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5,805 results for “Data model”
Data from: How biological attention mechanisms improve task performance in a large-scale visual system model
How does attentional modulation of neural activity enhance performance? Here we use a deep convolutional neural network as a large-scale model of the visual system to address this question. We model the feature similarity gain model of attention, in which attentional modulation is applied according to neural stimulus tuning. Using a variety of visual tasks, we show that neural modulations of the kind and magnitude observed experimentally lead to performance changes of the kind and magnitude observed experimentally. We find that, at earlier layers, attention applied according to tuning does not successfully propagate through the network, and has a weaker impact on performance than attention applied according to values computed for optimally modulating higher areas. This raises the question of whether biological attention might be applied at least in part to optimize function rather than strictly according to tuning. We suggest a simple experiment to distinguish these alternatives.
Air parcel trajectories data generated by MIMICA code and simulation results generated by a trajectory box model
<p>The dataset includes trajectories of air parcels extracted from the large-eddy (cloud-resolving model) simulations of the deep convective clouds from the Amazon based on the soundings retrieved on April 8, 2020, April 23, 2020, and April 27, 2020, over Manaus, Brazil, as well as the results of the chemical box model simulations quantifying the transport of some atmospheric trace gases abundant in the Amazon.</p>
Data input for Modelling investment and dispatch decisions for flexibility options
<p>This dataset contains data on:</p> <ul> <li>Time series of scenario-dependent residual load per country</li> <li>Technology-specific data</li> <li>NTC data</li> <li>DSM process data</li> <li>Data for dispatchable RES</li> </ul>
Experimental data of manuscript "Marine Target Extraction Based on Adjoint Covariance Correction Model"
<p>Experimental data of manuscript "Marine Target Extraction Based on Adjoint Covariance Correction Model"</p>
Code and Data: WRF v.3.9 sensitivity to land surface model and horizontal resolution changes over North America
<p>Data and code used to obtain results published in Garcia-Garcia et al 2021: WRF v.3.9 sensitivity to land surface model and horizontal resolution changes over North America. Submited to<em> Geosci. Model Dev</em>.</p>
CT data and 3D models associated with: Palaeoneurology of the Early Cretaceous iguanodont Proa valdearinnoensis and its bearing on the parallel developments of cognitive abilities in theropod and ornithopod dinosaurs
<p><i>Proa valdearinnoensis </i>is a relatively large-headed and stocky iguanodontian dinosaur from the latest Early Cretaceous of Spain. Its braincase is known from three specimens. Similar to that of other dinosaurs, it shows a mosaic ossification pattern in which most of the bones seem to have fused together indistinguishably while a few bones (frontoparietal, basioccipital) might have remained loosely attached. The endocasts of the three specimens are described based on CT data and digital reconstructions. They show unmistakable morphological similarities with the endocast of closely related taxa, such as <i>Sirindhorna khoratensis </i>(which is close in age but from Thailand). This supports a high conservatism of the endocranial cavity. The issue of volumetric correspondence between endocranial cavity and brain in dinosaurs is analysed. Although a brain-to-endocranial cavity (BEC) index of 0.50 has been traditionally used, we employ instead 0.73. This is indeed the mid-value between the situation in adults of <i>Alligator mississippiensis</i> and <i>Gallus gallus</i>, which are members of the extant bracketing taxa of dinosaurs (Crocodilia and Aves). We thence gauge the level of encephalisation of <i>Proa valdearinnoensis</i> by the calculation of the Encephalisation Quotient (EQ), which remains valuable as a metric for assessing the degree of cognitive function in extinct taxa, especially those with fully ossified braincases like dinosaurs and other archosaurs. The EQ obtained for <i>Proa valdearinnoensis</i> (3.611) suggests that this species was significantly more encephalised than most if not all extant non-avian, non-mammalian amniotes. Our work adds to the growing body of data concerning theoretical cognitive capabilities in dinosaurs and supports the idea that increasing encephalisations were fostered not only once in theropods but also in parallel in the shorter-lived lineage of ornithopods. <i>Proa valdearinnoensis</i> was ill-equipped to respond to theropod dinosaurs and possibly lived in groups as a strategy to mitigate the risk of being predated upon. We hypothesize that group-living and protracted caring of juveniles in this and possibly many other iguanodontian ornithopods favoured a degree of encephalisation that was outstanding by reptile standards.</p>
Presence, precipitation, and temperature data used to estimate eastern forest songbird historical distributions using climatic niche modeling
<p>Boundaries between vegetation types, known as ecotones, can be dynamic in response to climatic changes. The North American Great Plains includes a forest-grassland ecotone in the south-central United States that has expanded and contracted in recent decades in response to historical periods of drought and pluvial conditions. This dynamic region also marks a western distributional limit for many passerine birds that typically breed in forests of the eastern United States. To better understand the influence that variability can exert on broad-scale biodiversity, we explored historical longitudinal shifts in the western extent of breeding ranges of eastern forest songbirds in response to the variable climate of the southern Great Plains. We used climatic niche modeling to estimate current distributional limits of nine species of forest-breeding passerines from 30-year average climate conditions from 1980 to 2010. During this time the southern Great Plains experienced an unprecedented wet period without periodic multi-year droughts that characterized the region's long-term climate from the early 1900s. Species' climatic niche models were then projected onto two historical drought periods: 1952–1958 and 1966–1972. Threshold models for each of the three time periods revealed dramatic breeding range contraction and expansion along the forest-grassland ecotone. Precipitation was the most important climate variable defining breeding ranges of these nine eastern forest songbirds. Range limits extended farther west into southern Great Plains during the more recent pluvial conditions of 1980–2010 and contracted during historical drought periods. An independent dataset from BBS was used to validate 1966–1972 range limit projections. Periods of lower precipitation in the forest-grassland ecotone are likely responsible for limiting the western extent of eastern forest songbird breeding distributions. Projected increases in temperature and drought conditions in the southern Great Plains associated with climate change may reverse range expansions observed in the past 30 years.</p>
