cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25493/tk68-40p
title: Mapping of potentiated synapses in mouse hippocampus and organotypic hippocampal slices using SynActive constructs

description: Synaptic engrams are defined as the neural population sustaining a given memory and they can be considered the cellular basis of learning processes characterized by newly formed spines. Nowadays there are no tools able to detect engrams at synaptic level. We created a pair of Adeno Associate Viruses (AAV)-carried constructs to tag and visualize potentiated dendritic spines, in a spatially localized and activity-dependent manner. In a set of in vivo experiments, the pair was stereotaxically injected into the mouse hippocampus. Injected mice were exposed to contextual fear conditioning to trigger synaptic plasticity and potentiation. Confocal imaging of fixed brain sections allowed quantification of the distribution of potentiated spines along the dendritic tree of hippocampal pyramidal neurons. These data can be reused to implement computational models to infer synaptic plasticity rules leading to the formation of synaptic memory engrams. Second, we infected organotypic hippocampal slices with the AAV pair and then stimulated with chemical long-term potentiation. Confocal imaging of fixed organotypic slices reveals a strong SynActive signal (potentiated synapses), partially merged with the not-potentiated spines only in infected-stimulated organotypic slices compared to their controls (not infected cultures or infected-not stimulated, thus showing the specificity of the SynActive signal in potentiated synapses. Broadly, confocal imaging of fixed organotypic hippocampal slices allowed quantification of the distribution of potentiated spines along the dendritic tree of hippocampal pyramidal neurons. These data can be reused to implement computational models to infer synaptic plasticity rules leading to the formation of synaptic memory engrams.
DOI: 10.25493/dsvm-h3f
title: Probability map of bundle lh_CMF-PrC_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 Caudal Middle Frontal and Precentral regions of the Desikan-Killiany atlas, in the MNI ICBM152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fibre shape (fibre clustering), from the tractography datasets of 78 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fibre belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibres going through.
DOI: 10.25493/x7my-8n4
title: Anterograde visualization of projections from lateral orbitofrontal cortex in rat (case: F37)

description: High-resolution bright-field microscopy images (42) of serial coronal brain sections showing anterogradely labeled axons in orbitofrontal cortex (OFC) in a female adult Sprague Dawley rat. The anterograde tracer 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: 10.25493/81ev-zvt
title: Parcellation-based structural and resting-state functional brain connectomes of a healthy cohort

description: Nowadays, connectivity patterns of brain networks are of special interest, as they may reflect communication in the brain at the structural and functional levels. Their extraction, however, is a complex process that requires deep knowledge of magnetic resonance imaging (MRI) data processing methods. Furthermore, there is no consensus as to which parcellation of the brain is most suitable for a given analysis. Therefore, 19 different state-of-the-art cortical parcellations were used in this dataset to reconstruct the region-based empirical structural connectivity (representing the anatomy of axonal tracts) and functional connectivity (representing the temporal correlation between neuronal activity of brain regions) from diffusion-weighted (dwMRI) and resting-state functional magnetic resonance imaging (fMRI) data, respectively. The repository provides individual connectomes for 200 subjects from the Human Connectome Project. The data can be used by members of the neuroimaging community to investigate structural and functional human connectomes, and to extend the investigation to whole-brain models for further analyses of brain structure and function.
DOI: 10.25493/amw1-z16
title: Coronal section images series showing neuronal nuclei, calbindin and parvalbumin in the rat hippocampal region

description: Bright-field microscopy images of serial coronal brain sections showing neuronal nuclei (NeuN), calbindin and parvalbumin in an adult male Long Evans rat (case 1366), starting from the anterior hippocampus to the posterior end of the entorhinal cortex. The images show the detailed architecture of this complex brain region and enable identification of regional and subregional boundaries.
DOI: 10.25493/bvt0-h3u
title: Probabilistic cytoarchitectonic map of Area OP4 (POperc) (v9.4)

