cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25493/b2e3-jqr
title: Probabilistic cytoarchitectonic map of Area Id7 (Insula) (v6.0)

description: This dataset contains the distinct probabilistic cytoarchitectonic map of Area Id7 (Insula) 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 Id7 (Insula). The probability map of Area Id7 (Insula) 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 Id7 (Insula): Amunts et al. (2019) [Data set, v6.1] [DOI: 10.25493/88QG-JMS](https://doi.org/10.25493%2F88QG-JMS) The most probable delineation of Area Id7 (Insula) 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: 10.25493/9bhd-wdp
title: Paxinos and colleagues' “MRI/DTI Atlas of the Rat Brain” (1st edition) spatially registered to the Waxholm Space atlas of the rat brain

description: The dataset contains location metadata defining the spatial registration of the 1st edition of “MRI/DTI Atlas of the Rat Brain” (Paxinos et al, 2015) to the MRI/DTI image volume of the Waxholm Space atlas of the rat brain (Version 1.01; RRID:SCR017124). The stereotaxic atlas of Paxinos and colleagues contains 96 coronal diagrams drawn based on slices through an averaged MRI/DTI image volume from five adult Wistar rats. The schematic diagram images were spatially registered to the Waxholm Space atlas of the rat brain. The dataset consists of an .xml file with spatial metadata that can be opened in the QuickNII tool (RRID:SCR016854) to view overlay images of the two atlases. The atlas images are not shared due to copyright restrictions, but the user can use own images together with the .xml file provided here, following the procedure provided in the accompanying data descriptor file. The dataset can be used for direct comparison of anatomical landmarks and spatial correspondences of brain region delineated in the two atlases.
DOI: 10.25493/h836-w4n
title: Molecular fingerprinting of potentiated synapses using an activity-dependent probe for proteomics

description: We created a pair of AAV-carried constructs to immunoprecipitate the interactome of the synaptic hub protein PSD95 specifically at potentiated synapses, or from the whole synaptic bulk. Either AAV was stereotaxically injected into the mouse hippocampus. Injected mice were exposed to contextual fear conditioning to trigger synaptic plasticity and potentiation. Immunoprecipitation was then performed and samples were processed for mass spectrometry. These data can be reused to implement computational models of the structural features differentiating a potentiated synapse from a basally active one, thus providing a molecular basis for memory at the synaptic scale.
DOI: 10.25493/6b87-wrq
title: Probabilistic cytoarchitectonic map of Area 5Ci (SPL) (v9.0)

description: This dataset contains the distinct architectonic Area 5Ci (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 5Ci (SPL). The probability map of Area 5Ci (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 5Ci (SPL): Scheperjans et al. (2018) [Data set, v8.2] [DOI: 10.25493/BQ0H-ZNC](https://doi.org/10.25493%2FBQ0H-ZNC) 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) 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: 10.25493/5dpt-p6v
title: 3D reconstructions of mouse striatal and cerebellar neurons

description: We have produced 3D reconstructions of D1 striatal neurons and Stellate, Basket, Golgi and Granular neurons of the cerebellum of the mouse using Neurolucida software from 3D confocal stack of images. Data from 3D reconstructions will be useful to modeling and integration of anatomical data with functional studies in these brain regions.
DOI: 10.25493/a4qs-825
title: Probability map of bundle rh_IP-MT_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 Inferior Parietal 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.
DOI: 10.25493/mdar-xeb
title: Recordings of cerebellar granule cells current-voltage relations

description: Study and characterization of the intrinsic properties of granule cells.
DOI: 10.25493/16nk-ky1
title: Probabilistic cytoarchitectonic map of HATA (Hippocampus) (v13.0)

description: This dataset contains the distinct architectonic HATA (Hippocampus) 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 HATA (Hippocampus). The probability map of HATA (Hippocampus) 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 HATA (Hippocampus): Amunts et al. (2018) [Data set, v11b.0] [DOI: 10.25493/VHFH-N2](https://doi.org/10.25493%2FVHFH-N2) Amunts et al. (2019) [Data set, v11.1] [DOI: 10.25493/M1XP-VSQ](https://doi.org/10.25493%2FM1XP-VSQ) The most probable delineation of HATA (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. (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: 10.25493/4sfg-tx
title: Density measurements of different receptors for stratum cellulare of CA (Hippocampus) [human, v1.0]

