cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25493/basp-tr
title: Anterograde visualization of projections from ventral and ventrolateral orbitofrontal cortex in rat (case: F31)

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. Two anterograde tracers, biotinylated dextran amine (BDA) and Phaseolus vulgaris-leucoagglutinin (PHA-L), were injected into the ventrolateral (VLOC) and ventral orbitofrontal cortex (VOC), respectively. Brain sections are 300 µm apart and 50 µm thick. The dataset contains two 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/z4rw-7dn
title: Density measurements of different receptors for Area Oc2L [rat, v1.0]

description: This dataset contains the densities (in fmol/mg protein) of receptors for classical neurotransmitters of Area Oc2L 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_ **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, 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/jbv5-j8j
title: Probabilistic cytoarchitectonic map of Area hIP8 (IPS) (v7.0)

description: This dataset contains the distinct probabilistic cytoarchitectonic map of Area hIP8 (IPS) 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 Area hIP8 (IPS). The probability map of Area hIP8 (IPS) 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 hIP8 (IPS): Richter et al. (2019) [Data set, v7.1] [DOI: 10.25493/YYT8-FT8](https://doi.org/10.25493%2FYYT8-FT8) The most probable delineation of Area hIP8 (IPS) 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/r7vy-xy6
title: Density measurements of different receptors for DG (Hippocampus) [rat, v1.0]

description: This dataset contains the densities (in fmol/mg protein) of receptors for classical neurotransmitters of DG (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_ 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/mkhd-xbj
title: Distribution of muscarinic acetylcholine receptors (type 2) in adult male C57Bl/J6 mice (coronal sections)

description: This dataset contains confocal image data of coronal sections following immunohistochemical staining for muscarinic acetylcholine receptor (type 2) – positive cells. These cells can facilitate the identification of the border between the primary visual cortex and the secondary visual cortex. According to Ji et al. (2015; “Modularity in the Organization of Mouse Primary Visual Cortex”, Neuron, 87, 632-643), layers IV and III in the primary visual cortex show very strong M2-expression levels, layers I, II and Vb moderate and layers VI and Va little to none. In the secondary visual cortex, layer IV shows only moderate expression levels allowing the identification of the border. Additionally, the primary somatosensory cortex shows stronger expression levels compared to its surrounding areas (e.g. secondary visual and somatosensory cortices) in layer IV. The temporal association area and area 36 of the perirhinal cortex show little to no expression in layer IV (see Wang et al., 2011, “Gateways of Ventral and Dorsal Streams in Mouse Visual Cortex”, Journal of Neuroscience, 31, 1905-1918).
DOI: 10.25493/td88-5aq
title: Probabilistic map of the posterior segment of the left arcuate fasciculus (atlas of deep white matter fibre bundles, version 2018)

description: This data contains the probability map of the posterior segment of the left arcuate 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/rehy-eex
title: Multiunit recordings from visual areas in monkeys performing a detection task

description: This dataset contains electrophysiological data (Multi-unit activity) from areas V1, V4 and dlPFC of macaque monkey during either a Contrast (visual) or Phosphene (electrical stimulation) detection task. The data is split in two zip files (Visual Stimulation and Electrical Stimulation), including scripts to generate images used in the associated article. See data-descriptor-00789 for further details.
DOI: 10.25493/t1fr-se
title: Probabilistic cytoarchitectonic map of Area 5L (SPL) (v9.0)

description: This dataset contains the distinct architectonic Area 5L (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 5L (SPL). The probability map of Area 5L (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 5L (SPL): Scheperjans et al. (2018) [Data set, v8.2] [DOI: 10.25493/A5V4-HFH](https://doi.org/10.25493%2FA5V4-HFH) Scheperjans et al. (2019) [Data set, v8.4] [DOI: 10.25493/C1FQ-2F](https://doi.org/10.25493%2FC1FQ-2F) The most probable delineation of Area 5L (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) 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/vwv1-fyy
title: Probabilistic cytoarchitectonic map of Area hIP1 (IPS) (v6.0)

description: This dataset contains the distinct probabilistic cytoarchitectonic map of Area hIP1 (IPS) 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 Area hIP1 (IPS). The probability map of Area hIP1 (IPS) 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 hIP1 (IPS): Choi et al. (2019) [Data set, v6.1] [DOI: 10.25493/92FE-7S6](https://doi.org/10.25493%2F92FE-7S6) The most probable delineation of Area hIP1 (IPS) 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/evm7-q3x
title: Input architecture of cortical parvalbumin interneurons: dendritic synaptome

