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4,753 results for “SHAPE”
Fig. 1. Figure 1. Representative Spinicaudata and their typical head shapes. A in Pseudosesarma crassimanum
Fig. 1. Figure 1. Representative Spinicaudata and their typical head shapes. A) Ozestheria altus Shu et al., 2015, male head left lateral view; B) Cyzicus californicus (Packard, 1874), female head left lateral view; C) Ozestheria pilosa (Rogers et al., 2013), male head left lateral view; D) Leptestheria kunmingensis Shu et al., 2015, male head left lateral view; E) L. kunmingensis Shu, et al., 2015, female head left lateral view; F) Eocyzicus taiwanensis Rogers et al., 2017, male head left lateral view; G) Ozestheria sp. "Mongolia", DCR collection 729, male head left lateral view; H) Ozestheria sp. "Mongolia", DCR collection 729, male limb I endopod distal portion, right lateral view; I) Metalimnadia sp. DCR collection 853, male head left lateral view; J) Eoleptestheria cf. ticinensis from Australia, male head left lateral view. Designations: f = fornix; on = occipital notch; oc = occipital condyle; rs = rostral spine; r = rostrum.
Fig. 2 in Does size matter for horny beetles? A geometric morphometric analysis of interspecific and intersexual size and shape variation in Colophon haughtoni Barnard, 1929, and C. kawaii Mizukami, 1997 (Coleoptera: Lucanidae)
Fig. 2 Landmarks used for geometric morphometric analysis of Colophon specimens: a male C. haughtoni mandible; b male C. kawaii mandible; c male C. haughtoni head; d female head; e pronotum; f elytron. Scale bars represent 2 mm
Fig. 1 Adult Colophon beetles. a Colophon haughtoni. b in Does size matter for horny beetles? A geometric morphometric analysis of interspecific and intersexual size and shape variation in Colophon haughtoni Barnard, 1929, and C. kawaii Mizukami, 1997 (Coleoptera: Lucanidae)
Fig. 1 Adult Colophon beetles. a Colophon haughtoni. b Ventral photograph of C. haughtoni head showing (1) gena, (2) mandible base, (3) ventral process, (4) dorsal process and (5) apex of the mandible. c Ventral view of C. kawaii head. Scale bars represent 4 mm (a) and 2 mm (b, c). Photographs by H.J. de Klerk
Figure2. Generation of negative feedbacks gets tuned once a TCR completes stimulation beyond the threshold l. A TCell generates activation signal to BCell once it gets stimulation of its k-TCRs.-AIDEN: A Density Conscious Artificial Immune System for Automatic Discovery of Arbitrary Shape Clusters in Spatial Patterns
<p>A TCR at position p is stimulated if rp (x) - rn(x) > l. Figure 1 depicts this process. When a T<br> Cell receives stimulations on more than k receptors, it generates activation signal to a B Cell, as<br> represented in Figure2.</p>
Figure1. Static stimulation of a single TCR- The kinetic proofreading by the receptor on input x Є X forwards the receptor position p toward l. The receptor will generate negative feedback if p > β. The receptor will generate success signal when p== l.-AIDEN: A Density Conscious Artificial Immune System for Automatic Discovery of Arbitrary Shape Clusters in Spatial Patterns
<p>A TCR at position p is stimulated if rp (x) - rn(x) > l. Figure 1 depicts this process. When a T<br> Cell receives stimulations on more than k receptors, it generates activation signal to a B Cell, as<br> represented in Figure2.</p>
FIGURES 2 a-g -AIDEN: A Density Conscious Artificial Immune System for Automatic Discovery of Arbitrary Shape Clusters in Spatial Patterns
<p>The program was implemented in Matlab and tested with several patterns. The first, dataset1<br> consisted of 2 patterns each comprised of 100 points falling on two concentric circles of radii 10<br> and 20 respectively. The second, dataset2 consisted of 3 patterns each of 100 points falling on three<br> concentric circles of radii 10, 15, and 20 respectively. The model was further tested for its<br> capability to find clusters in patterns of open spatial form using dataset3 and dataset4 consisting of<br> 200 and 300 points falling on 2 and 3 concentric semi circles respectively. As shown in the<br> Figure2.a and Figure2.b, the algorithm is capable of determining spatial association of a data point<br> with other data points belonging to its appropriate circle only. The results successfully demonstrated<br> the capability of our model to automatically detect clean clusters of arbitrary shapes in the input<br> data represented in closed spatial form. The model was found even capable of determining clusters<br> of open spatial forms also, as shown in Figure2.c and Figure2.e. However, the output of the<br> algorithm was found affected by the values of the algorithm parameters k and a. In the present<br> experiment, k =8 and a =10 was sufficient for performing correct cluster associations. On the other<br> hand, correct clustering for the dataset2, could be obtained with 10NN estimation i.e. k =10, with<br> a.