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317 results for “Hierarchy”
Data from: Tropical arboreal ants form dominance hierarchies over nesting resources
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Data from: Contingency rules for pathogen competition and antagonism in a genetically based, plant defense hierarchy
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Data from: Fighting over food unites the birds of North America in a continental dominance hierarchy
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Data for: Hierarchial motor adaptations negotiate failures during force field learning
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Data from: Native plant traits and invasibility of restored communities: Importance of environmental context and trait hierarchies
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The glutamatergic projection from the substantia nigra pars reticulata to the dorsal raphe nucleus facilitates social hierarchy in mice
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Relationship between dominance hierarchy steepness and rank-relatedness of benefits in primates
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Social hierarchy reveals thermoregulatory trade-offs in response to repeated stressors
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The effects of female group-changing behavior on female-female aggression, female rank, and female hierarchy stability
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Hierarchy of fear: experimentally testing ungulate reactions to lion, African wild dog and cheetah
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Data from: The stronger, the better – trait hierarchy is driving alien species interaction
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Data from: Hierarchy in structuring of resource selection: Understanding elk selection across space, time, and movement strategies
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A hierarchy of global ocean models coupled to CESM1
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Reactome HSA v71 pathways and hierarchy
<p>Originally from:<strong> https://reactome.org/download-data</strong><br> Version 71: <strong>https://reactome.org/about/news/145-version-71-releases</strong></p> <p>What was done here:<br> Top pathways found in <strong>https://reactome.org/PathwayBrowser/</strong> were manually added as children to the parent R-HSA-0000000 in the file "NewestReactomeNodeRelations.txt". These top pathway descriptions were also added to the file "Top_Human_REACTOME_Nodes_ManualCuration.txt"</p> <p>The rest of the pathway parent child relationships were taken from:<br> <strong>https://reactome.org/download/current/ReactomePathwaysRelation.txt</strong><br> but only the R-HSA pathways were used and added to the file "NewestReactomeNodeRelations.txt"</p> <p>The pathway definitions are the ones found in<br> "Ensembl2Reactome_All_Levels_v71.txt"<br> </p>
Data from: The evolutionary origins of hierarchy
Hierarchical organization—the recursive composition of sub-modules—is ubiquitous in biological networks, including neural, metabolic, ecological, and genetic regulatory networks, and in human-made systems, such as large organizations and the Internet. To date, most research on hierarchy in networks has been limited to quantifying this property. However, an open, important question in evolutionary biology is why hierarchical organization evolves in the first place. It has recently been shown that modularity evolves because of the presence of a cost for network connections. Here we investigate whether such connection costs also tend to cause a hierarchical organization of such modules. In computational simulations, we find that networks without a connection cost do not evolve to be hierarchical, even when the task has a hierarchical structure. However, with a connection cost, networks evolve to be both modular and hierarchical, and these networks exhibit higher overall performance and evolvability (i.e. faster adaptation to new environments). Additional analyses confirm that hierarchy independently improves adaptability after controlling for modularity. Overall, our results suggest that the same force–the cost of connections–promotes the evolution of both hierarchy and modularity, and that these properties are important drivers of network performance and adaptability. In addition to shedding light on the emergence of hierarchy across the many domains in which it appears, these findings will also accelerate future research into evolving more complex, intelligent computational brains in the fields of artificial intelligence and robotics.
Data from: Stream hierarchy defines riverscape genetics of a North American desert fish
Global climate change is apparent within the Arctic and the south-western deserts of North America, with record drought in the latter reflected within 640 000 km2 of the Colorado River Basin. To discern the manner by which natural and anthropogenic drivers have compressed Basin-wide fish biodiversity, and to establish a baseline for future climate effects, the Stream Hierarchy Model (SHM) was employed to juxtapose fluvial topography against molecular diversities of 1092 Bluehead Sucker (Catostomus discobolus). MtDNA revealed three geomorphically defined evolutionarily significant units (ESUs): Bonneville Basin, upper Little Colorado River and the remaining Colorado River Basin. Microsatellite analyses (16 loci) reinforced distinctiveness of the Bonneville Basin and upper Little Colorado River, but subdivided the Colorado River Basin into seven management units (MUs). One represents a cline of three admixed gene pools comprising the mainstem and its lower-gradient tributaries. Six others are not only distinct genetically but also demographically (i.e. migrants/generation <9.7%). Two of these (i.e. Grand Canyon and Canyon de Chelly) are defined by geomorphology, two others (i.e. Fremont-Muddy and San Raphael rivers) are isolated by sharp declivities as they drop precipitously from the west slope into the mainstem Colorado/Green rivers, another represents an isolated impoundment (i.e. Ringdahl Reservoir), while the last corresponds to a recognized subspecies (i.e. Zuni River, NM). Historical legacies of endemic fishes (ESUs) and their evolutionary potential (MUs) are clearly represented in our data, yet their arbiter will be the unrelenting natural and anthropogenic water depletions that will precipitate yet another conservation conflict within this unique but arid region.