description: We have developed an immunohistochemistry-correlated electron microscopy (EM) method - the "mirror" technique - by which long series of EM ultrathin sections can be obtained of neurochemically identified interneurons (INs) with the preservation of high-fidelity ultrastructure. This approach allows quantitative assessment of morphometric parameters of synaptic inputs along the whole length of dendrites originating from the parent soma. Adjoining sections always have cut cell bodies which appear on the facing surface of both sections. Using the mirror-technique, in one of the sections the histochemical marker of the GABAergic subtype, parvalbumin (PV) was revealed. After identifying immuno-positive neurons which were cut on the surface the remaining part of the very same cell bodies were identified on the surface of the adjoining section. Here we provide quantitative data on the synaptic coverage of one dendrite segments belonging to one PV immuno-positive IN. The spatial distribution of asymmetric and symmetric synapses, surface area and volume of the presynaptic boutons, area extent of the active zones and morphometric parameters of synaptic vesicles were determined.
DOI: 10.25493/vzj5-8wj
title: Probabilistic cytoarchitectonic map of Ch 4 (Basal Forebrain) (v4.2)

description: This dataset contains the distinct architectonic Ch 4 (Basal Forebrain) 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 Ch 4 (Basal Forebrain). The probability map of Ch 4 (Basal Forebrain) 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 Ch 4 (Basal Forebrain): Zaborszky et al. (2018) [Data set, v4.0] [DOI: 10.25493/BWZ1-5MV](https://doi.org/10.25493%2FBWZ1-5MV) The most probable delineation of Ch 4 (Basal Forebrain) 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) Amunts et al. (2021) [Data set, v2.6] [DOI: 10.25493/KJQN-AM0](https://doi.org/10.25493%2FKJQN-AM0)
DOI: 10.25493/5zvq-r8r
title: Probabilistic cytoarchitectonic map of Area FG1 (FusG) (v1.4)

description: This dataset contains the distinct architectonic Area FG1 (FusG) 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 FG1 (FusG). The probability map of Area FG1 (FusG) 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 FG1 (FusG): Caspers et al. (2018) [Data set, v1.2] [DOI: 10.25493/534D-V55](https://doi.org/10.25493%2F534D-V55) The most probable delineation of Area FG1 (FusG) 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/bq0h-znc
title: Probabilistic cytoarchitectonic map of Area 5Ci (SPL) (v8.2)

description: This dataset contains the distinct probabilistic cytoarchitectonic map of Area 5Ci (SPL) 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 5Ci (SPL). The probability map of Area 5Ci (SPL) 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 5Ci (SPL): Scheperjans et al. (2019) [Data set, v8.4] [DOI: 10.25493/SQVP-GK1](https://doi.org/10.25493%2FSQVP-GK1) The most probable delineation of Area 5Ci (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/k611-e89
title: Anterograde visualization of projections from medial orbitofrontal cortex in rat (case: F9)

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 medial orbitofrontal cortex (MOC). Brain sections are 300 µm apart and 50 µm thick. The dataset contains a complete series throughout the anterior-posterior 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: 10.34810/data72/364
title: 01CO_1.MR.0004.0196.2016.02.04.15.44.11.109375.67141750.IMA
DOI: 10.25493/thb5-b64
title: Probabilistic cytoarchitectonic map of Area 1 (PostCG) (v8.4)

description: This dataset contains the distinct architectonic Area 1 (PostCG) 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 1 (PostCG). The probability map of Area 1 (PostCG) 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 1 (PostCG): Geyer et al. (2018) [Data set, v8.2] [DOI: 10.25493/3D29-NJ7](https://doi.org/10.25493%2F3D29-NJ7) The most probable delineation of Area 1 (PostCG) 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/w5n5-pvx
title: Density measurements of different receptors for CA3 (Hippocampus) [human, v1.0]

description: This dataset contains the densities (in fmol/mg protein) of receptors for classical neurotransmitters in 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_ 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/ga16-m2p
title: Afferents of the perirhinal cortex (PRH) in mice

description: This dataset contains confocal image data of coronal sections following retrograde tract tracer injections (Cholera toxin (subunit b) conjugated with Alexa 594) in the perirhinal cortex in five adult male C57BL/J6 mice. The images show connections from other areas in the brain to the perirhinal cortex.