=15. Moreover setting k =15, with a.=15 was required for dataset4, as clustering error was<br> observed with k =10, with a.=15, as in Figure2.d. Figure2.f and Figure2.g show the correct<br> clustering even in presence of combination of open and closed form of input patterns. In each<br> figure, the first sub-plot shows the original data and the second sub-plot shows the clusters<br> identified by our program.</p>
Figure3. APCs A1-A4 connected within range of cohesion-factor-threshold form members of one ARB-AIDEN: A Density Conscious Artificial Immune System for Automatic Discovery of Arbitrary Shape Clusters in Spatial Patterns
<p>Figure3 depicts this process. The<br> model with the above specification then effectively detects self or non-self pathogens. In terms of<br> its application to the task of clustering, this interpretation means making the affinities high within<br> clusters and low across clusters. A pathogen corresponding to an outlier would not stimulate a TCR<br> sufficiently and may not form part of any ARB.</p>
Research data for: On the persistent shape and coherence of pulsating auroral patches
<p>Data for the research article: On the persistent shape and coherence of pulsating auroral patches in Journal of Geophysical Research: Space physics. For example all-sky imager movies of 557.7 nm pulsating/fluctuating aurora on 1 March 2012. </p>
Identifying shape transformations from photographs of real objects
<p>Dataset relative to the following publication:</p> <p>Schmidt, F., & Fleming, R. W. (2018). Identifying shape transformations from photographs of real objects. <em>PLoS ONE, 13(8):e0202115</em>, 1-20. <strong><a href="https://doi.org/10.1371/journal.pone.0202115">https://doi.org/10.1371/journal.pone.0202115</a></strong></p> <p>Each experiment folder contains the data relative to one experiment and a text file with comments. The stimuli folder contains downsampled image files of the experimental stimuli.</p>
Posteromedial reversed L-shaped approach for posterior column tibial plateau fractures
<blockquote>Posterior column tibial plateau fractures are best treated via a posterior approach. Various approaches have been described for reaching the posterior aspect of the tibia plateau: posterolateral, direct posterior, and posteromedial. The posteromedial reversed L-shaped approach however, has been proven to be very elegant and straightforward, and offers an excellent exposure of the whole posterior wall. The WAVE proximal posterior tibia plate fits in this approach with its identical reversed L-shaped configuration. The combined approach and implant are referred to as the reversed L-shaped concept. Here we demonstrate the posteromedial reversed L-shaped approach for a two-column tibial plateau fracture using the WAVE proximal posterior tibia plate in a step-by-step-fashion.</blockquote>
Visual Perception of Shape-Transforming Processes: 'Shape Scission'
<p>Dataset relative to the following publication:</p> <p>Schmidt, F., Phillips, F., & Fleming, R. W. (in press). Visual Perception of Shape-Transforming Processes: ‘Shape Scission’. <em>Cognition, 189</em>, 167-180. https://doi.org/10.1016/j.cognition.2019.04.006</p> <p>Each experiment folder contains the data relative to one experiment and a text file with comments. The stimuli folder contains image files of the experimental stimuli.</p>
Data from: The more you get, the more you give: Positive cascading effects shape the evolutionary potential of prenatal maternal investment
<p>Data from 'The more you get, the more you give: Positive cascading effects shape the evolutionary potential of prenatal maternal investment'</p> <p> </p> <p>Description of variables in CME_dat.csv</p> <p>egg.mass - mean offspring egg mass (grams)</p> <p>maternal.line - selection line of mother (H- high investment, L - low investment)</p> <p>paternal.line - selection lines of father (H- high investment, L - low investment)</p> <p>replicate - selection line replicate</p> <p>animal - animal id (links with data from Pick et al. 2016 on dryad)</p> <p>mother - mother id</p> <p>father - father id</p> <p>maternal.egg.mass - mean maternal egg mass (grams)</p>
