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45 results for “Visual selection”
Data from: Olfactory and visual plant cues as drivers of selective herbivory
Food quality is an important consideration in the foraging strategy of all animals, including herbivores. Those that can detect and assess the nutritional value of plants from afar, using senses such as smell and sight, can forage more efficiently than those that must assess food quality by taste alone. Selective foraging not only affects herbivore fitness but can influence the structure and composition of plant communities, yet little is known about how olfactory and visual cues help herbivores to find preferred plants. We tested the ability of a free-ranging, generalist mammalian browser, the swamp wallaby Wallabia bicolor, to use olfactory and visual plant cues to find and/or browse differentially on Eucalyptus pilularis seedlings grown under different nutrient conditions. Low-nutrient seedlings differed from high-nutrient seedlings, having lighter coloured leaves, red stems and lower biomass and nitrogen content. In the absence of visual cues, wallabies used odour to differentiate vials containing cut seedlings. They visited and investigated patches with high-nutrient seedling odour most, followed by patches with low-nutrient seedling odour, and patches with no added odour least. However, when visual and olfactory cues of seedlings were present, wallabies reversed their foraging response and were more likely to browse low- than high-nutrient seedlings. This browsing difference, in turn, disappeared when long-range visual cues were reduced by pinning seedlings horizontal to the ground. We suggest that visual cues overrode the effects of olfactory cues on browsing patterns of intact seedlings. Our study shows that herbivores can respond to odours of higher nutrient plants but in ecologically realistic scenarios they use a variety of visual and olfactory cues, with a context-dependent outcome that is not always selection of high nutrient food. Our results demonstrate the importance of testing the sensory abilities of herbivores in realistic multi-sensory settings to understand their function in selective foraging.
Dataset from: "Selective weighting of action-related feature dimensions in visual working memory"
<p>Dataset from the following publication:</p> <p>Heuer, A. & Schubö, A. (2016). Selective weighting of action-related feature dimensions in visual working memory. <em>Psychonomic Bulletin & Review.</em> doi:10.3758/s13423-016-1209-0</p>
Emergence of Emotion Selectivity in Deep Neural Networks Trained to Recognize Visual Objects
<h1>Datasets and analysis code of the following publication:</h1> <p>Peng Liu, Ke Bo, Mingzhou Ding and Ruogu Fang (2024). Emergence of Emotion Selectivity in Deep Neural Networks Trained to Recognize Visual Objects. <em>PLOS Computational Biology. </em>DOI: 10.1371/journal.pcbi.1011943</p> <p>For any questions please contact the first author at mail pliu1 [at] ufl [dot] edu</p> <h2><strong>Contents:</strong></h2> <p><strong> Code_DataAnalysis</strong><br> - Extracted Selectivity</p> <p> -- IAPS and NAPS datasets</p> <p> -- Neurons In Alexnet and VGG networks</p> <p> --Networks are pre-trained on ImageNet and randomly initialized</p> <p> - Extracted Overlapped Selectivity across IAPS and NAPS.</p> <p> - Extracted tuning performance changes from two datasets and the VGG network</p> <p> -Code to replicate the key results including </p> <p> --Tuning quality </p> <p> -- Number of overlapped neurons</p> <p> -- Enhance neuron activity</p> <p> -- Lesion neurons</p> <p> <strong>TrainedNetworks</strong></p> <p> --Pre-trained VGG network on ImageNet </p> <p> --Pre-trained Alexnet network on ImageNet</p> <p>After pre-training these networks on ImageNet, we fixed their weights and trained them to classify pleasant, neutral, and unpleasant images into three emotion categories using both IAPS and NAPS datasets.<br> </p> <p><strong>Image datasets</strong></p> <p>Access image datasets by request from https://csea.phhp.ufl.edu/media/iapsmessage.html for IAPS and https://lobi.nencki.edu.pl/research/8/ for NAPS.</p>
Data from: Evolutionary analyses of visual opsin genes in frogs and toads: diversity, duplication, and positive selection
<p>Data from: Evolutionary analyses of visual opsin genes in frogs and toads: diversity, duplication, and positive selection</p>
Dataset and code for "Tiltable objective microscope visualizes selectivity for head motion direction and dynamics in zebrafish vestibular system", Nat Commun 13, 7622 (2022). https://doi.org/10.1038/s41467-022-35190-9
<p>Dataset and code for "Tiltable objective microscope visualizes selectivity for head motion direction and dynamics in zebrafish vestibular system", Tanimoto, Watakabe, and Higashijima.</p> <p> </p> <p>The spreadsheet files contain source data for the figures.</p> <p>The file named "register_rotated_images_demo.zip" contains the MATLAB code, example image data, and instruction text data. To use the code, unzip the file and follow the instructions in the "readme.txt" file. The file named "register_rotated_images_demo_output.zip" contains expected output image data.</p> <p> </p>
Impact of Patient Selected Visual Art in the Hospital Room During Antepartum Admission on Hospital Satisfaction Scores and Patient Experience
ClinicalTrials.gov study NCT06790043. IPD Sharing: UNDECIDED. Countries: 1. Publications: 7.
Investigation of Relations Between Edinburgh Visual Gait Score and Selective Motor Control for Children With CP
ClinicalTrials.gov study NCT04686630. IPD Sharing: YES. Countries: 1. Publications: 1.
