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149 results for “network connectivity”
Feature attention graph neural network for estimating brain age and identifying important neural connections in mouse models of genetic risk for Alzheimer's disease
<p>Connectome, traits and behavior data for APOE234 mice.</p> <ul> <li>1. connectome.zip: mouse brain structural connectivity matrices from diffusion MRI.</li> <li>2. FAGNN_Phenotype.csv: a sheet of trait information of mice used in the study.</li> </ul> <p>columns: winding numbers, total distance, normalized NE time, normalized NE distance, normalized NW time, normalized NW distance, normalized SE time, normalized SE distance, normlaized SW time, normalized SW distance, island latency to first entry, island entries, normalized thigmataxis time, and normalized thigmotaxis distance</p> <div>rows: 4 trials for each day from day 1 to day 5 with 1 probing test each at day 5 and day 8</div> <ul> <li>3. mouse_anatomy.csv: brain region information regarding the connectivity matrix.</li> <li>4. behavior.zip: behavioral data for each mouse from Morris Water Maze experiments.</li> </ul>
Total Family Resemblance Network: Virtual - 20000 connections in Gephi
<p>This is the rendering of the entire network on a large scale with additional zoomed-in views for better clarity. The size of the feature nodes is proportional to their degree. The degree of a node is defined by its number of connections. Therefore, nodes with a greater degree are represented as larger in size. This variation in size effectively embeds an additional dimension of information into the network’s structure.</p> <div>These perspectives enhance the readability of specific sections of the network and add depth to the representation, thereby illustrating the complexity and intricacies of the relationships within it.</div> <div>The view of the center closely resembles a weave or fabric due to the sheer volume of connections, creating an effect where the edges themselves seem indistinguishable, collectively forming a fabric-like structure. This representation invites multiple interpretations: it illustrates the dynamic and continually evolving nature of the concept, where new connections and features are perpetually integrated, further enriching the network; it signifies a high level of integration, suggesting that understanding one semantic feature likely leads to insights into others; and it implies that a segmented approach might not suffice for fully comprehending and analyzing this concept. Instead, a holistic view, considering the synergy and cumulative impact of various features, might be more effective in grasping the concept.</div>
Network analyses reveal the role of large snakes in connecting feeding guilds in a species-rich Amazonian snake community
<p class="normal">In ecological communities, interactions between consumers and resources lead to the emergence of ecological networks and a fundamental problem to solve is to understand which factors shape network structure. Empirical and theoretical studies on ecological networks suggest predator body size is a key factor structuring patterns of interaction. Because larger predators consume a wider resource range, including the prey consumed by smaller predators, we hypothesized that variation in body size favors the rise of nestedness. In contrast, if resource consumption requires specific adaptations, predators are expected to consume distinct sets of resources, thus favoring modularity. We investigate these predictions by characterising the trophic network of a species-rich Amazonian snake community (62 species). Our results revealed an intricate network pattern resulting from larger species feeding on higher diversity of prey, promoting nestedness, and specific lifestyles feeding on distinct resources, promoting modularity. Species removal simulations indicated that the nested structure is favored mainly by the presence of five species of the family Boidae, which because of their body size and generalist lifestyles connect modules in the network. Our study highlights the particular ways traits affect the structure of interactions among consumers and resources at the community level.</p>
Connecting Intelligence and Smart Orchestration for B5G/6G Networks
<p>Hexa-X project will pave the way towards future 6G system concepts by explorative research. Hexa-X is working out a set of 6G technology enablers to interconnect human, physical, and digital worlds. An essential tool to empower this 6G vision is the application of Artificial Intelligence (AI)/Machine Learning (ML) technologies to significantly improve efficiency and service experience by the research on "Connecting Intelligence". Wide exploration on the potential of AI/ML is necessary to monetise generated data and optimize network management. This can substantially enhance the cost, energy consumption, trust level and service efficiency of network infrastructure. AI allows networks to faster and more precisely adapt to scenarios and traffic demand by acting on predictive orchestration mechanisms in future 6G. Network orchestration should incorporate a complete end-to-end perspective in its decisions and enforcing actions from far edge/devices to RAN disaggregated functions, edge computing, core and cloud elements. This presentation will give an overview on the research and application of AI/ML algorithms to a holistic network orchestration and smart service management.</p>
Differences in network structure and connectivity of four (protected) Palearctic-Afrotropical flyways
