Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
333
datasets available to search
ShareScore release 0.9.0
Dataset results
333 results for “functional network”
Data from: Frugivore biodiversity and complementarity in interaction networks enhance landscape-scale seed dispersal function
1. Animal biodiversity matters for the provision of ecosystem functions derived from trophic activity. However, the mechanisms underlying this pattern remain elusive since animal abundance and diversity, which are the components commonly used for representing biodiversity, provide poor information about ecological complementarity in species assemblages. An approach based on species interaction networks may overcome this constraint. 2. Here, we relate frugivore biodiversity and frugivore-plant network structure with landscape-scale seed dispersal function. We sampled, for two years, and at fourteen plots with variable assemblages of frugivores and plants in the Cantabrian Range (N Spain), data on the abundance and diversity of frugivorous birds, the consumption of fleshy fruits of woody plants, and the landscape-scale patterns of avian seed deposition. As a measure of interaction complementarity in seed dispersal networks, we estimated the degree to which frugivore and plant species specialize in their interacting partners. 3. Specialization varied strongly across the seed dispersal networks of the different plots, being higher in networks harboring smaller bird species that dispersed mostly small-fruited plants, and also in networks with late-ripening, dominant fruiting species dispersed mostly by wintering birds. 4. Bird abundance markedly affected seed deposition. Plots harboring more birds received a higher density of dispersed seeds, and showed higher probabilities of seed arrival and seed deposition in open microhabitats. Bird diversity also had a positive effect on the density of dispersed seed and, to a lesser extent, seed arrival probability. Independently of frugivore abundance and diversity, the density of dispersed seeds increased in plots where seed dispersal networks showed a higher degree of specialization. 5. This study considers the structure of interaction networks to re-address the relationship between biodiversity and ecosystem functionality, evidencing that specialization in frugivore-plant networks drives the large-scale process of seed dispersal. These results encourage the consideration of interaction complementarity as an underlying mechanism linking animal biodiversity and trophic-related functions.
Data from: Quantifying species contributions to ecosystem processes: a global assessment of functional trait and phylogenetic metrics across avian seed-dispersal networks
Quantifying the role of biodiversity in ecosystems not only requires understanding the links between species and the ecological functions and services they provide, but also how these factors relate to measurable indices, such as functional traits and phylogenetic diversity. However, these relationships remain poorly understood, especially for heterotrophic organisms within complex ecological networks. Here, we assemble data on avian traits across a global sample of mutualistic plant–frugivore networks to critically assess how the functional roles of frugivores are associated with their intrinsic traits, as well as their evolutionary and functional distinctiveness. We find strong evidence for niche complementarity, with phenotypically and phylogenetically distinct birds interacting with more unique sets of plants. However, interaction strengths—the number of plant species dependent on a frugivore—were unrelated to evolutionary or functional distinctiveness, largely because distinct frugivores tend to be locally rare, and thus have fewer connections across the network. Instead, interaction strengths were better predicted by intrinsic traits, including body size, gape width and dietary specialization. Our analysis provides general support for the use of traits in quantifying species ecological functions, but also highlights the need to go beyond simple metrics of functional or phylogenetic diversity to consider the multiple pathways through which traits may determine ecological processes.
Data from: Functional outcomes of mutualistic network interactions: a community-scale study of frugivore gut passage on germination
1. Current understanding of mutualistic networks is grounded largely in data on interaction frequency, yet mutualistic network dynamics are also shaped by interaction quality—the functional outcomes of individual interactions on reproduction and survival. The difficulty of obtaining data on functional outcomes has resulted in limited understanding of functional variation among a network's pairwise species interactions, of the study designs that are necessary to capture major sources of functional variation, and of predictors of functional variation that may allow generalization across networks. 2. In this community-scale study, we targeted a key functional outcome in plant-frugivore networks: the impact of frugivore gut passage on seed germination. We used captive frugivore feeding trials and germination experiments in an island ecosystem, attaining species-level coverage across all extant native frugivores and the plants they consume to 1) assess sources of functional variation, 2) separate effects of pulp removal from those of scarification via gut passage, and 3) test trait-based correlates of gut passage effect sizes. 3. We found antagonistic seed predation effects of a frugivore previously assumed to be a seed disperser, highlighting the need to consider functional outcomes rather than interaction frequency alone. The other frugivores each exhibited similar impacts for individual plant species, with benefits primarily caused by pulp removal rather than scarification, supporting the use of animal functional groups in this context. In contrast, plant species varied widely in impacts of gut passage on germination. Species with smaller seeds and more frugivore partners had larger benefits of gut passage, showing promise for network metrics and functional traits to predict functional variation among plants. 4. Synthesis. Combining network and demographic approaches, we assessed the degree and sources of variation in a key functional outcome of plant-frugivore interactions across an entire network. Using a detailed study design, our work shows how simpler study designs can capture primary sources of functional variation and that functional traits and network metrics may allow generalization across networks. Efficiently measuring and generalizing sources of functional variation within mutualistic networks will strengthen our ability to model network dynamics and predict mutualist responses to global change.