Synthetic Data for Neutrophil Analysis: Sets with irregular shapes and Poisson noise
<p><strong>Synthetic Datasets with irregular shapes and Poisson noise.</strong></p> <p><strong>Part of the PhagoSight neutrophil tracking and analysis package (Henry, et al., PLOS ONE, 2013):</strong></p> <p> </p> <p>https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0072636</p> <p>http://www.phagosight.org</p> <p>https://github.com/phagosight/phagosight</p> <p> </p> <p>A series of synthetic data sets that reproduce different behaviour characteristics of migrating neutrophils were generated in MATLAB. The data sets consisted of six artificial neutrophils that travelled along paths that presented different conditions of tortuosity, times to activation and proximity to other neutrophils during 98 time frames.</p> <p>Numerous data sets of neutrophils in zebrafish were carefully observed before setting the characteristics. Six trajectories were manually determined by setting the row, column positions of the centroids at every time point for 98 time frames. Each trajectory was designed so that it would represent different neutrophil behaviours: some trajectories were very oriented and had movements with uniform distance between time frames, whilst others were less uniform and would move at different velocities, some were tortuous whilst others were straight. The trajectories of cells 1 and 2 collided several times in the second half of the time frames whilst cells 3 and 4 collided at the beginning of the movement. Cell 6 migrated without meandering and then stopped at the end (which represents the wound area of an inflammation-based experiment) whilst 5 presented a delayed activation. </p> <p>Each time frame consisted of 11 slices of z-stack each with 275 x 275 pixels, where the neutrophils were formed by <strong>irregular shapes </strong>(sum of Gaussians) and <strong>Poisson Noise</strong> (check the corresponding sets with regular shapes, i.e. Gaussians with Gaussian noise plus another set with a <strong>single large neutrophil</strong> and Poisson noise) distributions of higher intensities than the background. The orientation of the Poisson varied according to the displacement of the artificial neutrophils, <em>i.e.</em>they were round when the cells were static, or elongated when in movement. The tracks with the Shapes were saved as the <em>gold standard</em> and five different data sets were generated by adding varying levels of white Poisson noise resulting in data sets with distributions with increasing similarity between the neutrophils and the background reflected by the decreasing values of the Bhattacharyya Distance (1.61, 1.25, 1, 0.66, 0.45) as defined by Coleman 1979.</p> <p> </p> <p>Files corresponding to the sets with irregular shapes and Poisson noise (noise increases from 1 to 5):</p> <ul> <li><strong> x,y,t trajectories ThreeDTracks</strong></li> <li><strong> Ground Truth syntheticData_P_mat_La </strong></li> <li><strong> First data set syntheticData_P1_mat_Re</strong></li> <li><strong> Second data set syntheticData_P2_mat_Re</strong></li> <li><strong> Third data set syntheticData_P3_mat_Re</strong></li> <li><strong> Fourth data set syntheticData_P4_mat_Re</strong></li> <li><strong> Fifth data set syntheticData_P5_mat_Re</strong></li> </ul> <p>Corresponding GIF files are also included as illustrations of the cells in motion.</p> <p> </p> <p>Main Reference:</p> <p><a href="https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0072636"><strong><em>PhagoSight</em>: An Open-Source MATLAB® Package for the Analysis of Fluorescent Neutrophil and Macrophage Migration in a Zebrafish Model</strong> </a><br> Henry KM, Pase L, Ramos-Lopez CF, Lieschke GJ, Renshaw SA, Reyes-Aldasoro CC. (2013) <em>PhagoSight</em>: An Open-Source MATLAB® Package for the Analysis of Fluorescent Neutrophil and Macrophage Migration in a Zebrafish Model. PLOS ONE 8(8): e72636. <a href="https://doi.org/10.1371/journal.pone.0072636">https://doi.org/10.1371/journal.pone.0072636</a></p>
Synthetic Data for Neutrophil Analysis: Sets with regular shapes and Gaussian noise