Data from: Inferring longitudinal hierarchies: framework and methods for studying the dynamics of dominance
1. Social inequality is a consistent feature of animal societies, often manifesting as dominance hierarchies, in which each individual is characterized by a dominance rank denoting its place in the network of competitive relationships among group‐members. Most studies treat dominance hierarchies as static entities despite their true longitudinal, and sometimes highly dynamic, nature. 2. To guide study of the dynamics of dominance, we propose the concept of a longitudinal hierarchy: the characterization of a single, latent hierarchy and it's dynamics over time. Longitudinal hierarchies describe the hierarchy position (r) and dynamics (∆) associated with each individual as a property of its interaction data, the periods into which these data are divided based on a period delineation rule (p), and the method chosen to infer the hierarchy. Hierarchy dynamics result from both active (∆a) and passive (∆p) processes. Methods that infer longitudinal hierarchies should optimize accuracy of rank dynamics as well as of the rank orders themselves, but no studies have yet evaluated the accuracy with which different methods infer hierarchy dynamics. 3. We modify three popular ranking approaches to make them better suited for inferring longitudinal hierarchies. Our three 'informed' methods assign ranks that are informed by data from the prior period rather than calculating ranks de novo in each observation period, and use prior knowledge of dominance correlates to inform placement of new individuals in the hierarchy. These methods are provided in an R package. 4. Using both a simulated dataset and a long‐term empirical dataset from a species with two distinct sex‐based dominance structures, we compare the performance of these methods and their unmodified counterparts. We show that choice of method has dramatic impacts on inference of hierarchy dynamics via differences in estimates of ∆a. Methods that calculate ranks de novo in each period overestimate hierarchy dynamics, but incorporation of prior information leads to more accurately inferred ∆a. Of the modified methods, Informed MatReorder infers the most conservative estimates of hierarchy dynamics and Informed Elo infers the most dynamic hierarchies. 5. This work provides crucially needed conceptual framing and methodological validation for studying social dominance and its dynamics.
Functional Connectivity Development along the Sensorimotor-Association Axis Enhances the Cortical Hierarchy
<p><span>Human cortical maturation has been posited to be organized along the sensorimotor-association axis, a hierarchical axis of brain organization that spans from unimodal sensorimotor cortices to transmodal association cortices. Here, we investigate the hypothesis that the development of functional connectivity during childhood through adolescence conforms to the cortical hierarchy defined by the sensorimotor-association axis. We tested this pre-registered hypothesis in four large-scale, independent datasets (total <em>n </em>= 3,355; ages 5-23 years): the Philadelphia Neurodevelopmental Cohort (<em>n </em>= 1,207), Nathan Kline Institute-Rockland Sample (<em>n</em> = 397), Human Connectome Project: Development (<em>n</em> = 625), and Healthy Brain Network (<em>n</em> = 1,126). Across datasets, the development of functional connectivity systematically varied along the sensorimotor-association axis. Connectivity in sensorimotor regions increased, whereas connectivity in association cortices declined, refining and reinforcing the cortical hierarchy. These consistent and generalizable results establish that the sensorimotor-association axis of cortical organization encodes the dominant pattern of functional connectivity development. <strong><span> </span></strong><span> </span></span></p>
Supporting Software Maintenance with Dynamically Generated Document Hierarchies
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Uncertainty in Pedestrian Decision-Making in Urgent Scenarios Modulates Multi-Level Neural Hierarchies from Perception to Execution
<p><span>In urgent traffic scenarios, pedestrians exhibit decision-making uncertainty, significantly influencing safe interaction dynamics with automated vehicles. However, the inherent mechanisms of such decision behavior remain inadequately understood. To address this gap, we designed dynamic interactive stimulus experiments to replicate pedestrian-vehicle interactions in urgent scenarios, incorporating spatiotemporal pressure and introducing substantial penalties for decision failures. We employed multimodal data analysis, including behavioral data, electroencephalography (EEG) and eye-tracking data, to investigate the influence of urgency on uncertainty in decision-making and the underlying multi-level neural processes. Our findings demonstrate that as the urgency of the stimulus increases, humans adjust their decision objectives, resulting in an initial decrease followed by an increase in decision uncertainty when dealing with more urgent stimuli. Specifically, urgency augments top-down perceptual processes during the early perception stage. <span>Such a mechanism implies an enhanced dependence on prior experiences for perceptual </span></span><span><span><span>decision<span>-making in high-urgency situations. </span></span></span></span><span>While urgency accelerated motion preparation time during the decision-execution stage, it is noteworthy that the culmination of evidence accumulation (represented by the CPP peak) manifested later than the actual response. These results suggest that insufficient perceptual information and evidence accumulation may increase decision-making uncertainty. Our experimental study unveils a correlation between human decision-making uncertainty and scenario urgency, particularly within a defined urgency range. </span></p>
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.