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2,031 results for “transformer”
Transformed crane data from: Balancing structural complexity with ecological insight in spatio-temporal species distribution models
<p>The potential for statistical complexity in species distribution models (SDMs) has greatly increased with advances in computational power. Structurally complex models provide the flexibility to analyse intricate ecological systems and realistically messy data, but can be difficult to interpret, reducing their practical impact. Founding model complexity in ecological theory can improve insight gained from SDMs. </p> <p>Here, we evaluate a marked point process approach, which uses multiple Gaussian random fields to represent population dynamics of the Eurasian crane (<em>Grus grus</em>) in a spatio-temporal species distribution model. We discuss the role of model components and their impacts on predictions, in comparison with a simpler binomial presence/absence approach. Inference is carried out using Integrated Nested Laplace Approximation (INLA) with inlabru, an accessible and computationally efficient approach for Bayesian hierarchical modelling, which is not yet widely used in SDMs. </p> <p>Using the marked point process approach, crane distribution was predicted to be dependent on the density of suitable habitat patches, as well as close to observations of the existing population. This demonstrates the advantage of complex model components in accounting for spatio-temporal population dynamics (such as habitat preferences and dispersal limitations) that are not explained by environmental variables. However, including an AR1 temporal correlation structure in the models resulted in unrealistic predictions of species distribution; highlighting the need for careful consideration when determining the level of model complexity.</p> <p>Increasing model complexity, with careful evaluation of the effects of additional model components, can provide a more realistic representation of a system, which is of particular importance for a practical and impact-focused discipline such as ecology (though these methods extend to applications for a wide range of systems). Founding complexity in contextual theory is not only fundamental to maintaining model interpretability, but can be a useful approach to improving insight gained from model outputs. </p>
Acoustic models of Brazilian Portuguese Speech based on Neural Transformers - Pretraining Datasets raw audios from CORAA
<p>This repository contains all the pretraining datasets used in the paper: Acoustic models of Brazilian Portuguese Speech based on Neural Transformers by Marcelo Gauy and Marcelo Finger. These datasets are part of a collection of datasets from the TaRSila project (see https://sites.google.com/view/tarsila-c4ai). The audios published here were in part also published with annotations and transcriptions as the CORAA dataset (see https://github.com/nilc-nlp/CORAA). Here we publish the original raw audios from the following datasets (without transcriptions) - ALIP, C-Oral, SP2010, NURC-Recife, NURC-São Paulo and Programa Certas Palavras. In total, the datasets contain about 800 hours of Brazilian Portuguese Speech.</p> <p>The audios have been converted to mp3 to facilitate the upload. ALIP, C-Oral and SP2010 are integrally contained in one file each. Programa Certas Palavras and NURC-Recife are split in 3 parts each, while NURC-SP is split in 7 parts of roughly equal size. More information on the datasets can be found in the paper Acoustic models of Brazilian Portuguese Speech based on Neural Transformers as well as on the original references which created these datasets.</p>
Transforming the UK's diagnostics agenda after COVID-19 and grand challenges – Future Blood Testing Landscape report - Prof Dimitris Grammatopoulos (University Hospitals Coventry & Warwickshire, University of Warwick)
