cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25493/4160-b8k
title: Probabilistic cytoarchitectonic map of Area 2 (PostCS) (v5.0)

description: This dataset contains the distinct architectonic Area 2 (PostCS) 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 2 (PostCS). The probability map of Area 2 (PostCS) 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 2 (PostCS): Grefkes et al. (2018) [Data set, v3.2] [DOI: 10.25493/JZP0-Q97](https://doi.org/10.25493%2FJZP0-Q97) Grefkes et al. (2019) [Data set, v3.4] [DOI: 10.25493/QA8F-DD2](https://doi.org/10.25493%2FQA8F-DD2) The most probable delineation of Area 2 (PostCS) 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/pf1p-yse
title: Spike time dependent plasticity (STDP) data from neonate neuroligin-3 knock-in 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>451C</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>451C</sup> KI mice, the impairment in STD-LTP is maintained in adulthood when MF are glutamatergic. This set of data refers to the neonate, NLR<sup>451C</sup> KI, positive pairing condition.
DOI: 10.25493/h2h6-0sa
title: Probabilistic cytoarchitectonic map of Area Ig1 (Insula) (v11.0)

description: This dataset contains the distinct probabilistic cytoarchitectonic map of Area Ig1 (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 Ig1 (Insula). The probability map of Area Ig1 (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 Ig1 (Insula): Kurth et al. (2019) [Data set, v13.1] [DOI: 10.25493/EKV9-29D](https://doi.org/10.25493%2FEKV9-29D) The most probable delineation of Area Ig1 (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, v1.13] [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/rnsm-y4y
title: Probabilistic cytoarchitectonic map of Area hIP5 (IPS) (v7.1)

description: This dataset contains the distinct architectonic Area hIP5 (IPS) 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 hIP5 (IPS). The probability map of Area hIP5 (IPS) 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 hIP5 (IPS): Richter et al. (2019) [Data set, v7.0] [DOI: 10.25493/WZNZ-DPQ](https://doi.org/10.25493%2FWZNZ-DPQ) The most probable delineation of Area hIP5 (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) 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/p8x0-v1g
title: Probabilistic cytoarchitectonic map of Area hIP3 (IPS) (v8.4)

description: This dataset contains the distinct architectonic Area hIP3 (IPS) 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 hIP3 (IPS). The probability map of Area hIP3 (IPS) 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 hIP3 (IPS): Scheperjans et al. (2018) [Data set, v8.2] [DOI: 10.25493/J9T6-TX9](https://doi.org/10.25493%2FJ9T6-TX9) The most probable delineation of Area hIP3 (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/btkk-cry
title: Paxinos & Franklin's “The Mouse Brain in Stereotaxic Coordinates” (2nd edition) spatially registered to the Allen Mouse Common Coordinate Framework

description: The dataset contains location metadata defining the spatial registration of the 2nd edition of “The Mouse Brain in Stereotaxic Coordinates” (Paxinos & Franklin, 2001) to the serial two-photon tomography (STPT) volume of the Allen Mouse Common Coordinate Framework (CCF, version 3; Oh et al., 2015). The stereotaxic atlas of Franklin & Paxinos contains revised delineations of 100 coronal and 32 sagittal diagrams from young adult C57BL/6J mice. The schematic diagram images were spatially registered to the Allen Mouse CCF. The dataset consists of an .xml file with spatial metadata that can be opened in the QuickNII tool (RRID:SCR_016854) 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/nk4r-2re
title: Simultaneous cortical fluorescence imaging and LFP recording in striatum after optogenetic striatal stimulation

description: Striatum is involved in cortico-basal ganglia-thalamocortical loop and divided in dorsolateral, dorsomedial and ventral striatum, which are anatomically and functionally distinct. Cortico-striatal connectivity plays a fundamental role in planning movements and cognitive processes. Since striato-cortical communications is largely unexplored, to dissect its connectivity we used a tapered optical fiber implanted unilaterally to optogenetically stimulate targeted domains of striatum in channelrhodopsin(ChR2)-expressing Drd1-Cre awake mice. By changing the light input angle, the illumination is gradually moved along the fiber for striatal region-selective illumination. A microelectrode implanted on the fiber allowed recording of the local field potential from dorsolateral striatum during stimulation. Mice were transfected with AAV9-syn-GCaMP6f for large-scale recording of striatal-evoked neuronal activity using wide-field calcium imaging over right hemisphere. This combination of tools is used to highlight the functional correlation of selected striatal domains with both spatiotemporal cortical patterns over the right cortical mantle, evoked-striatal LFP and evoked-behavior. Preliminary results showed that optogenetic activation of DRD1+-neurons in dorsomedial striatum evoked complex forelimb movements associated with large calcium transients in motor cortex.
DOI: 10.25493/65r0-e9u
title: Structure-phenotype associations for Julich-Brain Cytoarchitectonic Atlas regions