description: This dataset contains the distinct architectonic Area OP4 (POperc) in the MNI Colin 27 and MNI ICBM 152 reference spaces. As part of the Julich-Brain 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. 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 OP4 (POperc). The probability map of Area OP4 (POperc) 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 OP4 (POperc): Eickhoff et al. (2018) [Data set, v9.2] [DOI: 10.25493/51S0-K7W](https://doi.org/10.25493%2F51S0-K7W) Eickhoff et al. (2019) [Data set, v11.0] [DOI: 10.25493/99GW-N85](https://doi.org/10.25493%2F99GW-N85) The most probable delineation of Area OP4 (POperc) derived from the calculation of a maximum probability map of all currently released Julich-Brain brain structures can be found here: Amunts et al. (2019) [Data set, v1.13] [DOI: 10.25493/Q3ZS-NV6](https://doi.org/10.25493%2FQ3ZS-NV6) Amunts et al. (2019) [Data set, v1.18] [DOI: 10.25493/8EGG-ZAR](https://doi.org/10.25493%2F8EGG-ZAR) Amunts et al. (2020) [Data set, v2.2] [DOI: 10.25493/TAKY-64D](https://doi.org/10.25493/TAKY-64D)
DOI: 10.25493/6dys-m3w
title: Extraction of Parvalbumin positive cells from an Allen mouse brain in situ hybridisation experiment

description: Aim of project: To assign coordinates and quantify parvalbumin positive cells extracted from a series of brain section images obtained from the Allen Brain ISH repository. Study design: The image series was exported from the Allen Mouse Brain Atlas Data Portal, http://mouse.brain-map.org/experiment/show/75457579 (© 2004 Allen Institute for Brain Science. Allen Mouse Brain Atlas. Available from: mouse.brain-map.org). The series included images of 20 sagittal mouse brain sections from the left hemisphere labelled for parvalbumin by in situ hybridisation (Specimen 06-0419, Probe RP_060523_03_E07; Image credit: Allen Institute). Positive cells were identified by segmentation with the ilastik software. The section images were registered to reference atlas space with the QuickNII software and custom atlas maps were exported. Extracted features were quantified, localised and assigned coordinates with the Nutil software. Study output: 20 segmentation images 20 customised atlas maps 20 atlas maps with superimposed colour coded features A .json file with coordinates for visualising the parvalbumin positive cells in atlas space (Allen mouse brain Common Coordinate framework version 3). 2 reports (.docx) with quantifications per atlas region (1 report is for the whole brain, the other per section). Reference: Allen Mouse Brain Atlas. Lein, E.S. et al. (2007) Genome-wide atlas of gene expression in the adult mouse brain, Nature 445: 168-176. doi:10.1038/nature05453.
DOI: 10.25493/1bf1-0ev
title: Probability map of bundle lh_IP-IT_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 Inferior Parietal and Inferior 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: 10.34810/data72/379
title: 01CO_1.MR.0004.0178.2016.02.04.15.44.11.109375.67141029.IMA
DOI: 10.25493/dkcc-74t
title: Probabilistic cytoarchitectonic map of Area Id2 (Insula) (v8.0)

description: This dataset contains the distinct probabilistic cytoarchitectonic map of Area Id2 (Insula) 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 Id2 (Insula). The probability map of Area Id2 (Insula) 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 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 Id2 (Insula): Quabs et al. (2019) [Data set, v7.1] [DOI: 10.25493/377R-T96](https://doi.org/10.25493/377R-T96) The most probable delineation of Area Id2 (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/10.25493/8EGG-ZAR) 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: 10.25493/2e5c-pvm
title: Density measurements of different receptors for ventral part of Area hOc2 (V2, 18) [human, v1.0]

description: This dataset contains the densities (in fmol/mg protein) of receptors for classical neurotransmitters in the ventral part of Area hOc2 (V2, 18) 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_ For exemplary samples, we also provide laminar _profiles_ (**pr**) and/or color-coded laminar _autoradiography_ images (**ar**). The density profiles provide, for a single tissue sample, an exemplary density distribution for a single receptor from the pial surface to the border between layer VI and the white matter. 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, 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/gft3-w4m
title: Probability map of bundle lh_PoCi-PrCu_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 Posterior Cingulate and Precuneus 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: 10.25493/2gqm-h83
title: Structural covariance of thickness is organized along neurogenetic and neurodevelopmental axes