<p><strong>Synthetic Datasets with regular shapes and Gaussian noise.</strong></p> <p><strong>Part of the PhagoSight neutrophil tracking and analysis package (Henry, et al., PLOS ONE, 2013):</strong></p> <p> </p> <p>https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0072636</p> <p>http://www.phagosight.org</p> <p>https://github.com/phagosight/phagosight</p> <p> </p> <p>A series of synthetic data sets that reproduce different behaviour characteristics of migrating neutrophils were generated in MATLAB. The data sets consisted of six artificial neutrophils that travelled along paths that presented different conditions of tortuosity, times to activation and proximity to other neutrophils during 98 time frames.</p> <p>Numerous data sets of neutrophils in zebrafish were carefully observed before setting the characteristics. Six trajectories were manually determined by setting the row, column positions of the centroids at every time point for 98 time frames. Each trajectory was designed so that it would represent different neutrophil behaviours: some trajectories were very oriented and had movements with uniform distance between time frames, whilst others were less uniform and would move at different velocities, some were tortuous whilst others were straight. The trajectories of cells 1 and 2 collided several times in the second half of the time frames whilst cells 3 and 4 collided at the beginning of the movement. Cell 6 migrated without meandering and then stopped at the end (which represents the wound area of an inflammation-based experiment) whilst 5 presented a delayed activation. </p> <p>Each time frame consisted of 11 slices of z-stack each with 275 x 275 pixels, where the neutrophils were formed by Gaussian distributions of higher intensities than the background and <strong>Gaussian noise </strong>(check the corresponding irregular shapes with Poisson noise plus another set with a <strong>single large neutrophil</strong> and Poisson noise). The orientation of the Gaussians varied according to the displacement of the artificial neutrophils, <em>i.e.</em>they were round when the cells were static, or elongated when in movement. The tracks with the Gaussians were saved as the <em>gold standard</em> and five different data sets were generated by adding varying levels of white Gaussian noise resulting in data sets with distributions with increasing similarity between the neutrophils and the background reflected by the decreasing values of the Bhattacharyya Distance (1.61, 1.25, 1, 0.66, 0.45) as defined by Coleman 1979.</p> <p> </p> <p>Files corresponding to the sets with irregular shapes and Poisson noise (noise increases from 1 to 6):</p> <ul> <li><strong> x,y,t trajectories ThreeDTracks</strong></li> <li><strong> Ground Truth syntheticData0_mat_Re </strong></li> <li><strong> First data set syntheticData1_mat_Re</strong></li> <li><strong> Second data set syntheticData2_mat_Re</strong></li> <li><strong> Third data set syntheticData3_mat_Re</strong></li> <li><strong> Fourth data set syntheticData4_mat_Re</strong></li> <li><strong> Fifth data set syntheticData5_mat_Re</strong></li> <li><strong> Sixth data set syntheticData6_mat_Re</strong></li> </ul> <p> </p> <p>Corresponding GIF files are also included as illustrations of the cells in motion.</p> <p> </p> <p>Main Reference:</p> <p><a href="https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0072636"><strong><em>PhagoSight</em>: An Open-Source MATLAB® Package for the Analysis of Fluorescent Neutrophil and Macrophage Migration in a Zebrafish Model</strong> </a><br> Henry KM, Pase L, Ramos-Lopez CF, Lieschke GJ, Renshaw SA, Reyes-Aldasoro CC. (2013) <em>PhagoSight</em>: An Open-Source MATLAB® Package for the Analysis of Fluorescent Neutrophil and Macrophage Migration in a Zebrafish Model. PLOS ONE 8(8): e72636. <a href="https://doi.org/10.1371/journal.pone.0072636">https://doi.org/10.1371/journal.pone.0072636</a></p>
Magnetically Addressable Shape-Memory and Stiffening in a Composite Elastomer
<p>Open access data set for manuscript "Magnetically Addressable Shape-Memory and Stiffening in a Composite Elastomer" published in Advanced Materials (2019), 1900561</p> <p> </p> <p><a href="https://doi.org/10.1002/adma.201900561">https://doi.org/10.1002/adma.201900561</a></p>
Dataset: Decay of Torsional Stiffness of RC U-shaped Walls When Subjected Simultaneously to In-Plane Loading