Data from: Control of adaptive action selection by secondary motor cortex during flexible visual categorization
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Data from: Olfactory and visual plant cues as drivers of selective herbivory
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Spatial point pattern analysis of traces (SPPAT): an approach for visualizing and quantifying site-selectivity patterns of drilling predators
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Data from: Selective visual representation of letters and words in the left ventral occipito-temporal cortex with intracerebral recordings
We report a comprehensive cartography of selective responses to visual letters and words in the human ventral occipito-temporal cortex (VOTC) with direct neural recordings, clarifying key aspects of the neural basis of reading. Intracerebral recordings were performed in a large group of patients (n = 37) presented with visual words inserted periodically in rapid sequences of pseudofonts, nonwords, or pseudowords, enabling classification of responses at three levels of word processing: letter, prelexical, and lexical. While letter selective responses are found in much of the VOTC, with a higher proportion in left posterior regions, prelexical/lexical responses are confined to the middle and anterior sections of the left fusiform gyrus. This region overlaps with and extends more anteriorly than the visual word form area typically identified with functional magnetic resonance imaging. In this region, prelexical responses provide evidence for populations of neurons sensitive to the statistical regularity of letter combinations independently of lexical responses to familiar words. Despite extensive sampling in anterior ventral temporal regions, there is no hierarchical organization between prelexical and lexical responses in the left fusiform gyrus. Overall, distinct word processing levels depend on neural populations that are spatially intermingled rather than organized according to a strict posteroanterior hierarchy in the left VOTC.
Data from: Using geometric morphometric visualizations of directional selection gradients to investigate morphological differentiation
Researchers studying extant and extinct taxa are often interested in identifying the evolutionary processes that have lead to the morphological differences among the taxa. Ideally, one could distinguish the influences of neutral evolutionary processes (genetic drift, mutation) from natural selection, and in situations for which selection is implicated, identify the targets of selection. The directional selection gradient is an effective tool for investigating evolutionary process, because it can relate form (size and shape) differences between taxa to the variation and covariation found within taxa. However, although most modern morphometric analyses use the tools of geometric morphometrics (GM) to analyze landmark data, to date, selection gradients have mainly been calculated from linear measurements. To address this methodological gap, here we present a GM approach for visualizing and comparing between-taxon selection gradients with each other, associated difference vectors, and "selection" gradients from neutral simulations. To exemplify our approach, we use a dataset of 347 three-dimensional landmarks and semilandmarks recorded on the crania of 260 primate specimens (112 humans, 67 common chimpanzees, 36 bonobos, 45 gorillas). Results on this example dataset show how incorporating geometric information can provide important insights into the evolution of the human braincase, and serve to demonstrate the utility of our approach for understanding morphological evolution.
Data from: Eye and head movements are complementary in visual selection
In the natural environment, visual selection is accomplished by a system of nested effectors, moving the head and body within space and the eyes within the visual field. However, it is not yet known if the principles of selection for these different effectors are the same or different. We used a novel gaze-contingent display in which an asymmetric window of visibility (a horizontal or vertical slot) was yoked to either head or eye position. Participants showed highly systematic changes in behaviour, revealing clear differences in the principles underlying selection by eye and head. Eye movements were more likely to move in the direction of visible information—horizontally when viewing with a horizontal slot, and vertically with a vertical slot. Head movements showed the opposite and complementary pattern, moving to reveal new information (e.g. vertically with a horizontal slot and vice versa). These results are consistent with a nested system in which the head favours exploration of unknown regions, while the eye exploits what can be seen with finer-scale saccades.
Data from: Concurrent visual and motor selection during visual working memory guided action
Visual working memory enables us to hold onto past sensations in anticipation that these may become relevant for guiding future actions. Yet laboratory tasks have treated visual working memories in isolation from their prospective actions and have focused on the mechanisms of memory retention rather than utilization. To understand how visual memories become used for action, we linked individual memory items to particular actions and independently tracked the neural dynamics of visual and motor selection when memories became used for action. This revealed concurrent visual-motor selection, engaging appropriate visual and motor brain areas at the same time. Thus we show that items in visual working memory can invoke multiple, item-specific, action plans that can be accessed together with the visual representations that guide them, affording fast and precise memory-guided behavior.
Integrating Visual Aids to Enhance the Code Reviewer Selection Process Replication Package
<p>Modern Code Review (MCR) is an integral part of a software development strategy that accelerates product quality by identifying defects, code smells, and other harmful practices. However, assigning appropriate reviewers to evaluate changed code during the review process remains challenging. While automated tools for reviewer assignments have limited impact in practice, the process often relies on manual investigation of project histories to retrieve knowledge of team members and their activities. Therefore, in this study, we present an approach to automatically assemble developers' information and visualize it meaningfully, which helps to choose appropriate reviewers. First, we propose three metrics that measure developers' collaboration, reviewers' expertise, and reviewers' workload and visualize them through networks. Second, we perform a case study of three popular open-source projects, where we compute and visualize each developers' information according to the proposed metrics. Finally, we conducted two online surveys to assess the developers' perceptions of the proposed visual benefits. The results show that the proposed method can assist in identifying relevant reviewers and be immensely helpful to new developers. Additionally, survey respondents expressed reliance on the efficacy of the visual aids in workload balancing and reducing review time. </p>
Data from: Eye and head movements are complementary in visual selection
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Data from: Selective visual representation of letters and words in the left ventral occipito-temporal cortex with intracerebral recordings
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Data from: Using geometric morphometric visualizations of directional selection gradients to investigate morphological differentiation
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Data from: Real-time social selection maintains honesty of a dynamic visual signal in cooperative fish
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Data from: Concurrent visual and motor selection during visual working memory guided action
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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.