description: This dataset contains the densities (in fmol/mg protein) of receptors for classical neurotransmitters in stratum cellulare of CA (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/ptkw-r7w
title: Probabilistic cytoarchitectonic map of Area Fp1 (FPole) (v2.4)

description: This dataset contains the distinct architectonic Area Fp1 (FPole) 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 Fp1 (FPole). The probability map of Area Fp1 (FPole) 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 Fp1 (FPole): Bludau et al. (2018) [Data set, v2.2] [DOI: 10.25493/RPDP-VMG](https://doi.org/10.25493%2FRPDP-VMG) The most probable delineation of Area Fp1 (FPole) 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: 10.34810/data72/349
title: 01CO_1.MR.0004.0207.2016.02.04.15.44.11.109375.67142191.IMA
DOI: 10.25493/czta-p58
title: Probabilistic cytoarchitectonic map of Area 6mp (SMA, mesial SFG) (v9.0)

description: This dataset contains the distinct probabilistic cytoarchitectonic map of Area 6mp (SMA, mesial SFG) 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 6mp (SMA, mesial SFG). The probability map of Area 6mp (SMA, mesial SFG) 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 6mp (SMA, mesial SFG): Ruan et al. (2019) [Data set, v9.1] [DOI: 10.25493/2E1T-47F](https://doi.org/10.25493%2F2E1T-47F) The most probable delineation of Area 6mp (SMA, mesial SFG) 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/x71t-hz
title: Density measurements of different receptors for Area PGp (IPL) [human, v1.0]

description: This dataset contains the densities (in fmol/mg protein) of receptors for classical neurotransmitters in Area PGp (IPL) obtained by means of quantitative _in vitro_ autoradiography. The receptor densities are visualized as _fingerprints_ (**fp**), which provide the mean density and standard deviation for each of the analyzed receptor types, averaged across samples. Overview of available measurements [ **receptor** \| **_neurotransmitter_** \| _labeling agent_ ]: **AMPA** \| **_glutamate_** \| _[<sup>3</sup>H]AMPA_ **kainate** \| **_glutamate_** \| _[<sup>3</sup>H]kainate_ **NMDA** \| **_glutamate_** \| _[<sup>3</sup>H]MK-801_ **mGluR2/3** \| **_glutamate_** \| _[<sup>3</sup>H]LY341495_ **GABA<sub>A</sub>** \| **_GABA_** \| _[<sup>3</sup>H]muscimol_ **GABA<sub>B</sub>** \| **_GABA_** \| _[<sup>3</sup>H]CGP54626_ **GABA<sub>A</sub>/BZ** \| **_GABA_** \| _[<sup>3</sup>H]flumazenil_ **muscarinic M<sub>1</sub>** \| **_acetylcholine_** \| _[<sup>3</sup>H]pirenzepine_ **muscarinic M<sub>2</sub>** \| **_acetylcholine_** \| _[<sup>3</sup>H]oxotremorine-M_ **muscarinic M<sub>3</sub>** \| **_acetylcholine_** \| _[<sup>3</sup>H]4-DAMP_ **nicotinic α<sub>4</sub>β<sub>2</sub>** \| **_acetylcholine_** \| _[<sup>3</sup>H]epibatidine_ **α<sub>1</sub>** \| **_noradrenalin/norepinephrine_** \| _[<sup>3</sup>H]prazosin_ **α<sub>2</sub>** \| **_noradrenalin/norepinephrine_** \| _[<sup>3</sup>H]UK-14,304_ **5-HT<sub>1A</sub>** \| **_serotonin_** \| _[<sup>3</sup>H]8-OH-DPAT_ **5-HT<sub>2</sub>** \| **_serotonin_** \| _[<sup>3</sup>H]ketanserin_ **D<sub>1</sub>** \| **_dopamine_** \| _[<sup>3</sup>H]SCH23390_ Information on the used tissue samples and corresponding subjects for the receptor fingerprints, profiles and autoradiographs as well as a list of analyzed receptors accompanies the provided dataset. **For methodological details, see:** Zilles, K. et al. (2002). Quantitative analysis of cyto- and receptorarchitecture of the human brain, pp. 573-602. In: Brain Mapping: The Methods, 2nd edition (A.W. Toga and J.C. Mazziotta, eds.). San Diego, Academic Press. Palomero-Gallagher N, Zilles K. (2018) Cyto- and receptorarchitectonic mapping of the human brain. In: Handbook of Clinical Neurology 150: 355-387
DOI: 10.25493/tt2y-23n
title: Brain-wide quantitative data on calbindin positive neurons in the mouse