Data from: Loss of functional connectivity in migration networks induces population decline in migratory birds
Migratory birds rely on a habitat network along their migration routes by temporarily occupying stopover sites between breeding and non-breeding grounds. Removal or degradation of stopover sites in a network might impede movement, and thereby reduce migration success and survival. The extent to which the breakdown of migration networks, due to changes in land use, impacts the population sizes of migratory birds is poorly understood. We measured the functional connectivity of migration networks of waterfowl species that migrate over the East Asian-Australasian Flyway from 1992-2015. We analysed the relationship between changes in non-breeding population sizes and changes in functional connectivity, while taking into account other commonly-considered species traits, using a Phylogenetic Linear Mixed Model. We found that population sizes significantly declined with a reduction in the functional connectivity of migration networks; no other predictor variables were important. We conclude that the current decrease in functional connectivity, due to habitat loss and degradation in migration networks, can negatively and crucially impact population sizes of migratory birds. Our findings provide new insights into the underlying mechanisms that affect population trends of migratory birds under environmental changes. Establishment of international agreements leading to the creation of systematic conservation networks associated with migratory species' distributions and stopover sites may safeguard migratory bird populations.
Data from: Ditch network sustains functional connectivity and influences patterns of gene flow in an intensive agricultural landscape
In intensive agricultural landscapes, plant species previously relying on semi-natural habitats may persist as metapopulations within landscape linear elements. Maintenance of populations' connectivity through pollen and seed dispersal is a key factor in species persistence in the face of substantial habitat loss. The goals of this study were to investigate the potential corridor role of ditches and to identify the landscape components that significantly impact patterns of gene flow among remnant populations. Using microsatellite loci, we explored the spatial genetic structure of two hydrochorous wetland plants exhibiting contrasting local abundance and different habitat requirements: the rare and regionally protected Oenanthe aquatica and the more commonly distributed Lycopus europaeus, in an 83 km2 agricultural lowland located in northern France. Both species exhibited a significant spatial genetic structure, along with substantial levels of genetic differentiation, especially for L. europaeus, which also expressed high levels of inbreeding. Isolation-by-distance analysis revealed enhanced gene flow along ditches, indicating their key role in effective seed and pollen dispersal. Our data also suggested that the configuration of the ditch network and the landscape elements significantly affected population genetic structure, with (i) species-specific scale effects on the genetic neighborhood and (ii) detrimental impact of human ditch management on genetic diversity, especially for O. aquatica. Altogether, these findings highlighted the key role of ditches in the maintenance of plant biodiversity in intensive agricultural landscapes with few remnant wetland habitats.