description: Structural covariance of regional cortical thickness reflects genetic processes, structural, and functional connectivity, and relates to individual differences in health and disorder ([Alexander-Bloch A et al. 2013](https://www.ncbi.nlm.nih.gov/pubmed/23531697)). Previous studies of the mammalian cortex have specified various natural dimensions of systematic variations in cortical features as a function of laminar differentiation, cytoarchitecture, gene expression, and functional connectivity ([Huntenburg JM et al. 2018](https://www.ncbi.nlm.nih.gov/pubmed/29203085)). These dimensions have behavioral ramifications ([Huntenburg JM et al. 2018](https://www.ncbi.nlm.nih.gov/pubmed/29203085)), and relate to the timing of neurogenesis and neurogenetic origin of cortical organization ([Sanides F 1962; Goulas A et al. 2019](https://www.springer.com/de/book/9783540028864)). Here, we studied the topology of structural covariance using a data-driven framework in humans and macaque monkeys and explore its genetic origin.
DOI: 10.25493/samm-ykz
title: Probabilistic cytoarchitectonic map of Area hOc3d (Cuneus) (v2.2)

description: This dataset contains the distinct probabilistic cytoarchitectonic map of Area hOc3d (Cuneus) 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 hOc3d (Cuneus). The probability map of Area hOc3d (Cuneus) 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 hOc3d (Cuneus): Kujovic et al. (2019) [Data set, v2.4] [DOI: 10.25493/F9X3-JVJ](https://doi.org/10.25493%2FF9X3-JVJ) The most probable delineation of Area hOc3d (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)
DOI: 10.25493/a2e4-kxy
title: 3D reconstructions of pyramidal cells in the human neocortex

description: 3D reconstructions of pyramidal cells in the human temporal neocortex in two different individuals (s-idab1 and s-idab2), and in the human neocortex from multiple cortical areas (cingular and frontal) in four different individuals (s-idif6, s-idif10, s-idif12 and s-idif16) was performed using Neurolucida software from 3D confocal stack of images. This dataset involves a total of 217 reconstructed cells: 94 in the temporal cortex, 64 in the cingular cortex and 59 in the frontal cortex.
DOI: 10.25493/5e7r-rb
title: Probabilistic cytoarchitectonic map of HC-Parasubiculum (Hippocampus) (v13.0)

description: This dataset contains the distinct architectonic HC-Parasubiculum (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 HC-Parasubiculum (Hippocampus). The probability map of HC-Parasubiculum (Hippocampus) 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. The most probable delineation of Entorhinal Cortex 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, v2.5] [DOI: 10.25493/8JKE-M53](https://doi.org/10.25493/8JKE-M53)
DOI: 10.25493/w97c-01r
title: Ca2+/calmodulin-dependent protein kinase II tetracycline-transactivator expression: coronal sections (case 317.8)

description: Bright-field microscopy images of serial coronal brain sections showing Ca2+/calmodulin-dependent protein kinase II (Camk2a) promoter expression in a bigenic Camk2a-tetracycline-transactivator (tTA) mouse brain (case 317.8, adult female), using a driver-reporter construct in which the Camk2a-tTA promoter regulates the expression of the E. coli derived LacZ reporter gene encoding β-galactosidase, which is visualized histologically using X-gal (5-Bromo-4-chloro-3-indolyl β-d-galactopyranoside) as a substrate. Methodological details are provided in Odeh et al., Neuroimage 54:2603-11, 2011. Our data show that the Camk2a-tTA promoter is spatially expressed in multiple brain regions, including the cerebral cortex, several basal ganglia regions, hippocampus, tectum, and cerebellum.
DOI: 10.25493/548a-c5k
title: Probability map of bundle rh_PoC-PrC_1 (atlas of superficial white matter fibre bundles, version 2018)

description: This data contains the probability map of a short fibre bundle connecting the right hemisphere Postcentral and Precentral regions of the Desikan-Killiany atlas, in the MNI ICBM152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fibre shape (fibre clustering), from the tractography datasets of 78 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fibre belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibres going through.
DOI: 10.25493/bpg7-360
title: Probabilistic cytoarchitectonic map of Area hOc5 (LOC) (v2.2)

description: This dataset contains the distinct probabilistic cytoarchitectonic map of Area hOc5 (LOC) 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 hOc5 (LOC). The probability map of Area hOc5 (LOC) 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 hOc5 (LOC): Malikovic et al. (2019) [Data set, v2.4] [DOI: 10.25493/2WSH-MCT](https://doi.org/10.25493%2F2WSH-MCT) The most probable delineation of Area hOc5 (LOC) 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)