<p>Reinforced concrete U-shaped walls are a popular construction choice, commonly used to resist the lateral loads from wind and earthquakes. When subjected to earthquake ground motions, it is likely that these structural elements will not only bend in flexure but twist due to asymmetries of the building plan layout and the location of the shear center outside of the section. This research investigates the dependency of the torsional stiffness of U-shaped walls on the in-plane translational displacement demands using novel experimental evidence and advanced numerical models. The experimental results show that for a given flexural position, the torsional stiffness decreases with increasing in-plane translational displacement. Furthermore, the numerical and experimental results indicate that when the wall is centered the torsional stiffness degrades at the same rate at the translational stiffness of the walls. Thus, the torsional stiffness of a U-shaped wall as a function of ductility can be estimated using the translational secant stiffness. The numerical results also show that the torsional stiffness increases as a function of the axial load ratio of the wall. The experimental and numerical dataset from this research investigation can be downloaded from a publicly accessible repository.</p>
How Confidence in Prior Attitudes, Social Tag Popularity, and Source Credibility Shape Confirmation Bias Toward Antidepressants and Psychotherapy in a Representative German Sample: Randomized Controlled Web-Based Study
<p>ABSTRACT</p> <p>Background: In health-related, Web-based information search, people should select information in line with expert (vs nonexpert) information, independent of their prior attitudes and consequent confirmation bias.</p> <p>Objective: This study aimed to investigate confirmation bias in mental health–related information search, particularly (1) if high confidence worsens confirmation bias, (2) if social tags eliminate the influence of prior attitudes, and (3) if people successfully distinguish high and low source credibility.</p> <p>Methods: In total, 520 participants of a representative sample of the German Web-based population were recruited via a panel company. Among them, 48.1% (250/520) participants completed the fully automated study. Participants provided <em>prior attitudes</em> about antidepressants and psychotherapy. We manipulated (1) <em>confidence</em> in prior attitudes when participants searched for blog posts about the treatment of depression, (2) <em>tag popularity</em> —either psychotherapy or antidepressant tags were more popular, and (3) <em>source credibility</em> with banners indicating high or low expertise of the tagging community. We measured <em>tag</em> and <em>blog post</em> selection, and <em>treatment</em><em>efficacy ratings</em> after navigation.</p> <p>Results: Tag popularity predicted the proportion of selected antidepressant tags (beta=.44, SE 0.11; <em>P</em><.001) and blog posts (beta=.46, SE 0.11; <em>P</em><.001). When confidence was low (−1 SD), participants selected more blog posts consistent with prior attitudes (beta=−.26, SE 0.05; <em>P</em><.001). Moreover, when confidence was low (−1 SD) and source credibility was high (+1 SD), the efficacy ratings of attitude-consistent treatments increased (beta=.34, SE 0.13; <em>P</em>=.01).</p> <p>Conclusions: We found correlational support for defense motivation account underlying confirmation bias in the mental health–related search context. That is, participants tended to select information that supported their prior attitudes, which is not in line with the current scientific evidence. Implications for presenting persuasive Web-based information are also discussed.</p> <p>Trial Registration: ClinicalTrials.gov NCT03899168; https://clinicaltrials.gov/ct2/show/NCT03899168 (Archived by WebCite at http://www.webcitation.org/77Nyot3Do)</p> <p>J Med Internet Res 2019;21(4):e11081</p> <p>doi:10.2196/11081</p>
Text-fig. 8.—The shape of the frontals. A, the Jordan theropod, LACM 28471, B, Albertosaurus libratus, AMNH 5664, C, A. libratus, USNM 12814. All are drawn to the same length. Vertical lines to the right indicate relative lengths of the three frontals respectively. (B, courtesy of Dale A. Russell, C, redrawn from Russell, 1970). in A new Theropod Dinosaur from the Upper Cretaceous of Central Montana
Text-fig. 8.—The shape of the frontals. A, the Jordan theropod, LACM 28471, B, Albertosaurus libratus, AMNH 5664, C, A. libratus, USNM 12814. All are drawn to the same length. Vertical lines to the right indicate relative lengths of the three frontals respectively. (B, courtesy of Dale A. Russell, C, redrawn from Russell, 1970).