<p class="MsoNormal"><em><span>Aim – </span></em><span>Waterbirds that travel seasonally between Europe and Africa use wetlands along four major Palearctic-Afrotropical flyways. However, it is unknown to what extent the overall connectivity of these flyways may be threatened by ongoing habitat loss and degradation. Here, we contrasted the wetland connectivity along these four flyways, applying graph-theoretic connectivity metrics on an intercontinental scale. We also explored for which flyway connectivity is most at risk. We then identified the most important wetlands by their contribution to connectivity in each flyway. </span></p> <p class="MsoNormal"><em><span>Location – </span></em><span>Western Palearctic, Afrotropics</span></p> <p class="MsoNormal"><em><span>Methods – </span></em><span>Based on high-resolution wetland maps, we calculated directional probabilistic connectivity metrics. Estimates of overall connectivity of each flyway were obtained, as well as the relative importance of wetlands, for birds with different migration strategies: short-distance hoppers and long-distance jumpers.</span></p> <p class="MsoNormal"><em><span>Results – </span></em><span>The East-Atlantic flyway and Eastern Mediterranean flyway had higher overall functional connectivity than the two central routes, reflecting the larger barrier represented by the Mediterranean Sea and Sahara Desert. Fewer than 5% of all wetlands supported more than 70% of the total connectivity of the network in each flyway, regardless of the considered migration strategy. These wetlands were either large, strategically positioned, or both. Removing non-protected wetlands from the analysis showed that the connectivity of some flyways could be jeopardised and that the East-Atlantic and Eastern Mediterranean flyway may be most vulnerable to additional habitat loss. </span></p> <p class="MsoNormal"><em><span>Main conclusions – </span></em><span>Our results illustrate (1) the major contribution of unprotected wetlands to flyway connectivity, (2) the importance of integrating migration ecology into site-based connectivity analyses, and (3) the utility of graph-based connectivity metrics to inform conservation prioritisation under present and future scenarios.</span></p>
Forest cover and connectivity have pervasive effects on the maintenance of evolutionary distinct interactions in seed dispersal networks
<p>Seed dispersal by animals is one of the most important ecological processes in tropical forests, entailing millions of years of evolutionary adaptations of plants and frugivorous animals forming networks of interactions that, ultimately, contribute to the resilience of such forests. We analyze 29 seed dispersal networks in the threatened Atlantic Forest biodiversity hotspot, with data on the frequency of feeding visits by birds to fruiting plants to answer: (1) which are the effects of forest cover and landscape connectivity on the maintenance of phylogenetic diversity (PD) of interacting birds and plants and the evolutionary distinctiveness of the interactions (EDi) between them; and (2) how EDi and plant/bird PD affects the robustness of the interaction networks? We found that forest cover positively influences both plant and bird PD and EDi. Landscape connectivity is an important predictor of bird PD, but not plant PD, suggesting that the spatial arrangement of forest remnants is essential for guaranteeing bird movement among forest fragments. Furthermore, interaction networks of areas with higher PD and EDi had great robustness to the simulated extinction of species, which underscore the importance of larger forest blocks for conserving evolutionary information and, consequently, the health and natural resistance of seed dispersal networks against environmental change.</p>
Data from: Network analysis of sea turtle movements and connectivity: a tool for conservation prioritization
<p><strong>Aim</strong>: Understanding the spatial ecology of animal movements is a critical element in conserving long-lived, highly mobile marine species. Analysing networks developed from movements of six sea turtle species reveals marine connectivity and can help prioritize conservation efforts.</p> <p><strong>Location</strong>: Global.</p> <p><strong>Methods</strong>: We collated telemetry data from 1,235 individuals and reviewed the literature to determine our dataset's representativeness. We used the telemetry data to develop spatial networks at different scales to examine areas, connections, and their geographic arrangement. We used graph theory metrics to compare networks across regions and species and to identify the role of important areas and connections.</p> <p><strong>Results</strong>: Relevant literature and citations for data used in this study had very little overlap. Network analysis showed that sampling effort influenced network structure and the arrangement of areas and connections for most networks was complex. However, important areas and connections identified by graph theory metrics can be different than areas of high data density. For the global network, marine regions in the Mediterranean had high closeness while links with high betweenness among marine regions in the South Atlantic were critical for maintaining connectivity. Comparisons among species-specific networks showed that functional connectivity was related to movement ecology, resulting in networks composed of different areas and links.</p> <p><strong>Main conclusions</strong>: Network analysis identified the structure and functional connectivity of the sea turtles in our sample at multiple scales. These network characteristics could help guide the coordination of management strategies for wide-ranging animals throughout their geographic extent. Most networks had complex structures that can contribute to greater robustness, but may be more difficult to manage changes when compared to simpler forms. Area-based conservation measures would benefit sea turtle populations when directed towards areas with high closeness dominating network function. Promoting seascape connectivity of links with high betweenness would decrease network vulnerability.</p>