<p>This video is the second talk from our two day Future Blood Testing: Challenges & Opportunities Event that took place on the 13/09/2022.</p> <p>Transforming the UK’s diagnostics agenda after COVID-19 and grand challenges – Future Blood Testing Landscape report - Prof Dimitris Grammatopoulos (University Hospitals Coventry & Warwickshire, University of Warwick)</p> <p>Bio: Dimitris Grammatopoulos, PhD, FRCPath, is Professor of Molecular Medicine at Warwick Medical School and Consultant in Clinical Biochemistry and Molecular Diagnostics at the University Hospitals of Coventry and Warwickshire, NHS Trust, United Kingdom. He also leads the Novel Biomarkers theme of the Institute of Precision Diagnostics and Translational Medicine, Pathology-UHCW NHS Trust. where he combines clinical expertise in diagnostic laboratory medicine with a research track-record in application of cutting edge multidiscipline methodologies in routine clinical diagnostics. He received academic and clinical training in Newcastle, Bristol, Johns Hopkins-Baltimore and Warwick. He has expertise in biochemical/molecular diagnosis of many endocrine and metabolic disorders. His translational research interest is focused on stress hormones and homeostatic adaptations of fetal development to maternal disease as well as development of novel -omics based biomarker approaches suitable for precision medicine and better characterisation of patient phenotype. He has experience around use of AI and ML for development and refinement of clinical and diagnostic pathways for complex chronic conditions that are considered as national priorities. Dimitris is the Lead in Diagnostics, Global Health Priorities in Health, University of Warwick.</p> <p>Further details on this event can be found at: https://futurebloodtesting.org/event/13-14-09-2022/</p> <p>This video is an output from the Future Blood Testing Network which is funded by EPSRC under Grant Number EP/W000652/1</p> <p>YouTube Link: https://youtu.be/HiOlRzJPR7Q</p>
Data for "Impact of Gaussian transformation on cloud cover data assimilation for historical weather reconstruction"
<p>This dataset contains the simulation results in "Impact of Gaussian transformation on cloud cover data assimilation for historical weather reconstruction".</p>
Supplementary material - Eggerthella lenta DSM 2243 alleviates bile acid stress response in Clostridium ramosum and Anaerostipes caccae by transformation of bile acids
<p>The word document is a collection of supplementary figures and tables. <br> The excel file is a collection of raw data from experiments.</p>
Technical Debt Classification in Issue Trackers using Natural Language Processing based on Transformers
<p>In order to ensure transparency and reproducibility, we have made everything available publicly here, including the Code, Models, Datasets and more. All the files and their functionality used in this paper are explained clearly in the <strong>README.md</strong> file.</p> <p>Background: Technical Debt (TD) needs to be controlled and tracked during software development. Support to automatically track TD in issue trackers is limited. </p> <p>Aim: We explore the usage of a large dataset of developer-labeled TD issues in combination with cutting-edge Natural Language Processing (NLP) approaches to automatically classify TD in issue trackers.</p> <p>Method: We mine and analyze more than 160GB of textual data from GitHub projects, collecting over 55,600 TD issues and consolidating them into a large dataset (GTD dataset). We use such datasets to train and test Transformer ML models. Then we test the model's generalization ability by testing them on six unseen projects. Finally, we re-train the models including part of the TD issues from the target project to test their adaptability. </p> <p>Results and Conclusion: (i) We create and release the GTD dataset, a comprehensive dataset including TD issues from 6,401 public repositories with various contexts; (ii) By training Transformers using the GTD dataset, we achieve performance metrics that are promising; (iii) Our results are a significant step forward towards supporting the automatic classification of TD in issue trackers, especially when the models are adapted to the context of unseen projects after fine-tuning.</p>
Breaking the constraint on the number of cervical vertebrae in mammals: on homeotic transformations in lorises and pottos
<p><strong>Data-collection</strong></p> <p><em>Specimens</em>. We analysed 1090 skeletons of wild-born primates belonging to 60 species of ten families (Table 1). These skeletons are held in collections of ten European and American natural history museums (Naturalis Biodiversity Center, Leiden (Naturalis); The Natural History Museum, London (NHMUK); the Royal Museum for Central Africa, Tervuren (RMCA); the Royal Belgian Institute of Natural Sciences, Brussels (RBINS); the Natural History Museum of Denmark, Copenhagen (ZMUC); Naturhistorisches Museum Wien, Vienna (NHMW); the Swedish Museum of Natural History, Stockholm (NRM); Museum fur Naturkunde, Berlin (MfN); and the National Museum for Natural History, Paris (MNHN), Natural History Museum Oslo, American Museum of Natural History, New York, Field Museum of Natural History, Chicago (FMNH). Five families belonged to the Strepsirrhini (Lorisidae, Galagidae, Daubentoniidae, Lemuridae, Indriidae) and five to the Haplorrhini, of which two Platyrrhini (Cebidae, Atelidae) and three Catarrhini (Cercopithecidae, Hylobatidae, Hominidae).