description: Our aim in this project was to characterize the behavioral profile of brain regions defined in the Julich-Brain Cytoarchitectonic Atlas by mapping interindividual variability in local structure as measured with grey matter volume (GMV) to interindividual variability in psychometric data. From a large cohort of healthy individuals [Nooner et al. 2012](https://doi.org/10.3389/fnins.2012.00152), we selected a subgroup of 466 participants with good quality preprocessed T1-weighted MR-scans, using CAT12 toolbox [http://www.neuro.uni-jena.de/cat/](http://www.neuro.uni-jena.de/cat/), and available scores in a broad range of psychometric measures covering multiple cognitive domains (such as attention, episodic memory), personality and emotion scores. The preprocessed individual GMV maps, their corresponding psychometric scores and the regions of the Julich-Brain Cytoarchitectonic Atlas are then entered into the pyJUSBB tool [https://github.com/shahrzadkh/pyJUSBB/](https://github.com/shahrzadkh/pyJUSBB/), where non-parametric partial correlations between variability in average GMV in each of the brain regions and each of the 48 behavioral scores are assessed and ranked to create the behavioral profile of each region. The stability of each association is demonstrated as 95% Bootstrap confidence interval (10000 times).
DOI: 10.25493/ww8g-t2g
title: Probabilistic cytoarchitectonic map of Area Ia (Insula) (v3.1)

description: This dataset contains the distinct architectonic Area Ia (Insula) in the MNI Colin 27 and MNI ICBM 152 reference spaces. As part of the Julich-Brain 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. 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 Ia (Insula). The probability map of Area Ia (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 integration of new brain structures may lead to small deviations in earlier released datasets. The most probable delineation of Area Ia (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)
DOI: 10.25493/k47e-eqe
title: Wistar rat hippocampus CA1 pyramidal cell morphologies – Extension with additional reconstructions

description: This dataset includes 3D morphological reconstruction of rat hippocampus CA1 neurons using Neurolucida software. This dataset contains additional data related to the dataset by Markram et al. (2016; doi: 10.5281/zenodo.57082). Experiments were performed identically, and the data from these two dataset can be used in combination.
DOI: 10.25493/69zh-bgu
title: Probability map of bundle lh_PrC-SF_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 Precentral and Superior Frontal 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: 10.25493/8ptb-jdh
title: Probabilistic cytoarchitectonic map of Interposed Nucleus (Cerebellum) (v6.2)

description: This dataset contains the distinct architectonic Interposed Nucleus (Cerebellum) 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 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 both reference spaces, where each voxel was assigned the probability to belong to Interposed Nucleus (Cerebellum). The probability map of Interposed Nucleus (Cerebellum) 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 Interposed Nucleus (Cerebellum): Tellmann et al. (2019) [Data set, v6.0] [DOI: 10.25493/8MRR-JHC](https://doi.org/10.25493%2F8MRR-JHC) The most probable delineation of Interposed Nucleus (Cerebellum) 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/xhn8-m8y
title: Regional and laminar distribution of receptors for GABA in the rat brain

description: The present dataset provides the quantitative regional and laminar distribution of key molecules of inhibitory neurotransmission, namely the γ-aminobutyric acid (GABA) receptors GABA<sub>A</sub> and GABA<sub>B</sub> as well as the GABA<sub>A</sub> associated benzodiazepine (GABA<sub>A</sub>/BZ) binding 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 muscimol, CGP 54626 and flumazenil. 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: 10.34810/data72/372
title: 01CO_1.MR.0004.0227.2016.02.04.15.44.11.109375.67144017.IMA
DOI: 10.25493/4gz1-shh
title: Density measurements of different receptors for Putamen [human, v1.0]

description: This dataset contains the densities (in fmol/mg protein) of receptors for classical neurotransmitters in Putamen (Pu) 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/gky8-nzr
title: Density measurements of different receptors for mediodorsal part of the Thalamic Nucleus [human, v1.0]

description: This dataset contains the densities (in fmol/mg protein) of receptors for classical neurotransmitters in mediodorsal part of the Thalamic Nucleus (ThMD) 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 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