contains the densities (in fmol/mg protein) of receptors for classical neurotransmitters of CA3 (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_ **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, 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 oDensity measurements of different receptors for DG (Hippocampus) [human, v2.0]f the human brain. In: Handbook of Clinical Neurology 150: 355-387
DOI: 10.34810/data72/375
title: 01CO_1.MR.0004.0089.2016.02.04.15.44.11.109375.67137460.IMA
DOI: 10.25493/84n0-2j6
title: Anterograde visualization of projections from ventral orbitofrontal cortex in rat (case: F17)

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 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/vw70-659
title: Cholinergic interneurons in the striatum - Single cell patch clamp recordings

description: The study entails the collection of single cell patch-clamp recordings, done in conjunction with morphological reconstructions, from cholinergic interneurons in the striatum.
DOI: 10.25493/2wnf-f8g
title: Probabilistic cytoarchitectonic map of Area PFop (IPL) (v11.0)

description: This dataset contains the distinct architectonic Area PFop (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 PFop (IPL). The probability map of Area PFop (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 PFop (IPL): Caspers et al. (2018) [Data set, v9.2] [DOI: 10.25493/XYBW-69Q](https://doi.org/10.25493%2FXYBW-69Q) Caspers et al. (2019) [Data set, v9.4] [DOI: 10.25493/M2PM-92Q](https://doi.org/10.25493%2FM2PM-92Q) The most probable delineation of Area PFop (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)