</p> <p><strong>Cervical vertebrae and transitional cervicothoracic vertebrae</strong>. We determined the number of cervical vertebrae and transitional cervicothoracic vertebrae (vertebrae with both cervical and thoracic characteristics, i.e. a seventh vertebrae with a rudimentary rib or one full rib instead of two, or an eighth vertebrae with rudimentary ribs or without ribs on one side). The identification of transitional cervicothoracic vertebrae was based on the presence of cervical or rudimentary first ribs. In the case of a fusion of rudimentary cervical ribs with the transverse process (apophysomegaly), the vertebra was counted as a transitional cervicothoracic vertebra when the transverse process was at least 15% longer than that of the first thoracic vertebra, or when traces of the articulation were still visible.</p> <p><strong>Explanatory variables. </strong>Per specimen where we determined the vertebral pattern, we recorded the species, life style ("fast" vs. "slow"), individual age class and sex and whether the animal was kept in a zoo later in life or not. This last indicator variable can accommodate effects of relaxed selection in captive environments on the probability of finding an abnormal pattern.</p> <p><strong>Phylogeny. </strong>We used the consensus phylogeny of primates provided by the 10k Trees Project (Arnold & Nunn, 2010) to represent our data per species graphically and to calculate correlations between species effects</p> <p><strong>Statistical analysis. </strong>The R script with our analysis is added.</p> <p> </p>
Figure 2: The intput and output forms of the transformation engine
<p>The goal of the project was to develop a translation system between two<br> knowledge representation forms. One of the representation forms is a new<br> kind of abstract predicate oriented conceptual graphs called ECG. The second<br> representation form is a set of sentences of a given language. While the ECG<br> is a general, language independent tool, the sentences belong to a language<br> and a speci¯c grammar.</p>
Figure 1: Abstract Meta-Model-UNDERSTANDING SERVICE COMPOSITION WITH NON-FUNCTIONAL PROPERTIES USING DECLARATIVE MODEL-TO-MODEL TRANSFORMATIONS
<p>To de¯ne the model we ¯rst de¯ned the abstract meta-model which con-<br> tains all the processes which can be used in the application model. These are<br> used to model the behaviour of the application (see Figure 1).</p>
Figure 1. Protelytron permianum Tillyard, 1931 in Reinvestigation of Protelytron permianum (Insecta; Early Permian; USA) as an example for applying reflectance transformation imaging to insect imprint fossils
Figure 1. Protelytron permianum Tillyard, 1931, holotype (YPM IP 001019b), habitus. Interpretative drawing (a) and photograph (b side, extracted from the RTI file available from Béthoux et al., 2016) (b). See text for abbreviations and colour coding.
Figure 3 in Reinvestigation of Protelytron permianum (Insecta; Early Permian; USA) as an example for applying reflectance transformation imaging to insect imprint fossils
Figure 3. Template for assembly of operative models of right fore- and hind wing reconstructions of Protelytron permianum Tillyard, 1931. Dorsal (a) and ventral (b) views. See text for abbreviations and colour coding, and Béthoux et al. (2016) for a video tutorial. Assembly instructions: print the whole figure and fold along the grey dashed line; glue inner sides of paper sheet together; cut out wings along their outlines; in the hind wing, imprint the folds with a needle and a ruler; imprint concave folds (purple) on the dorsal side; imprint convex folds (green, orange, and blue) on ventral side; and imprint red fold weakly on both sides. To assist colour-blind readers, folds should be imprinted where represented by a full-colour full line (as opposed to a pale-colour dash-dotted line).
Figure 2. Protelytron permianum Tillyard, 1931 in Reinvestigation of Protelytron permianum (Insecta; Early Permian; USA) as an example for applying reflectance transformation imaging to insect imprint fossils
Figure 2. Protelytron permianum Tillyard, 1931, holotype (YPM IP 001019b), detail of the left hind wing as located in Fig. 1b. Photograph (extracted from the RTI file available from Béthoux et al., 2016) (a) and the same but with interpretative drawing (reproduced from Fig. 1a). See text for abbreviations and colour coding.