Interspecific social interactions shape public goods production in natural microbial communities
<p>The R code (Hesse_etal.R) descibes step by step how metal polution affects the ecology and evolution of a community-wide public good – the production of metal-detoxifying siderophores. This code accompanies the manuscript "Interspecific interactions shape public goods production in natural microbial communities" (https://www.biorxiv.org/content/10.1101/710715v1).</p> <p>The R code is divided into different sections per figure (1-5 and supplementary Figure S1). Each section first starts with reading in the appropriate data files (cvs files) and continues with statistics and plotting of figures.</p>
Hydrodynamic shape changes underpin nuclear rerouting in branched hyphae of an oomycete pathogen
<p><strong>Note:</strong> These are mp4 files. While being a widespread file format, mp4 may require additional codecs on some platforms. We recommend users to install a free media player with mp4 support such as <a href="https://www.videolan.org/vlc/index.fr.html">VLC</a>.</p> <p> </p> <p><strong>Video</strong><strong> 1. </strong>Time-lapse confocal microscopy of germinating <em>P. palmivora </em>cysts from a transgenic strain expressing a cytoplasmic tdTomato and a nuclear-localized mTFP1 (LILI-td-NT) during exploratory growth at the surface of <em>N. benthamiana</em> roots. Z-stacks were collected every 5 min. Still images corresponding to this video are displayed in <strong>Figure 1</strong>. Scale bar is 10 µm.</p> <p><strong>Video 2.</strong> Time-lapse confocal microscopy of <em>P. palmivora </em>LILI-td-NT infection structures during <em>N. benthamiana</em> root infection. The video is composed of two movies representing successful (<strong>Video 2</strong><strong>A</strong><strong>)</strong> and unsuccessful <strong>(Video 2</strong><strong>B</strong><strong>)</strong> infection events. Z-stacks were collected every 5 min. Still images corresponding to this video are displayed in <strong>Figure 2</strong>. Scale bar is 20 µm.</p> <p><strong>Video 3.</strong> Time-lapse confocal microscopy of <em>P. palmivora </em>LILI-td-NT hyphae differentiating haustoria during <em>N. benthamiana</em> leaf infection. Plastids autofluorescence is shown in magenta. Frames were collected every 6.6 s. Still images corresponding to this video are shown in <strong>Figure 3</strong>. Scale bar is 20 µm.</p> <p><strong>Video 4.</strong> Time-lapse confocal microscopy of <em>P. palmivora </em>LILI-td-NT hyphae during haustoria differentiation in <em>N</em><em>. benthamiana</em> leaf tissues. Plastids autofluorescence is shown in magenta. Frames were collected every 4 s. Still images corresponding to this video are shown in <strong>Figure 3</strong>. Scale bar is 10 µm.</p> <p><strong>Video 5.</strong> Time-lapse confocal microscopy of a <em>P. palmivora </em>LILI-td-NT hyphal tip on V8 agar plate. Frames were collected every 4.5 s. Still images corresponding to this video are displayed in <strong>Figure 3</strong>. Scale bar is 20 µm.</p> <p><strong>Video 6.</strong> Time-lapse confocal microscopy of a <em>P. palmivora </em>LILI-td-NT hyphal tip on V8 agar plate. Frames were collected every 4.8 s. Still images corresponding to this video are displayed in <strong>Figure 3</strong>. Scale bar is 20 µm.</p> <p><strong>Video </strong><strong>7</strong><strong>.</strong> Time-lapse confocal microscopy of a <em>P. palmivora </em>LILI-td-NT hyphal branch point on V8 agar plate. Frames were collected every 15 s. Still images corresponding to this video are displayed in <strong>Figure </strong><strong>5</strong>. Scale bar is 20 µm.</p> <p><strong>Video </strong><strong>8</strong><strong>.</strong> Time-lapse confocal microscopy of <em>P. palmivora </em>LILI-td-NT mycelium on V8 agar plate without (DMSO control) <strong>(Video 8</strong><strong>A</strong><strong>)</strong> or with 10 mg/L Benomyl <strong>(Video 8</strong><strong>B</strong><strong>)</strong>. Frames were collected every 12.8 s and 13 s, respectively. Still images corresponding to this video are displayed in <strong>Figure </strong><strong>6</strong>. Scale bar is 20 µm.</p> <p><strong>Video </strong><strong>9</strong><strong>.</strong> Time-lapse confocal microscopy of <em>P. palmivora </em>mycelium from a transgenic strain expressing a mCitrine-Centrin2 reporter and a nuclear-localized mTFP1 (LILI-NT-Ce) on V8 agar plate. Frames were collected every 5 s. This video is linked to <strong>Figure 7</strong>. Scale bar is 20 µm.</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.