cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25493/y12f-ymu
title: Probabilistic cytoarchitectonic map of Area 5M (SPL) (v8.4)

description: This dataset contains the distinct architectonic Area 5M (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 5M (SPL). The probability map of Area 5M (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 5M (SPL): Scheperjans et al. (2018) [Data set, v8.2] [DOI: 10.25493/CG41-Q6U](https://doi.org/10.25493%2FCG41-Q6U) The most probable delineation of Area 5M (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/n490-vmf
title: Input architecture of cortical calretinin 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, calretinin (CR) 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 two dendrite segments belonging to two CR immuno-positive INs. 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: 10.25493/534d-v55
title: Probabilistic cytoarchitectonic map of Area FG1 (FusG) (v1.2)

description: This dataset contains the distinct probabilistic cytoarchitectonic map of Area FG1 (FusG) 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 FG1 (FusG). The probability map of Area FG1 (FusG) 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 FG1 (FusG): Caspers et al. (2019) [Data set, v1.4] [DOI: 10.25493/5ZVQ-R8R](https://doi.org/10.25493%2F5ZVQ-R8R) 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: 10.25493/2xww-k4y
title: Metadata Schema of Common Data Elements for Traumatic Brain Injury (v4)

description: Data in the Medical Informatics Platform (MIP) resides in hospital servers and never leaves the hospital. Analyses and experiments are executed with respect to that principle while preserving patients’ anonymity making it infeasible for their identity to be inferred. Hospitals importing their data to the Medical Informatics Platform join a federation so as to run analyses on data from other hospital nodes as well. Each federation in the MIP refers to a specific Medical Condition. Here the metadata for the federation of hospitals that studies traumatic brain injury is presented. This metadata schema, consisting of a total of 17 variables, has the following main variable categories: **1. Demographics** - 2 variables for basic demographic information that does not reveal patient’s identity **2. Neurological assessment** - 6 variables for Glasgow Coma Scale1 and pupil reactivity scores **3. Imaging** - 4 multinomial variables for cisternal compression, epidural hematoma, midline shift, marshall classification **4. Second insults** - 2 variables for hypoxic and hypotensive episodes **5. Outcomes** - 1 variable for the Glasgow Outcome Scale Extended score **6. Laboratory tests** - Values of glucose and hemoglobin level The metadata viewing and management is done by Data Catalogue, a central web portal of MIP. Data Catalogue offers presentation, search and hierarchical visualisation of metadata information for datasets imported into the MIP while providing metadata management features to authorized users. One of its features is parsing metadata descriptions in XLSX files and generating their equivalent in a hierarchical JSON format which the MIP uses. In this repository we upload metadata in both XLSX and the generated JSON format. A new data version of Metadata Schema of CDE for TBI can be found here: Muraleedharan et al. (2020) [Data set, v5] [DOI: 10.25493/YBY9-QA](https://kg.ebrains.eu/search/instances/Dataset/a526f0c6-cbd4-4864-ae3a-87ad2cb7496a)
DOI: 10.25493/x4mv-59j
title: Pathway-Specific Genetic Risk Scores for Alzheimer’s Disease to Differentiate Regional Cortical Atrophy in Older Adults

description: Brain aging is highly variable and represents a challenge to delimit aging from disease processes. Moreover, genetic variation may influence both aging and disease. Here we used a genetic risk score (GRS) based on twenty loci previously identified to be associated with late-onset Alzheimer’s disease (AD) at genome-wide significance and evaluated the polygenic effects on cortical thickness (CT) of older adults from a population cohort (1000BRAINS). The aim was to develop a genetically informed predictor that helps to differentiate disease-associated from aging-associated regional atrophy in the cerebral cortex. The presented data reflect the allelic scoring information to calculate six pathway-specific GRS (cholesterol metabolism, APP metabolism, MAPT metabolism, cytoskeleton/axon development, immune response, endocytosis), and a total GRS (total) that summarizes the effects across all pathways.
DOI: 10.25493/82ya-0hu
title: 7T-fMRI data to study mental imagery and illusory perception in the layers of human primary visual cortex (V1)