FIGURE 12 in Redescription of soft tissue preservation in the holotype of Scaphognathus crassirostris (Goldfuss, 1831) using reflectance transformation imaging
FIGURE 12. Distribution of the different soft tissue types occurring on the main slab of the Scaphognathus crassirostris holotype IGPB Goldfuss 1304a, illustrated in a modified version of Figure 2A. This Figure functions as a guide for the respective location of the soft part types intensively described in the manuscript and the captions to give an overview about their spatial distribution and their occurrence on the main slab, supported by the interpretative drawings of the soft tissues. Pycnofibre Type 2 (smaller red and yellow circles), Type 3 (orange circle), Type 4 (red rectangle), Type 5 (larger red circle), Type 6 (green circle), aktinofibrils (red ellipse), and putative patagium vessels marked by red transverse lines.
FIGURE 5 in Redescription of soft tissue preservation in the holotype of Scaphognathus crassirostris (Goldfuss, 1831) using reflectance transformation imaging
FIGURE 5. Close-up RTIViewer snapshots of the region dorsal to the dorsal vertebral column on the main slab, taken under different lighting conditions, but all processed using the specular enhancement mode (except for Figure 5D). Scale bar for all illustrations equals 10 mm. 5A-5B. Caudal region dorsal to the dorsal vertebral column (lower right corner of both images) and next to the semi-circular indent, illustrated under different lighting conditions. 5C. Sketch of Figure 5A and 5B showing the appearance and the orientation of the pycnofibres under normal light. 5D-5E. Pycnofibres dorsal to the first anterior dorsal vertebrae (lower right corner), showing a striking pycnofibre accumulation under normal light (5D) as well as under the specular enhancement mode (5E). Note the spreading of pycnofibres in a radially symmetrical pattern from an arc-like starting point (red arrows, starting point marked by a red arc in 5E-5F). Also, note the branching in the dorsalmost part of the whitish limestone surface (orange circle in 5D-5F). 5F. Interpretative drawing of 5D and 5E, illustrating the arrangement of the pycnofibre impressions under normal light.
FIGURE 8 in Redescription of soft tissue preservation in the holotype of Scaphognathus crassirostris (Goldfuss, 1831) using reflectance transformation imaging
FIGURE 8. Close-up RTIViewer snapshots of the region ventral to the zeugopodial bones of the right wing on the counter slab, taken under different lighting conditions, but all processed using the specular enhancement mode (except for 8A). Scale bar for all illustrations equals 10 mm, except for 8E (1 mm). Markings for various pycnofibre types used throughout this Figure: the location of aktinofibrils impressions is marked by a red rectangle, the direction in which pycnofibre impressions point is highlighted by red arrows, the Type 2 pycnofibre is illustrated by a red circle. 8A. The whitish amorphous rock surface with pycnofibres between the zeugopodial bones of the right wing (upper right corner) and the first two phalanges of the right wing finger (lower left corner). Note first type pycnofibre impressions (red lines). The locality of overlapping impressions is marked by an orange circle in 8A and 8B (although not well visible in the image). 8B. Idealised sketch of Figure 8A after comparing several RTI images with each other to better visualise the trend of the decreasing abundance of crossing/ overlapping pycnofibres. Note that a trend of opposing impression directions seems to exist in this area of the counter slab (see the two red arrows). 8C. Specular enhancement image depicting the lower image part of 8A encompassing a wider field of vision. Aktinofibrils-like impressions heading for the lower right edge of the image (red arrows within the orange rectangle). 8D. Sketch of 8C. 8E. Enlarged close-up of the Type 2 pycnofibre. A much smaller terminal bifurcation is indicated (red arrow), suggesting that it might even be another type of bifurcated pycnofibre. 8F. Sketch of 8E, illustrating the smaller terminal bifurcation (yellow circle). 8G, 8I. The inconsistent appearance of the pycnofibres directly ventral to the articulation of the metacarpal bones with the phalanges of the right wing finger, taking on interesting shapes depending on the direction of incident light (red oval in 8G and also indicated in 8H). At some places, the pycnofibre impressions cross each other at specific angles (marked by two red angles in 8G and 8I). 8H. Sketch of 8G to highlight the oval shape of an accumulation of impressions.
