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1,321 results for “Navigator”
Fig.5 in Neuroplasticity in desert ants (Hymenoptera: Formicidae) - importance for the ontogeny of navigation
Fig.5: 3odel for processing of navigational information and sites of structural synaptic neuroplasticity in visual pathways after first sensory exposure and following learning walks. The left side depicts sensory input from the panoramic scenery, the geo- magnetic field and the sky polarization pattern with the position of the sun.Directional sky-compass information (compass cues: global vector) is processed via the anterior optic tract (AOT) to the lateral (LX) and central complex (CX), whereas snapshots from panoramic information (panoramic memories, local vectors) are processed via the anterior superior optic tract (ASOT) to the mushroom bodies (MB). The large difference in the numbers of plastic synaptic complexes (microglomeruli,MG) at the input of the MB and LX indicated in magenta. The sensory pathways for geomagnetic information, the input of the endogenous clock for time-compensation, the connection from the MB output to the CX, and connections to the motor output are still hypothetical and depicted as dashed lines. Regions of structural (synaptic) neuroplasticity and potentially affected downstream connections highlighted in magenta (see text for details). Further abbreviations: AOTU anterior optic tubercle, KC Kenyon cell, LA lamina, LO lobula, MBON mushroom body output neuron, ME medulla, TL tangential neuron.
Fig.1 in Neuroplasticity in desert ants (Hymenoptera: Formicidae) - importance for the ontogeny of navigation
Fig.1: Individual life history and natural habitats of Cataglyphis ants. (A) The ants spend c. 4 weeks in the dark nest perform- ing interior tasks (callow, interior I, II) before they move on to perform learning walks close to the nest entrance for 2 - 3 days and finally to foraging using path integration and guidance by the panoramic scenery for c. 7 days until the ants die. The daily course of the sun (solar ephemeris) depicted as accumulated snapshots of different horizontal (azimuthal) positions across the sky together with visual panorama elements (in green) used for navigation. Further details in the text. (B) Natural habitat of Cataglyphis fortis and experimental test field in Tunisia (3enzel Chaker, Tunisia 34°57'N, 10°24'E). (C) Natural habitat of Cataglyphis nodus and experimental test field in Southern Greece. Fhotograph in (C) by Fauline Fleischmann (Schinias National Fark near 3arathon, Greece 38°08'N, 24°02'E).
Fig.4 in Neuroplasticity in desert ants (Hymenoptera: Formicidae) - importance for the ontogeny of navigation
Fig.4: Wuantitative analyses of structural synaptic plasticity in visual integration centers in the lateral complex (LX) and mush- room body (MB) of Cataglyphis brains. (A) Anti-synapsin immunolabeled distinct synaptic complexes in the MB (visual) collar. The position in the brain indicated by the square in the 3B-calyx collarin (C). (B) Anti-synapsin and f-actinphalloidin co-labeled synaptic complexes in the bulb of the lateral complex (LX). The position in the brain indicated by the rectangle in the LX in (C). The density and numbers of synaptic complexes in the MB calyx (A) and lateral complex (B) are quantified using computer guided analyses.Scale bar in (B), also valid for (A) = 10 —m. (C) Brain of Cataglyphis fortis labeled with an antibody to synapsin (magenta), f-actin stained with phallodin (green) and cell nuclei labeled with Hoechst 3458 (blue). Scale bar = 100 —m. (D) 3D reconstruction and surface rendering of the individual components of the mushroom body (upper, frontal view) and central complex (lower, ventral view) for volume analyses in the brain of Cataglyphis nodus. Scale bar = 100 —m. Further abbreviations: co collar, EB ellipsoid body, FB fan-shaped body, NO noduli,PB protocerebral bridge, li lip. Combined from STIEB & al.2012 (C) and GROB & al. (2017) (D). Whole mount images in (A) and (B) provided by Kornelia Grübel.
Fig.3 in Neuroplasticity in desert ants (Hymenoptera: Formicidae) - importance for the ontogeny of navigation
Fig.3: Two major visual pathways in the Cataglyphis brain. The visual pathway to the central complex (CX pathway, or sky-compass pathway) depicted in the right brain hemisphere of a C.fortis brain, the visual pathway to the mushroom body (MB pathway) shown on the left side. Brain labeled with an antibody to synapsin (magenta), f-actin staining by phallodin (green) and detection of cell nuclei by Hoechst 3458 (blue).Scale bar = 200 —m.Further abbreviations:AL antennal lobe,AOT anterior optic tract,AOTU anterior optic tubercle, ASOT anterior superior optic tract, co collar, CX central complex, DRA dorsal rim area, LA lamina, li lip, LO lobula, LX lateral complex, ME medulla. The brain image is from STIEB & al.(2012), and pathways combined from results by SCHMITT & al.(2016) and GROB & al. (2017).