Transposable element products, functions, and regulatory networks in Arabidopsis thaliana
<h1>README</h1> <p>This dataset includes the main outputs from the work titled <strong>Transposable element products, functions, and regulatory networks in <em>Arabidopsis thaliana</em>.</strong></p> <h2><strong>Summary</strong></h2> <p>Transposable elements (TEs) are DNA sequences with the ability to propagate themselves within and across genomes. Their mobilization is catalyzed by self-encoded factors, yet these factors have been poorly investigated due to difficulties in defining TE genes in genomes. Here, we leveraged extensive long- and short-read transcriptome data, together with structural predictions, transcription factor binding site identification, and transcriptional network analyses, to construct a comprehensive atlas of TE transcripts and TE-encoded products in the model organism <em>Arabidopsis thaliana</em>. We uncovered hundreds of transcriptionally competent TEs, each potentially encoding multiple proteins either through distinct genes, alternative splicing, or post-translational processing. Structural-based protein analyses revealed dozens of hitherto unidentified domains of unknown function, enabling us to predict proteins with multimerization and DNA binding domains forming macromolecular complexes involved in transposition. Furthermore, we demonstrate that TE expression is highly intertwined with the transcriptional network of cellular genes, and identified transcription factors and cis-regulatory elements associated with their coordinated expression during development or in response to environmental cues. This comprehensive atlas of TE-genes and TE-proteins provides a valuable resource for studying the mechanisms involved in transposition and their consequences for genome and organismal function.</p> <h2><strong>File description</strong></h2> <p>It includes the following data:</p> <ol> <li><code>annots/TE_Functional_Annotation.Borreda2024.gtf</code> - Annotation file including Arabidopsis TEs and TE-genes. TE-genes defined in our work are indicated in the 'Source' column of the gtf. TAIR10-defined TEs for whom we did not annotate new transcripts are also included.</li> <li><code>seqs</code> - This folders includes all the transcript sequences (cDNAs.tsv) and the first and longest ORFs found in each of them (prot.csv), which were used for further analyses. The specific copy, gene, isoform and, in the case of proteins, ORF, is indicated for each sequence.</li> <li><code>structures</code> - The zipped folder <code>full_length_prots_pdbs.zip</code> includes all the 3D structures from full-length TE proteins. Note that identical proteins, which would result in identical structures, have been collapsed to reduce the total dataset size; equivalences can be found in <code>identical_proteins</code>.</li> <li><code>structures/SD_Cluster_Functions.tsv</code> - We clustered all Structural Domains (SD) based on 3D similarity and assigned a function to each cluster based on the database hits. This table indicated, for each of these SDs, to which cluster it belongs, the superfamily, family and element containing it, the number of Conserved Domains included within it and the number of hits with resolved (retrieved from the RCSB-PDB database) or predicted (AlphaFold2) protein structures. The last column includes the putative function assigned to each cluster.</li> <li><code>coexpression</code> - Coexpressed genes were classiffied into modules using WGCNA. In the table <code>Gene_Modules.tsv</code> we include, for each gene and TE-gene (provided it has expression in at least one sample, see methods on the publication for details), the TE family and superfamily when applicable and the module to which it belongs. The modules were named based on the results of the GO enrichment analysis of the genes contained. The results of this GO enrichment are included in <code>GO_Enrichment.tsv</code>, where we include the main funciton of the associated GOs, the number of entries and TE-genes within the module, a list of GO terms enriched in that specific module and finally a list of TE families enriched in each module.</li> <li><code>dapseq</code> - We reanalized the DAP-seq dataset from O'Malley 2016, selecting only TFBS with a binding site within a DAP-seq peak. The list of filtered peaks we found is reported in <code>DAPseq_TFBS_Motifs.tsv</code>. The columns include the coordinates of the TFBS (which have been filtered to fall within a DAP-seq peak and include the TFBS motif), the strand of the motif, the score of the motif reported by FIMO, the motif sequence, the Sequence Read identified for the original DAP-seq data, and the family, name and gene of the TF associated with that specific peak.</li> </ol>
Functional connectivity and graph theory of self networks in toodlers with ASD
<p>The study collected fMRI data from children with autism and typical developmental disorders at 18-24 months and 25-48 months, and analyzed the brain's self network using functional connectivity and graph theory methods</p>
Data for DualNetGO: A Dual Network Model for Protein Function Prediction via Effective Feature Selection
<p>Data used in the paper, including annotation files, graph embeddings from TransformerAE, and protein attributes for both human and mouse, and for cafa3 data. Extract and place them in the <em>data </em>folder.</p>
Topographic deep neural networks predict the functional organization of the primate ventral visual pathway