Microbiome network connectivity and composition linked to disease resistance in strawberry plants
<p>The two R data files correspond phyloseq objects used in the study. The file phyloseq_nochim_silva.RData and phyloseq_nochim_unite.RData correspond to bacterial and fungal phyloseq objects, respectively. Both objects include count table, taxonomy table and metadata information. </p>
Analyses, data and figures related to: "Connecting ships: Using dendrochronological network analysis to determine the wood provenance of Roman-period river barges found in the Lower Rhine region and visualise wood use patterns"
<p>Analyses, data and figures related to: "Connecting ships: using dendrochronological network analysis to determine the wood provenance of Roman-period river barges found in the Lower Rhine region and to visualise patterns of wood use" by Ronald M. Visser (Saxion University of Applied Sciences, Deventer, the Netherlands) and Yardeni Vorst (Vorst wood research, Zaandam, the Netherlands) submitted to the International Journal of Wood Culture</p>
Activation and connectivity maps - A chronometric relationship between circuits underlying learning and error monitoring in the basal ganglia and salience network
<p>Activation and connectivity maps of the study "A chronometric relationship between circuits underlying learning and error monitoring in the basal ganglia and salience network".</p> <ul> <li>Error-correct.nii corresponds to the statistical map of group-level differences in BOLD signal between correct and erroneous responses shown in figure 4;</li> <li>Late-initial.nii corresponds to the statistical map of group-level differences in BOLD signal between the initial and late learning periods shown in figure 5;</li> <li>Conn_error-correct_dACC.nii corresponds to the results from the seed-to-voxel gPPI analysis, using the dACC as seed region, showing areas of higher functional connectivity in erroneous compared to correct responses, shown in figure 8.</li> </ul>
Data of "Multilayer spintronic neural networks with radio-frequency connections"
<p>This dataset corresponds to the open data of the publication <strong>"Multilayer spintronic neural networks with radio-frequency connections"</strong>.</p>
almost 3000 Networks (unweighted, undirected, simple, connected) from Network Repository
<p><strong>Data</strong></p> <p>All networks from <a href="https://networkrepository.com"><code>networkrepository.com</code></a> [1] with at most 1M edges (fall 2020) with the following modifications:</p> <ul> <li>weights and edge directions have been ignored</li> <li>multi-edges and self loops have been removed, i.e., the graphs are simple</li> <li>each graph has been reduced to its largest connected component</li> <li>for isomorphic graphs, only one copy has been kept</li> </ul> <p>[1] Ryan A. Rossi and Nesreen K. Ahmed, <em>The Network Data Repository with Interactive Graph Analytics and Visualization</em> (AAAI 2015)</p> <p><strong>Format</strong></p> <p>The data format is a simple edge list:</p> <ul> <li>each row contains two numbers <em>u</em> and <em>v </em>separated by a space representing an edge <em>{u, v}</em></li> <li>for a graph with <em>n</em> vertices, the numbers range from <em>0 </em>to <em>n - 1</em></li> <li>for each edge <em>{u, v} </em>only one of the pairs <em>u v</em> or <em>v u</em> is present, i.e., if the graph has <em>m</em> edges, the file contains <em>m</em> rows</li> </ul>
Catastrophes, connectivity and Allee effects in the design of marine reserve networks
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Functional connectivity in human auditory networks and the origins of variation in the transmission of musical systems
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Efficient sub-pixel fully connected neural network: an intelligent fault diagnosis method for signal resolution enhancement
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Designing conservation networks to ensure connectivity in a changing climate: application to Spanish forests
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SciStarter: exploring project connections across the citizen science landscape: a social network analysis of shared volunteers
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Network analyses reveal the role of large snakes in connecting feeding guilds in a species-rich Amazonian snake community
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Data from: Connectivity loss in experimental pond networks leads to biodiversity loss in microbial metacommunities
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Data from: Simulated poaching affects global connectivity and efficiency in social networks of African savanna elephants—An exemplar of how human disturbance impacts group-living species
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ScienceDex guides
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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.