Fig.2 in Neuroplasticity in desert ants (Hymenoptera: Formicidae) - importance for the ontogeny of navigation
Fig.2: Learning walks in Cataglyphis nodus. (Left) Path and time course of an individual learning walk around the nest entrance (black star). Time is color coded, and indicated on the left, the compass (red) is pointing north (N). Firouettes, characteristic body rotations during which the antsstop to look back to the nest entrance indicated by arrows depicting the view direction during the longest stopping phases. Scale bar = 5cm. (Upper right) Mean gaze directions during the longest stopping phases in pirouettesare not significantly different from the nest direction (the inner circle indicates Rayleigh's critical value α = 0.05; further details in FLEISCHMANN & al. 2017). (Lower right) Schematic drawing showing C.nodus performing a pirouette with a nest-directed view during a stopping phase. The green circular arrow shows the center of rotation during a pirouette. The alignments of views during pirouettes were measured and quantified by tracking the tip of the mandibles and the position of the thorax (yellow spots). Further details in the text.Images and graphs modified from FLEISCHMANN& al. (2017).
European Robotics League Consumer - Lisbon 2019 contest - FBM 2 - Navigation functionality
<p>Benchmark logs for the FBM2 benchmark: navigation functionality.</p> <p>ERL Consumer competition in Lisbon.</p>
Fish tracks and hydrodynamics at the navigation lock complex in Kwaadmechelen (Albert Canal, Belgium)
<p><strong>Description</strong></p> <p>Swimming tracks of European silver eels (Anguilla anguilla) upstream of the navigation lock complex in Kwaadmechelen (Albert Canal, Belgium), calculated with the YAPS algorithm. The swimming direction of the tracks is from square to circle. The eels were tagged with V9 and V13 Vemco transmitters, with a random burst interval of 17-33 seconds.</p> <p>The flow at the upstream side of the complex is modelled by use of CFD (Computational Fluid Dynamics) for one of the following events occurring during the fish track: filling of the Northern Lock (NL), filling of the Middle Lock (ML), filling of the Pushed Convoy Lock (PCL) and operation of the hydropower turbines.</p> <p>The left panel of each figure contains time series of parameters characterising the track, from top to bottom: fish-flow angle (angle), water velocity at the fish position (U), water acceleration at the fish position (A), distance to flow source (dist), discharge of the lock filling (flow), progress of the filling in minutes (min), fish velocity (V fish) and turning angle (turn).</p> <p><strong>Files</strong></p> <ul> <li><strong>Kwaadmechelen_study_area.jpg</strong>: air picture of the navigation lock complex, with the different structures indicated</li> <li><strong>lock_filling_passage_LOCK_ID_x.png</strong>: track during filling of a lock, followed by passage of the lock</li> <li><strong>lock_filling_nopassage_LOCK_ID_x.png</strong>: track during filling of a lock, but not followed by passage of the lock</li> <li><strong>no_flow</strong><strong>_ID_x.png</strong>: tracks during periods when no flow is present</li> <li><strong>turbine_flow_passage_xcub_ID_x.png</strong>: track during turbine operation (at ... m3/s) followed by passage via one of the turbines</li> <li><strong>turbine_flow_nopassage_xcub_ID_x.png</strong>: track during turbine operation (at ... m3/s) not followed by passage via one of the turbines</li> </ul>
Dataset for Uncovering multiscale structure in the variability of larval zebrafish navigation V2
<p>This is the dataset for reproducing the results from the paper "Uncovering multiscale structure in the variability of larval zebrafish navigation". The github repository for the code can be found here - https://github.com/GautamSridhar/Markov_Fish</p>
Robust CBF-based STL motion planning for socially responsible robot navigation in the presence of measurement noise
<p>Video of submitted paper entitled "Robust CBF-based STL motion planning for socially responsible robot navigation in the presence of measurement noise"</p>
Wide-angle simulated artificial vision enhances spatial navigation and object interaction in a naturalistic environment
<p>This folder contains the dataset and the processing code generated in the article 'Wide-angle simulated artificial vision enhances spatial navigation and object interaction in a naturalistic environment' by Hinrichs et al. </p> <p> </p>
Web-Based Location Tracking and Navigation System