FIGURE 4 in Redescription of soft tissue preservation in the holotype of Scaphognathus crassirostris (Goldfuss, 1831) using reflectance transformation imaging
FIGURE 4. Close-up RTIViewer snapshots of the region dorsal to the dorsal vertebral column on the main slab, taken under different lighting conditions but all processed using the specular enhancement mode (except for Figure 4A). Scale bar for all illustrations equals 10 mm. Comment on the settings in the RTIViewer software as visualised in the figures. A green sphere symbolises the direction of the incident light (upper right corner), a text box in the upper image margin contains the respective x- and ycoordinates of the incident light direction (the first value contains the x-coordinate, while the second one contains the ycoordinate), the zoom factor is given in brackets. A second text box contains the individual values of the specular enhancement mode (lower left corner). The first value stands for the parameter "specularity", the second one indicates the parameter "highlight size". The line drawings were sometimes made based on several RTI images with different settings to illustrate an individual impression more clearly. As far as the figures themselves are concerned, the interpretative drawings have tried to come as close as possible to the appearance and arrangement of the structures observed in the RTIViewer. However, some drawings, such as Figure 4B, represent rather idealised illustrations of the general pattern and arrangement of individual pycnofibre impressions in a given area. For this reason, the interpretative drawings may differ in detail from the respective RTI images to which they refer. In all figures, the orientation of the pycnofibres is marked by red arrows; the whitish semicircular indent, the starting point of most of the pycnofibres in the caudal region of the dorsal vertebrae, is symbolised by a red arc throughout Figure 4 and 5, the single occurrence of Type 2 pycnofibres is circled in red in the aforementioned figures. 4A. Overview of the pycnofibre impressions in the area dorsal to the dorsal vertebral column associated with the whitish amorphous rock surface under normal light. 4B. Interpretative drawing of Figure 4A (dorsal ribs in the lower right corner of the image) under normal light, idealised to give an overview of the spatial orientation of the pycnofibre impressions and therefore not reflecting the exact path of individual impressions. Thicker lines indicate better observable impressions. 4C. The same area as in 4A, seen under the specular enhancement mode. 4D. Pycnofibres of the caudalmost part of the area dorsal to the dorsal vertebral column (lower right corner). Note the pycnofibres showing a distinctive cross-over (red circle in 4D and 4E), representing Type 2. 4E. The same area as in 4D under other lighting conditions to highlight the overlapping impressions.
FIGURE 1 in Redescription of soft tissue preservation in the holotype of Scaphognathus crassirostris (Goldfuss, 1831) using reflectance transformation imaging
FIGURE 1. Images from the original publication by Georg August Goldfuss (1831). Main slab (1A) and counter slab (1B) of the holotype of Scaphognathus crassirostris IGPB Goldfuss 1304a (main slab) and 1304b (counter slab). 1C, Skeletal reconstruction of Scaphognathus crassirostris, including palaeobiological life reconstruction of two Scaphognathus crassirostris specimens in their presumed marginal marine habitat. However, the skeletal reconstruction contains two major errors: firstly, four instead of three clawed fingers are to be seen on the hand, and secondly, the long tail characteristic of most non-pterodactyloid pterosaurs is missing.
FIGURE 13 in Redescription of soft tissue preservation in the holotype of Scaphognathus crassirostris (Goldfuss, 1831) using reflectance transformation imaging
FIGURE 13. Different areas on the main slab as well as on the counter slab sum up the general mode of the soft part preservation in the Scaphognathus crassirostris holotype IGPB Goldfuss 1304b. The impressions on the main slab (images on the left figure side; 13A, 13C, and 13E) are in accordance with the corresponding elevations of the same impressions on the counter slab (right images 13B, 13D, and 13F; see for a direct comparison the red arrows). This illustrates the observation made by Goldfuss (1831), who stated that on the main slab, the soft part impressions are to be seen as grooves, whereas on the counter slab, they are shaped as elevations. This observation led Goldfuss (1831, p. 108) to the conclusion that the pycnofibres must have originally been under the limestone layer of the counter slab. 13A-13B. Pycnofibre impressions and the remains of the wing membrane including the aktinofibrils close to the articulation of the first with the second phalanx of the right wing finger (putative patagium border marked in both images by a red transversal line). 13C-13D. The impressions between the deltopectoral crest of the humerus and the zeugopodial bones of the right wing. Note the strong contrast between the deeply embedded grooves on the main slab (13C) and the clearly perceptible elevations on the counter slab (13D). 13E-13F. Blood vessel impressions. The grooves of the blood vessels on the main slab trace the exact contour of the corresponding elevations on the counter slab.
