cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25493/yetc-bn2
title: Density measurements of different receptors for DG (Hippocampus) [rat, v2.0]

description: This dataset contains the densities (in fmol/mg protein) of receptors for classical neurotransmitters of DG (hippocampus) obtained by means of quantitative _in vitro_ autoradiography. The receptor densities are visualized as _fingerprints_ (**fp**), which provide the mean density and standard deviation for each of the analyzed receptor types, averaged across samples. Overview of available measurements [ **receptor** \| **_neurotransmitter_** \| _labeling agent_ ]: **AMPA** \| **_glutamate_** \| _[<sup>3</sup>H]AMPA_ **kainate** \| **_glutamate_** \| _[<sup>3</sup>H]kainate_ **NMDA** \| **_glutamate_** \| _[<sup>3</sup>H]MK-801_ **GABA<sub>A</sub>** \| **_GABA_** \| _[<sup>3</sup>H]muscimol_ **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 tissDensity measurements of different receptors for DG (hippocampus) [rat, v2.0]ue 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/ftp2-sxv
title: Probabilistic cytoarchitectonic map of Area FG2 (FusG) (v3.0)

description: This dataset contains the distinct architectonic Area FG2 (FusG) in the individual, single subject template of the MNI Colin 27 as well as the MNI ICBM 152 2009c nonlinear asymmetric reference space. As part of the Julich-Brain cytoarchitectonic atlas, the area was identified using cytoarchitectonic analysis on cell-body-stained histological sections of 10 human postmortem brains obtained from the body donor program of the University of Düsseldorf. The results of the cytoarchitectonic analysis were then mapped to both reference spaces, where each voxel was assigned the probability to belong to Area FG2 (FusG). The probability map of Area FG2 (FusG) is provided in the NifTi format for each brain reference space and hemisphere. The Julich-Brain atlas relies on a modular, flexible and adaptive framework containing workflows to create the probabilistic brain maps for these structures. Note that methodological improvements and integration of new brain structures may lead to small deviations in earlier released datasets. Other available data versions of Area FG2 (FusG): Caspers et al. (2018) [Data set, v1.2] [DOI: 10.25493/X835-SK7](https://doi.org/10.25493%2FX835-SK7) Caspers et al. (2019) [Data set, v1.4] [DOI: 10.25493/F2JH-KVV](https://doi.org/10.25493%2FF2JH-KVV) The most probable delineation of Area FG2 (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) 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: 10.25493/35dk-jp6
title: Probability map of bundle lh_PoCi-PrCu_1 (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: 10.25493/3vk5-6wz
title: 3D cyto- and receptor architectonic map of macaque primary motor area 4a

description: A multimodal analysis of the macaque motor cortex was carried out to create a 3D atlas integrating and reconciling discrepancies between previously published maps. This involved a quantitative and statistically testable approach to the analysis of cytoarchitecture in the macaque monkey frontal agranular cortex, in combination with an in vitro quantitative receptor autoradiographic analysis of the regional and laminar distribution patterns of 13 different neurotransmitter receptors. The borders of the identified areas were traced onto a reference macaque monkey brain in stereotaxic space. We provide here for the first time a map of primary motor area 4a of the macaque monkey brain integrating cyto- and receptor architectonic features in stereotaxic space. It constitutes a valuable resource for the analysis of functional experiments with non-human primates, and provides crucial data for modeling approaches with realistic synaptic dynamics.
DOI: 10.25493/yw1e-6bw
title: P28 3D Edge-Aware Refined Atlas Derived from the Allen Developing Mouse Brain Atlas

description: 3D imaging necessitates corresponding 3D anatomical atlases, but generating such atlases is time consuming and challenging. Substantial efforts have generated such atlases including the Allen Developing Mouse Brain Atlas (ADMBA) but are typically limited by the process of serial 2D annotation for 3D reconstruction leading to artifacts. We have developed an automated, edge-aware atlas refinement method to curate existing atlases in a topologically consistent, 3D manner. Applying this approach to the P28 atlas in the ADMBA, we inferred labels for incompletely labeled areas, smoothed the labels in 3D, and realigned the labels to the underlying anatomical edges. As required, we also rotated images in 3D for midline symmetry.
DOI: 10.25493/7eed-gxe
title: Probability map of bundle rh_RMF-SF_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 Rostral Middle Frontal 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/tsen-qsy
title: Probabilistic cytoarchitectonic map of Area hIP4 (IPS) (v7.1)

description: This dataset contains the distinct architectonic Area hIP4 (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 hIP4 (IPS). The probability map of Area hIP4 (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 hIP4 (IPS): Richter et al. (2019) [Data set, v7.0] [DOI: 10.25493/DFB3-SPJ](https://doi.org/10.25493%2FDFB3-SPJ) The most probable delineation of Area hIP4 (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: 10.34810/data72/369
title: 01CO_1.MR.0004.0056.2016.02.04.15.44.11.109375.67136136.IMA
DOI: 10.25493/8t8d-qz0
title: Probabilistic cytoarchitectonic map of Area OP1 (POperc) (v12.0)