<p>The project ‘Design and Implementation of a Web-Based Location Tracking and Navigation</p> <p>System’ aims to develop a real-time tracking and navigation system that utilizes web</p> <p>technologies to provide accurate location information and directions to users. To ensure the</p> <p>safety of people, goods, and vehicles, there is a need for an innovative solution to address</p> <p>navigational difficulties. Thus, a web-based location tracking system was created that tracks</p> <p>and navigates the location of a user, vehicle, or goods. The system uses Global Positioning</p> <p>System (GPS) and Global System for Mobile Communication (GSM) to track and position</p> <p>users. The tracking device, made up of an Arduino Uno R3, SIM800L module, and NEO 6M</p> <p>GPS module, continuously monitors a moving user by interfacing serially with a GSM module</p> <p>and GPS module. The GPS module provides data like longitude and latitude, while the GSM</p> <p>module sends the user's position to a remote place. The user’s position can be viewed on a</p> <p>digital map using Google Maps API. The software includes a web application with Nodejs as</p> <p>the backend server and Firebase as the database host, while the frontend is developed using</p> <p>HTML, CSS, BOOTSTRAP framework, and JavaScript with Google Maps API embedded.</p> <p>The Firebase real-time database stores all GPS data and the Google Map API displays the</p> <p>location information on a Google Map. Test and Simulation were carried out in various areas</p> <p>of Ogun State to show the project’s flexibility and ease of use, the proposed system will offer</p> <p>an efficient and reliable way of navigating unfamiliar locations and will be useful tool for both</p> <p>individual and commercial use.</p>
Cognitive maps in the wild: Revealing the use of metric information in black howler monkeys' route navigation
<p>When navigating, wild animals rely on internal representations of the external world to take movement decisions – called "cognitive maps". As a rule, flexible navigation is hypothesized to be supported by sophisticated spatial skills (i.e., Euclidean cognitive maps); however, constrained movements along habitual routes is the most commonly reported navigation strategy. Even though incorporating metric information (i.e., distances and angles between locations) in route-based cognitive maps would likely enhance an animal's navigation efficiency, there has been no evidence of this strategy reported for non-human animals to date. Here, we examine the properties of the cognitive map used by a wild population of primates by testing a series of cognitive hypotheses against spatially-explicit movement simulations. We collected 3104 hours of ranging and behavioural data on five groups of black howler monkeys (<i>Alouatta pigra</i>) at Palenque National Park, Mexico, from September 2016 through August 2017. We simulated correlated-random walks mimicking the ranging behaviour of the study subjects and tested for differences between observed and simulated movement patterns. Our results indicated that black howler monkeys engaged in constrained movement patterns characterized by a high path recursion tendency, which limited their capacity to travel in straight lines and approach feeding trees from multiple directions. In addition, we found that the structure of observed route networks was more complex and efficient than simulated route networks, suggesting that black howler monkeys incorporate metric information into their cognitive map. Our findings not only expand the use of metric information during route navigation to non-human animals but also highlight the importance of considering efficient route-based navigation as a cognitively demanding mechanism.</p>
Comparison of a system using the MROS metacontroller to a benchmark system (Baseline) for a navigation mission
<p>The data from this navigation mission experiment of the paper "MROS: Runtime AdaptationFor Robot Control Architectures" can be found in this repo.</p>
Data from: Odor motion sensing enhances navigation of complex plumes
<p>Odor plumes in the wild are spatially complex and rapidly fluctuating structures carried by turbulent airflows. To successfully navigate plumes in search of food and mates, insects must extract and integrate multiple features of the odor signal, including odor identity, intensity, and timing. Effective navigation requires balancing these multiple streams of olfactory information and integrating them with other sensory inputs, including visual and mechanosensory cues. Studies dating back a century have indicated that, of these many sensory inputs, the wind provides the main directional cue in turbulent plumes, leading to the longstanding model of insect odor navigation as odor-elicited upwind motion. Here, we show that <em>Drosophila</em> shape their navigational decisions using an additional directional cue – <em>the direction of motion of odors</em> – which they detect using temporal correlations in the odor signal between their two antennae. Using a high-resolution virtual reality paradigm to deliver spatiotemporally complex fictive odors to freely-walking flies, we demonstrate that such odor direction sensing employs algorithms analogous to those in visual direction sensing. Combining simulations, theory, and experiments, we show that odor motion contains valuable directional information absent from the airflow alone and that both Drosophila and virtual agents are aided by that information in navigating naturalistic plumes. The generality of our findings suggests that odor direction sensing may exist throughout the animal kingdom and could improve olfactory robot navigation in uncertain environments. </p>