<p>Recording of presentation at the Neuroscience 2021 annual meeting (held virtually). The abstract follows:</p> <p> </p> <p>The primate ventral visual pathway is organized into functional maps, including pinwheel-like arrangements of orientation-tuned neurons in primary visual cortex (V1) and patches of category-selective neurons in higher visual cortex. While deep convolutional neural networks (DCNNs) trained for object recognition accurately predict neural representations throughout the ventral pathway, they have no spatial layout for features at a given retinotopic location and are thus unable to predict the rich topographic organization of visual cortex. Here, we close this gap by first assigning each DCNN unit a position in a 2D cortical sheet, then training the network to minimize a cost function with two components: one encouraging accurate object recognition, and another favoring correlated responses among nearby units in each model layer (Figure 1A, 1B). </p> <p>We find that training with this composite spatial loss produces brain-like topographic maps in both early and later model layers (Figure 1B). Early layers contain smooth orientation preference maps with pinwheels, clusters of units preferring the same spatial frequency, and color-preference domains resembling V1 “blobs”. In a later layer of the same model, we observe clusters of category-selective units, e.g., face patches, whose spatial organization largely matches that found in primate higher visual cortex. Our model thus leverages local response correlations, which have been linked to theories of wire-length minimization, to accurately predict neuron responses and functional organization throughout the ventral visual pathway. In support of the wire-length minimization hypothesis, we find that our topographic DCNN would require shorter connections than a standard DCNN to support connections between similarly-tuned neurons within early (38% reduction) and later (31% reduction) model layers (Figure 1D). These results suggest that the functional organization of visual cortex can be explained by two constraints: the need to perform object recognition and pressure for local populations of neurons to have correlated responses.</p>
Structure, function, and control of the musculoskeletal network
<p>Supplementary data for: Structure, function, and control of the musculoskeletal network</p> <p>Table S8: The assigned homunculus categories and data driven community assignments of muscles.</p> <p>Table S9: The hypergraph of muscles and bones from the Hosford muscle tables used in the main text.</p> <p>Table S10: The hypergraph of muscles and bones from Grant's atlas used in the supplementary text.</p>
Data Release: "A neural network emulator of the Advanced LIGO and Advanced Virgo selection function"
<p>This dataset contains results presented in "<strong>A neural network emulator of the Advanced LIGO and Advanced Virgo selection function</strong>" (<a href="https://www.arxiv.org/abs/2408.16828">arXiv: 2408.16828</a>).</p> <p>The code used to generate this data and produce figures in the paper can be found at <a href="https://github.com/tcallister/learning-p-det/">https://github.com/tcallister/learning-p-det/</a>. Specific instructions about the workflow are provided in the <a href="https://tcallister.github.io/learning-p-det/">accompanying documentation</a>.</p> <p>The primary deliverable of this work is a trained neural network emulator for the compact binary selection function during the Advanced LIGO and Advanced Virgo O3 observing run. This emulator is made available in a standalone companion repository, <a href="https://github.com/tcallister/pdet">https://github.com/tcallister/pdet</a>.</p> <p>Additional information:</p> <ul> <li>The files <em>endo3_bbhpop-LIGO-T2100113-v12.hdf5</em>, <em>endo3_bnspop-LIGO-T2100113-v12.hdf5</em>, and <em>endo3_nsbhpop-LIGO-T2100113-v12.hdf5</em>, used for network training, were created and released by the LIGO-Virgo-KAGRA Collaboration at <a href="../records/7890437">https://zenodo.org/records/7890437</a>.</li> <li>The file <em>sampleDict_FAR_1_in_1_yr.pickle</em>, used during hierarchical inference, was created via code in the repository <a href="https://github.com/tcallister/get-lvk-data">https://github.com/tcallister/get-lvk-data</a>.</li> <li>Inference results (<em>popsummary_standardInjections.h5</em> and <em>popsummary_dynamicInjections.h5</em>) are provided in the <em>popsummary</em> results format; see <a href="https://git.ligo.org/christian.adamcewicz/popsummary">https://git.ligo.org/christian.adamcewicz/popsummary</a>.</li> </ul> <p>Changelog:</p> <ul> <li>v2: Added missing file <em>sampleDict_FAR_1_in_1_yr.pickle</em></li> </ul>
Dataset for the article "A deep equivariant neural network approach for efficient hybrid density functional calculations"
<p>Dataset files for DeepH-hybrid, containing structures and preprocessed Hamiltonian matrices computed with HSE06 hybrid functional and ABACUS DFT package.</p> <p>Enclosed include:</p> <ol> <li>The four datasets corresponding to the four DeepH-hybrid models mentioned in DeepH-hybrid's paper, each containing material structures and electronic structure properties of </li> <li>Basis set files for the ABACUS DFT package</li> <li>Snapshot of a version of the additional codes utilized to preprocess hybrid DFT Hamiltonians (also available via this <a href="https://github.com/aaaashanghai/DeepH-hybrid">GitHub link</a>)</li> </ol> <p>Note only the additional codes of DeepH-hybrid is provided, and it may be used in combination with DeepH-E3 package for neural-network training. For additional details please refer to the "README" file of the code.</p>
Calcium-rich parent materials enhance multiple soil functions and bacterial network complexity
Open the record for dataset details and reuse information.