description: This data set is from the mental imagery and illusory perception project, currently pre-published on bioRxiv under the title “Two distinct feedback codes in V1 for ‘real’ and ‘imaginary’ internal experiences”, see [https://www.biorxiv.org/content/biorxiv/early/2019/06/13/664870.full.pdf](https://www.biorxiv.org/content/biorxiv/early/2019/06/13/664870.full.pdf). In the project, we investigate how mental imagery and illusory perception is processed in the different layers of V1. It contains fMRI data from 2 studies: The dataset of the first study contains data of 18 human subjects - T1-weighted anatomical images, and fMRI data (GE-EPI) of the experimental runs as well as retinotopic mapping. 2 of the 18 data sets were discarded prior to analysis due to functional inter-run alignment issues. The dataset of the second study contains data of 12 human subjects - T1-weighted anatomical images, and fMRI data (GE-EPI) of the experimental runs as well as retinotopic mapping. 2 of the 12 data sets were discarded prior to analysis due to functional inter-run alignment issues in both, and no discernible retinotopic mapping data in one.
DOI: 10.25493/nkry-ka7
title: Spike time dependent plasticity (STDP) data from neonate C57BL/6 (wild-type) mice, positive pairing

description: Spike-time dependent plasticity (STDP is a particular form of Hebbian type of learning which consists in bidirectional modifications of synaptic strength according to the temporal order of pre- and postsynaptic spiking (*Dan Y1, Poo MM (2006) Spike timing-dependent plasticity: from synapse to perception. Physiol Rev 86:1033-1048*). Thus, positively correlated pre- and postsynaptic spiking (pre before post) within a critical window leads to long term potentiation (LTP), whereas a negative correlation (post before pre) leads to long term depression (LTD). At the neonatal stage, the hippocampal mossy fiber (MF)-CA3 is GABAergic and exhibits STDP. Our data demonstrate that, at the same age, positive pairing fails to induce STD-LTP at MF-CA3 synapses in hippocampal slices obtained from neuroligin-3 (NL3) knock-in (NL3<sup>R451C</sup>KI) and NL3 knock-out (KO) mice. Similarly, in NLR<sup>R451C</sup> KI mice, negative pairing failed to cause STD-LTD. In contrast, STD-LTP and STD-LTD can be readily produced in control age-matched WT littermates. In NLR<sup>R451C</sup> KI mice, the impairment in STD-LTP is maintained in adulthood when MF are glutamatergic. This set of data refers to the neonate, C57BL/6 (wild-type), positive pairing condition.
DOI: 10.25493/t1wa-mbt
title: Probabilistic cytoarchitectonic map of Area TE 1.2 (HESCHL) (v5.0)

description: This dataset contains the distinct probabilistic cytoarchitectonic map of Area TE 1.2 (HESCHL) 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 TE 1.2 (HESCHL). The probability map of Area TE 1.2 (HESCHL) 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 TE 1.2 (HESCHL): Morosan et al. (2019) [Data set, v5.1] [DOI: 10.25493/R382-617](https://doi.org/10.25493%2FR382-617) 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/k9vk-ppm
title: Spike time dependent plasticity (STDP) data from adult C57BL/6 (wild-type) mice, positive pairing

description: Spike-time dependent plasticity (STDP is a particular form of Hebbian type of learning which consists in bidirectional modifications of synaptic strength according to the temporal order of pre- and postsynaptic spiking (*Dan Y1, Poo MM (2006) Spike timing-dependent plasticity: from synapse to perception. Physiol Rev 86:1033-1048*). Thus, positively correlated pre- and postsynaptic spiking (pre before post) within a critical window leads to long term potentiation (LTP), whereas a negative correlation (post before pre) leads to long term depression (LTD). At the neonatal stage, the hippocampal mossy fiber (MF)-CA3 is GABAergic and exhibits STDP. Our data demonstrate that, at the same age, positive pairing fails to induce STD-LTP at MF-CA3 synapses in hippocampal slices obtained from neuroligin-3 (NL3) knock-in (NL3<sup>R451C</sup>KI) and NL3 knock-out (KO) mice. Similarly, in NLR<sup>R451C</sup> KI mice, negative pairing failed to cause STD-LTD. In contrast, STD-LTP and STD-LTD can be readily produced in control age-matched WT littermates. In NLR<sup>R451C</sup> KI mice, the impairment in STD-LTP is maintained in adulthood when MF are glutamatergic. This set of data refers to the adult, C57BL/6 (wild-type), positive pairing condition.
DOI: 10.25493/d1pr-55a
title: Purkinje cell protein 2 tetracycline-transactivator expression: horizontal sections (case 3292)