Data for: A neural circuit for wind-guided olfactory navigation
<p>To navigate towards a food source, animals must frequently combine odor cues that tell them what sources are useful with wind direction cues that tell them where the source can be found. Where and how these two cues are integrated to support navigation is unclear. Here we identify a pathway to the Drosophila fan-shaped body (FB) that encodes attractive odor and promotes upwind navigation. We show that neurons throughout this pathway encode odor, but not wind direction. Using connectomics, we identify FB local neurons called h∆C that receive input from this odor pathway and a previously described wind pathway. We show that h∆C neurons exhibit odor-gated, wind direction-tuned activity, that sparse activation of h∆C neurons promotes navigation in a reproducible direction, and that h∆C activity is required for persistent upwind orientation during odor. Based on connectome data, we develop a computational model showing how h∆C activity can promote navigation towards a goal such as an upwind odor source. Our results suggest that odor and wind cues are processed by separate pathways and integrated within the FB to support goal-directed navigation.</p>
Activation of Human Visual Area V6 during Egocentric Navigation with and without visual Experience
<p>V6 is a retinotopic area located in the dorsal visual stream that integrates eye movements with retinal and visuo-motor signals. Despite the known role of V6 in visual motion, it is unknown whether it is involved in navigation and how sensory experiences shape its functional properties. We explored the involvement of V6 in egocentric navigation in sighted and in congenitally blind (CB) participants navigating via an in-house distance-to-sound sensory substitution device (SSD), the EyeCane. We performed two fMRI experiments on two independent datasets. In the first experiment, CB and sighted participants navigated the same mazes. The sighted performed the mazes via vision, while the CB via audition. The CB performed the mazes before and after a training session using the EyeCane SSD. In a second experiment a group of sighted people performed a motor topography task. Our results show that right V6 (rhV6) is selectively involved in egocentric navigation independently of the sensory modality used. Indeed, after training, rhV6 of CB is selectively recruited for auditory navigation, similar to rhV6 in the sighted. Moreover, we found activation for body movement in area V6, that can putatively contribute to its involvement in egocentric navigation. Taken together, our findings suggest that area rhV6 is a unique hub that transforms spatially relevant sensory information into an egocentric representation for navigation. While vision is clearly the dominant modality, rhV6 is in fact a supramodal area that can develop its selectivity for navigation in the absence of visual experience.</p>
Data used in Knowledge Transfer Research for Drone Navigation
<p>Data used in Knowledge Transfer Research for Drone Navigation.</p>
Supplementary Video for Hierarchical Vision Navigation System for Quadruped Robots with Foothold Adaptation Learning
<p>This file contains video of the real world experiments presented in the paper "Hierarchical Vision Navigation System for Quadruped Robots with Foothold Adaptation Learning". </p> <p>It also provides a high-level overview of the motivation and the theory developed in the paper.<br> </p>
New Challenges for Gender Equality in AI: Navigating the Ethical and Social Implications.- 1st SPATIAL podcast episode
<p>Gender bias can penetrate AI systems through multiple avenues, posing a significant challenge in ensuring fair and equitable outcomes. From historical biases ingrained in the data to biased data selection methods, these factors contribute to biased AI systems. Recognizing the implications of gender bias in AI is crucial, as it impacts various domains such as social media advertising, job recruitment, smart devices, facial recognition, and voice recognition. To strive for equity, it is essential to understand the interconnectedness of different social and political identities, emphasizing intersectionality and the need to avoid generalizing experiences.</p> <p>In the first episode of the <a href="https://spatial-h2020.eu/">SPATIAL </a>podcast, we had the privilege of conversing with Marcus Westberg, postdoctoral researcher and project manager at <a href="https://www.tudelft.nl/">TU Delft</a>, the coordinator of the SPATIAL project.</p>
Data repository for "Navigating trade-offs and sustainable development pathways in the Andean water-energy-food-ecosystem nexus"
<p>Data and code supporting the research article: Navigating trade-offs and sustainable development pathways in the Andean water-energy-food-ecosystem nexus.</p>
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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.