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) Eickhoff et al. (2020) [Data set, v11.0] [DOI: 10.25493/9SP6-8HA](https://doi.org/10.25493%2F9SP6-8HA) 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) 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/j43z-kh0
title: Spike time dependent plasticity (STDP) data from adult 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>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, neuroligin-3 knock-in mice, positive pairing condition.
DOI: 10.25493/kyz2-4gm
title: Density measurements of different receptors for stratum moleculare of CA (Hippocampus) [human, v2.0]

description: This dataset contains the densities (in fmol/mg protein) of receptors for classical neurotransmitters in stratum moleculare 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_ **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/qdqj-v0z
title: Densities and 3D distributions of synapses using FIB/SEM imaging in the human neocortex (Trans entorhinal cortex, TEC)

description: Synapses have been identified, segmented and quantified in the human neocortex (trans entorhinal cortex, TEC) with 3D electron microscopy (FIB-SEM). Layer II of the TEC has been studied. 5 cases have been used (AB1, AB2, IF10, M16 and M17) to achieve a total of 15 valid images stacks. Data obtained include the number of asymmetric and symmetric synapses, their sizes and their spatial distribution. The distribution of their post-synaptic targets has also been determined.
DOI: 10.25493/kktt-1tk
title: Density measurements of different receptors for the anterior Thalamic nucleus [human, v1.0]

description: This dataset contains the densities (in fmol/mg protein) of receptors for classical neurotransmitters in the anterior Thalamic nucleus (ThA) 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: 10.25493/77f8-7b4
title: Whole brain maps of resting state brain activation

description: Whole-brain images of neuronal activation in mouse brain acquired with light-sheet microscopy. Animal models will be used to detect immediate early genes (IEGs) expression.
DOI: 10.25493/dds9-hwt
title: GapMap Frontal to Temporal (v9.2)

description: This dataset contains the “GapMap Frontal to Temporal" in the individual, single subject template of the MNI Colin 27 as well as the MNI ICBM 152 2009c nonlinear asymmetric reference space. In order to provide whole-brain coverage for the cortex within the Julich-Brain Atlas, yet uncharted parts of the frontal cortex have been combined to the brain region “GapMap Frontal to Temporal”. The distributions were modeled so that probabilistic gap maps were computed in analogy to other maps of the Julich-Brain Atlas. The probabilistic map of “GapMap Frontal to Temporal” 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. New maps are continuously replacing parts of “GapMap Frontal to Temporal” with progress in mapping. Other available data versions of Gap Frontal to Temporal: Amunts et al. (2020) [Data set, v9.0] [DOI: 10.25493/KRRN-E62](https://doi.org/10.25493%2FKRRN-E62) Amunts et al. (2020) [Data set, v9.1] [DOI: 10.25493/468P-A99](https://doi.org/10.25493%2F468P-A99) The most probable delineation of GapMap Frontal to Temporal 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, v2.2] [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)
DOI: 10.25493/s0hp-esv
title: 3D cyto- and receptor architectonic map of macaque area PG of the inferior parietal lobe

description: A multimodal analysis of the macaque inferior parietal lobule was carried out to create a 3D atlas integrating and reconciling discrepancies between previously published maps. This involved a quantitative and statistically testable approach to the analysis of cytoarchitecture in the macaque monkey inferior parietal lobe, in combination with an in vitro quantitative receptor autoradiographic analysis of the regional and laminar distribution patterns of 15 different neurotransmitter receptors. The borders of the identified areas were traced onto a reference macaque monkey brain in stereotaxic space. We provide here for the first time a map of area PG of the macaque monkey brain integrating cyto- and receptor architectonic features in stereotaxic space. It constitutes a valuable resource for the analysis of functional experiments with non-human primates, and provides crucial data for modeling approaches with realistic synaptic dynamics.
DOI: 10.25493/ztm5-ngd
title: Anterograde visualization of projections from ventral orbitofrontal cortex in rat (case: F20)

description: High-resolution bright-field microscopy images (32) 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 ventral orbitofrontal cortex (VOC). 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/jzp0-q97
title: Probabilistic cytoarchitectonic map of Area 2 (PostCS) (v3.2)

description: This dataset contains the distinct probabilistic cytoarchitectonic map of Area 2 (PostCS) 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 2 (PostCS). The probability map of Area 2 (PostCS) 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 2 (PostCS): 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)