description: Bright-field microscopy images of serial horizontal brain sections showing Purkinje cell protein 2 (Pcp2) promoter expression in a bigenic Pcp2-tetracycline-transactivator (tTA) mouse brain (case 3292, adult female), generated using a driver-reporter construct in which the PCP2-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. Our data confirm earlier reports that Pcp2-tTA promoter expression is restricted to cerebellar Purkinje cells.
DOI: 10.25493/5fzf-chc
title: Probability map of bundle rh_ST-TT_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 Superior Temporal and Transverse 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/jp26-v66
title: Probability map of bundle rh_IC-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 right hemisphere Isthmus 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/xybw-69q
title: Probabilistic cytoarchitectonic map of Area PFop (IPL) (v9.2)

description: This dataset contains the distinct probabilistic cytoarchitectonic map of Area PFop (IPL) 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 PFop (IPL). The probability map of Area PFop (IPL) 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 PFop (IPL): 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)
DOI: 10.34810/data72/345
title: 01CO_1.MR.0004.0189.2016.02.04.15.44.11.109375.67141470.IMA
DOI: 10.25493/tkjg-9d5
title: Reference delineations of DG (Hippocampus) in individual sections of the BigBrain

description: This dataset contains cytoarchitectonic delineations of hippocampal area CA4 and Fascia dentata (FD) in the BigBrain dataset [Amunts et al. 2013]. The delineations were created after identification of the area in the histological, cell-stained sections based on the cytoarchitectonic criteria. Mappings are available on every 15th to 60th section of the CA4 and FD in both hemispheres. They were then transformed to the sections of the 3D reconstructed BigBrain space using the transformations used in Amunts et al. 2013, which were provided by Claude Lepage (McGill).
DOI: 10.25493/5zjy-phb
title: Mechanistic analysis of ERP in rodents

description: The aim of this task is to gain a better understanding on the nature of the evoked related potentials (ERPs) induced by a current stimulation of the secondary motor cortex (M2), which has been adopted for generating the cortical perturbation in task PCI-like measure in rodents. Since a current stimulation is not physiological, it can be difficult to predict the exact brain response. We, therefore, stimulated M2 of head-restrained awake rats with current pulses of different intensities, in order to approximate a stimulus-response function. We repeated these measures during general anaesthesia to verify if differences in the ERPs could be trivially explained by reduced brain excitability induced by the anaesthetic compound. We then explored the extension of the brain areas that are recruited in the response by simultaneously recording from several cortical regions and from the hippocampus, by mean of chronically implanted stainless-steel and tungsten electrodes respectively.
DOI: 10.25493/r867-nd3
title: Database of paired recordings in hippocampal slices

description: Simulating the function of brain networks requires a detailed characterization of neuronal interactions. Using paired recordings in hippocampal slices, the basic properties of synaptic transmission and short-term synaptic plasticity between identified cells were characterized, employing morphological and electrophysiological classification, as well as transgenic animals expressing cell-type-specific fluorescent markers to target specific connections.
DOI: 10.25493/9sp6-8ha
title: Probabilistic cytoarchitectonic map of Area OP1 (POperc) (v11.0)

description: This dataset contains the distinct probabilistic cytoarchitectonic map of Area OP1 (POperc) 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 OP1 (POperc). The probability map of Area OP1 (POperc) 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 OP1 (POperc): Eickhoff et al. (2018) [Data set, v9.2] [DOI: 10.25493/HVH9-KBR](https://doi.org/10.25493%2FHVH9-KBR) Eickhoff et al. (2019) [Data set, v9.4] [DOI: 10.25493/SH37-979](https://doi.org/10.25493%2FSH37-979) The most probable delineation of Area OP1 (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%2FTAKY-64D)
DOI: 10.25493/pv3d-xvg
title: Probability map of bundle lh_LOF-ST_0 (atlas of superficial white matter fibre bundles, version 2018)

description: This data contains the probability map of a short fibre bundle connecting the left hemisphere Lateral Orbitofrontal and Superior Temporal regions of the Desikan-Killiany atlas, in the MNI ICBM152 reference brain. This bundle was identified using a hybrid approach, incorporating anatomical information (from cortical regions of interest) and fibre shape (fibre clustering), from the tractography datasets of 78 subjects in the Neurospin’s ARCHI database. The map shows the probability of finding a fibre belonging to the bundle in each voxel of the reference brain. The maximum probability corresponds to the voxels with the highest number of putative fibres going through.