Data from: Replicated landscape genetic and network analyses reveal wide variation in functional connectivity for American pikas
Landscape connectivity is essential for maintaining viable populations, particularly for species restricted to fragmented habitats or naturally arrayed in metapopulations and facing rapid climate change. The importance of assessing both structural connectivity (the physical distribution of favorable habitat patches) and functional connectivity (how species move among habitat patches) for managing such species is well understood. However, the degree to which functional connectivity for a species varies among landscapes, and the resulting implications for conservation, have rarely been assessed. We used a landscape genetics approach to evaluate resistance to gene flow and, thus, to determine how landscape and climate-related variables influence gene flow for American pikas (Ochotona princeps) in eight federally managed sites in the western United States. We used those empirically-derived, individual-based landscape resistance models in conjunction with predictive occupancy models to generate patch-based network models describing functional landscape connectivity. Metareplication across landscapes enabled identification of limiting factors for dispersal that would not otherwise have been apparent. Despite the cool microclimates characteristic of pika habitat, south-facing aspects consistently represented higher resistance to movement, supporting the previous hypothesis that exposure to relatively high temperatures may limit dispersal in American pikas. We found that other barriers to dispersal included areas with a high degree of topographic relief, such as cliffs and ravines, as well as streams and distances greater than one to four kilometers depending on the site. Using the empirically-derived network models of habitat patch connectivity, we identified habitat patches that were likely disproportionately important for maintaining functional connectivity, areas in which habitat appeared fragmented, and locations that could be targeted for management actions to improve functional connectivity. We concluded that climate change, besides influencing patch occupancy as predicted by other studies, may alter landscape resistance for pikas, thereby influencing functional connectivity through multiple pathways simultaneously. Spatial autocorrelation among genotypes varied across study sites and was largest where habitat was most dispersed, suggesting that dispersal distances increased with habitat fragmentation, up to a point. This study demonstrates how landscape features linked to climate can affect functional connectivity for species with naturally fragmented distributions, and reinforces the importance of replicating studies across landscapes.
Dataset for: Multivascular networks and functional intravascular topologies within biocompatible hydrogels
<p>Dataset for:</p> <p>Multivascular networks and functional intravascular topologies within biocompatible hydrogels</p> <p>Bagrat Grigoryan1,∗, Samantha J. Paulsen1,∗, Daniel C. Corbett2,∗, Daniel W. Sazer1, Chelsea L. Fortin2, Alexander J. Zaita1, Paul T. Greenfield1, Nicholas J. Calafat1, John P. Gounley3, Anderson H. Ta1, Fredrik Johansson2, Amanda Randles3, Jessica E. Rosenkrantz4, Jesse D. Louis-Rosenberg4, Peter A. Galie5, Kelly R. Stevens2,†, Jordan S. Miller1,†</p> <p>1Department of Bioengineering, Rice University, Houston, TX 77005, USA 2Department of Bioengineering, University of Washington, Seattle, WA 98195, USA 3Department of Biomedical Engineering, Duke University, Durham, NC 27708, USA 4Nervous System, Somerville, MA 02143, USA 5Department of Biomedical Engineering, Rowan University, Glassboro, NJ 08028, USA</p> <p>∗Equal contribution. †Corresponding authors. Email: ksteve@uw.edu (K.R.S.) and jmil@rice.edu (J.S.M.).</p> <p>Solid organs transport fluids through distinct vascular networks that are biophysically and biochemically entangled, creating complex 3D transport regimes that have remained difficult to produce and study. We establish intravascular and multivascular design freedoms with photopolymerizable hydrogels using food dye additives as biocompatible yet potent photoabsorbers for projection stereolithography. We demonstrate monolithic transparent hydrogels produced in minutes comprising efficient intravascular 3D fluid mixers and functional bicuspid valves. We further elaborate entangled vascular networks from space-filling mathematical topologies and explore the oxygenation and flow of human red blood cells during tidal ventilation and distension of a proximate airway. In addition, we deployed structured biodegradable hydrogel carriers in a rodent model of hepatic disease to highlight the potential translational utility of this materials innovation.</p>