description: This dataset contains quantitative data extracted from four sets of calbindin stained sections covering the whole brain of normal, adult C57BL6/J mice. Section images from the dataset “Distribution of calbindin-positive interneurons in the normal adult mouse brain” [1] were analysed using the QUINT workflow. The dataset includes numbers and densities of cells for brain regions defined according to the Allen Mouse brain Common Coordinate Framework (CCF) and point coordinate data representing labelled cells across the brain. A detailed description of the number and distribution on calbindin neurons across brain regions is given in the related publication. To facilitate re-use of the data, the dataset furthermore includes atlas maps and segmented images in .png format and .nut files used to run the analyses. References: 1. Bjerke, I. & Leergaard, T. Distribution of calbindin positive neurons in the normal adult mouse brain. EBRAINS (2020) https://doi.org/10.25493/KHNT-KV8.
DOI: 10.25493/9wbs-pk4
title: NLG3KO mice exhibit deficits in social behavior

description: Autism spectrum disorders (ASDs) comprise a heterogeneous group of neuro-developmental abnormalities with a strong genetic component, characterized by deficits in verbal and non-verbal communication, impaired social interactions, and stereotyped behaviors. In a small percentage of cases, ASDs are associated with alterations of genes involved in synaptic function. Among these, relatively frequent are mutations/deletions of genes encoding for neuroligins (NLGs). NLGs are postsynaptic adhesion molecules that, interacting with their presynaptic partners neurexins, ensure the cross talk between pre- and postsynaptic specializations and synaptic stabilization, a condition needed for maintaining a proper excitatory/inhibitory balance within local neuronal circuits. We have focused on mice lacking NLG3 (NLG3 knock-out mice), animal models of a non-syndromic form of autism, which exhibit deficits in social behavior reminiscent of those found in ASDs. Data obtained in our experiments can be used by researchers to understand social deficits induced by lack of Neuroligin 3 protein.
DOI: 10.5281/zenodo.5115230
title: Genetic disruption of synthesis pathways of Arabidopsis secondary metabolites dramatically affects root-associated nematode populations directly and via modulation of microbial communities

description: Dataset of nematode, fungal and bacterial sequence reads of Arabidopsis roots. Dataset of fungal and bacterial sequence reads of Arabidopsis microbial suspension. DNA concentration of Arabidopsis root microbial suspension. Meloidogyne incognita J2 invasion into tomato roots. qPCR dataset of Meloidogyne hapla infection pressure into Arabidopsis roots.
DOI: 10.25493/p4dw-4rn
title: Density measurements of different receptors for CA, stratum cellulare (Hippocampus) [rat, v2.0]

description: This dataset contains the densities (in fmol/mg protein) of receptors for classical neurotransmitters of CA, stratum cellulare (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: 10.5281/zenodo.5115229
title: Genetic disruption of synthesis pathways of Arabidopsis secondary metabolites dramatically affects root-associated nematode populations directly and via modulation of microbial communities

description: Dataset of nematode, fungal and bacterial sequence reads of Arabidopsis roots. Dataset of fungal and bacterial sequence reads of Arabidopsis microbial suspension. DNA concentration of Arabidopsis root microbial suspension. Meloidogyne incognita J2 invasion into tomato roots. qPCR dataset of Meloidogyne hapla infection pressure into Arabidopsis roots.
DOI: 10.25493/91qd-8nc
title: Regional and laminar distribution of dopamine receptors and uptake sites in the rat brain

description: The present dataset provides the quantitative regional and laminar distribution of key molecules in signal transfer, namely the dopamine receptors D<sub>1</sub> and D<sub>2</sub>, as well as the dopamine uptake sites 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 SCH 23390, racloprid and mazindol. 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/rnqp-f5u
title: Reference delineations of Area ifs3 (IFS) in individual sections of the BigBrain

description: This dataset contains cytoarchitectonic maps of Area ifs3 (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 ifs3 (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.