FIGURE 11 in Redescription of soft tissue preservation in the holotype of Scaphognathus crassirostris (Goldfuss, 1831) using reflectance transformation imaging
FIGURE 11. Close-up RTIViewer snapshots of the region enclosed by the articulation of the humerus with the zeugopodial bones of the right wing and the deltopectoral crest of the humerus on the counter slab, taken under different lighting conditions, but all processed using the specular enhancement mode (except 11A and 11E). Scale bar for all illustrations equals 10 mm. Markings for various soft part impressions used throughout this Figure: red lines illustrate the path of the impressions and their orientation to each other and a red ellipse marks the longest blood vessel. 11A. The geometrically organised soft parts ventral to the deltopectoral crest of the humerus (uppermost left corner) and the zeugopodial bones of the right wing (lower margin). Note the distinct crossing of the two thick main branches (red circle in 11A and 11B). The arrangement of these impressions of a soft tissue type that cannot be determined with absolute certainty, but very probably once belonging to the Patagium reminds of the arrangement of the main vessels in the complex vessel system in the Rhamphorhynchus specimen JME SOS 4784 (Tischlinger and Frey, 2002; Frey et al., 2003). In this specimen, a large main vessel serves as an attachment point for side channels branching off from it at more or less right angles. 11B. Interpretative drawing of 11A. 11C-11D. Specular enhancement images of Figure 11A under different lighting conditions. The soft part impressions likely representing former patagium vessels appear either as elevations (11C) or as grooves (11D). The parallel arrangement of some side branches is confirmed under all lighting conditions, suggesting its interpretation as part of the patagium. 11E. The longest, unbranched and strongly bifurcated blood vessel (red circle in 11E). 11F-11G. The appearance of the pit-like depressions already shown in Figure 10 associated with the blood vessels.
FIGURE 7 in Redescription of soft tissue preservation in the holotype of Scaphognathus crassirostris (Goldfuss, 1831) using reflectance transformation imaging
FIGURE 7. Close-ups of RTIViewer snapshots of the region ventral to the zeugopodial bones of the right wing on the main slab, taken under different lighting conditions, but all processed using the specular enhancement mode (except for 7D and 7G). Scale bar for all illustrations equals 10 mm, except for Figure 7A (1 mm). Markings for various pycnofibre types used throughout this figure: red circle illustrating Type 5 (the tuft); red arrows highlighting the main branch and several side branches of Type 6 (feather-like) as well as the individual path of single pycnofibre impressions at the lower margin of the main slab (Fig. 7C). For better comparability, the outermost (longest) side branches of the "feather" are highlighted by red markings (inclusive all terminal bifurcations). 7A. Type 5 pycnofibre. Some impressions suggest a connection between the Type 5 and 6 pycnofibres, but are not consistent in their appearance. 7B. Schematic drawing of Figure 7A, showing possible connections between the tuft and neighbouring grooves (see red arrows, although not entirely confirmable by the RTI images). 7C. The accumulation of Type 1 pycnofibres at the edge of the main slab near the articulation of the first with the second phalanx of the right wing finger (towards the lower right corner). Red arrows indicate the opposing directions of the impressions. Note in the upper right image corner the sixth pycnofibre type of Figure 7D-7I (green circle). 7D. Type 6 pycnofibre, dorsal to the articulation of the first with the second phalanx of the right wing finger (lower right image corner). Some side branches bear even smaller ones (red parabola-like upside-down markings in Figure 7D, 7E and 7H). 7E. Specular enhancement image of the sixth type. 7F. Interpretative sketch of 7E, highlighting the similarity with a feather as Goldfuss (1831) previously pointed out. The extent, length and number of several side branches are difficult to determine. Therefore, the drawing may differ in some details from the structure visible in the RTI images.7G-7H. The feather-like pycnofibre impression from a greater distance under normal light (7G) and processed by using the specular enhancement mode (7H). 7I. Sketch of Figure 7G and 7H, suggesting no real connection between the Type 5 (tuft) and Type 6 (feather) pycnofibres.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.