Quality-aware Analysis and Optimisation of Virtual Network Functions
<p><strong>To watch it in Youtube:</strong></p> <p><a href="https://youtu.be/RGwIVCgANcU">https://youtu.be/RGwIVCgANcU</a></p> <p><strong>This is the live presentation of a conference paper. Please, access and cite the published version:</strong></p> <p><a href="https://doi.org/10.1145/3546932.3547007">https://doi.org/10.1145/3546932.3547007</a></p> <p>The softwarisation and virtualisation of network functionality is the last milestone in the networking industry. <em>Software-Defined Networks</em> (SDN) and <em>Network Function Virtualization</em> (NFV) offer the possibility of using software to manage computer and mobile networks and build novel <em>Virtual Network Functions</em> (VNFs) deployed in heterogeneous devices. To reason about the variability of network functions and especially about the quality of a software product defined as a set of VNFs instantiated as part of a service (i.e., Service Function Chaining), a variability model along with a quality model is required.</p> <p>However, this domain imposes certain challenges to quality-aware reasoning of service function chains, such as numerical features or configuration-level <em>Quality Attributes</em> (QAs) (e.g., energy consumption). Incorporating numerical reasoning with quality data into SPL analyses is challenging and tool support is rare. In this work, we present 3 groups of operations: model report, aggregate functions to dynamically convert QAs at the feature-level into the configuration-level, and quality-aware optimisation. Our objective is to test the most complete reasoning tools to exploit the extended variability with quality attributes needed for VNFs.</p>
Exploring functional flow heterogeneity in regulated flow regime: fish species turnover along hydraulic gradients in an artificial waterway network
<p><span>Humans have altered river flows and lateral aquatic habitats. The expansion of agriculture in floodplains has resulted in landscapes dominated by irrigated farmland. A key challenge in water management is to conserve existing ecological communities and habitat heterogeneity, while simultaneously maintaining engineered infrastructure for agriculture. In this study, we focused on an artificial channel network for irrigation with a regulated flow regime and its function as habitat for various fish species. Differences of hydraulic conditions among channels and compositional changes in fish species were examined to clarify functional flow heterogeneity. Species turnover was analyzed using pairwise Simpson dissimilarity among sampling reaches. Species turnover was positively associated with Froude number (flow intensity) differences at intermediate discharges, and with differences in cross-sectional areas (flow magnitude) at low discharges. Drastic changes in inflows should be considered for the effective conservation of flow heterogeneity, even under a regulated flow regime. Improved engineering design to manage the hydraulic environment is one option for maintaining the ecological value of lateral waterbodies in human-dominated landscapes. Our findings provide insights into the importance of functional flow heterogeneity to conserve fish species diversity.</span></p>
Enhancing Function in Later Life: Exercise and Functional Network Connectivity
ClinicalTrials.gov study NCT02068612. IPD Sharing: Not stated. Countries: 1. Publications: 4.
Harnessing Neuroplasticity of Postural Sensorimotor Networks Using Non-Invasive Spinal Neuromodulation to Maximize Functional Recovery After Spinal Cord Injury
ClinicalTrials.gov study NCT06213012. IPD Sharing: NO. Countries: 1. Publications: 0.
The Influence of Multi-domain Cognitive Training on Large-scale Structural and Functional Brain Networks in MCI
ClinicalTrials.gov study NCT03883308. IPD Sharing: Not stated. Countries: 1. Publications: 1.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.