Optimal Spectral Sampling Forward Model Test Data
<p>Binary and ASCII files for tests of the OSS forward model application.</p>
Data for "Learning from mistakes - Assessing the performance and uncertainty in process-based models"
<p><strong>Data for the publication "Learning from mistakes - Assessing the performance and uncertainty in process-based models"</strong></p> <p>The corresponding python code can be found at <a href="http://github.com/MoritzFeigl/Learning-from-mistakes">github.com/MoritzFeigl/Learning-from-mistakes</a>.</p> <p>This dataset contains data of hydrological and meteorological observations of the Fortress Ski Area (Alberta, Canada) for August 8-26, 2019. It consists of input and output files for the HFLUX models calibration period (C) and the validation periods (V, V3). The input files containes additional data used in the learning from mistakes workflow. The meteorological data and part of the hydrological data were provided by John Pomeroy and the University of Saskatchewan’s Cold Water Laboratory.</p>
GFDL-ESM2G Model data and scripts in support of "The deep ocean's role in climate and CO2 sensitivity"
<p>GFDL-ESM2G Model data and analysis scripts in support of the manuscript "The deep ocean's role in climate and CO2 sensitivity" by John Dunne and Lori Sentman submitted to Geophysical Research Letters including results from experiments with progressively shoaled maximum ocean depths of 4000 m to 1000 m in 500 m increments.</p>
Predicting readers' prototypical eye-movement behavior using MASC, a model of Attention in the Superior Colliculus: Stimulus materials, model code, data, and statistical analyses.
<p>The goal of the present research was to determine the role of rudimentary visuo-motor pathways, from the retina and the primary visual cortex to the superior colliculus (SC), in the guidance of human eye movement during reading. To this end, we used MASC, our model of Attention in the Superior Colliculus (Adeli et al., Journal of Neuroscience 2017), a model that relies on well-established saccade-programming principles in the SC. MASC predicts sequences of fixations over an input image by spatially integrating incoming signals in the space of the SC.</p> <p>Here, MASC computed the distribution of luminance contrast over sentences' images (visual-saliency map), after blurring it proportional to retinal eccentricity (retina transformation). It then projected the visual-saliency map into SC space, using a logarithmic afferent-mapping function (magnification factor). Input signals were averaged over retinotopically organized populations of neurons (point images) of constant size, first in the visual map and then in a spatially-registered motor map. The most active population was identified through a winner-take-all process. After jitter applied to the winning population, the next fixation location was determined using inverse efferent mapping. This sequence of events was then repeated to predict following fixation locations, but inserting after each saccade an inhibitory spatial tag (Inhibition of Saccade Return; ISR -referred to as IOR in the uploaded files). All MASC's parameters, but one, were biologically determined, using electrophysiological data in macaque; the ISR window was the one fit parameter.</p> <p>MASC was tested by comparing its predicted sequences of fixations over sentences from the French-Sentence Corpus (FSC) to the eye-movement behavior of 40 French-native speakers reading the same sentences for comprehension (Albrengues et al., Plos One 2019). Then, MASC was dissected to determine the crucial processing steps enabling prediction of human behavior (10 comparison models -see the general README file). Finally, to address crucial issues in the reading literature, i.e., the role of inter-word spacing and character print size in eye-movement guidance, MASC was additionally tested in four additional display conditions: the same sentences from the FSC, but with blank spaces between words being either filled or removed, or with the screen width angle being multiplied by 2 or 4, such that characters were larger in angular size (0.5° and 1°) than in the original experiment (0.25°). MASC's predicted effects of inter-word spacing and print size were compared to previously published data.</p> <p>All material relevant to the project is reported here, including the FSC materials (bitmap and information text files), the Matlab code for our MASC model, raw simulation data for MASC and all our comparison models, as well as MASC's simulations in the different display conditions, the scripts we developed in R to transform raw simulation data into data matrices for statistical analyses of (word-based) eye-movement behavior, the resulting data matrices for all models as well as the data matrix for FSC readers, the R-scripts for statistical comparison of oculomotor behavior between data sets and conditions, literature-review tables of previously published data (for comparison with MASC's predictions), and the R-scripts generating the figures summarizing our results.</p> <p>Further information can be found in the general README file as well as in the README files attached to each folder. The authors' respective contributions to the project, the licence attached to the included materials and their condition of use are listed in the general README file.</p> <p>A manuscript reporting and discussing these modeling data is in preparation (Vitu, F., Adeli, H. & Zelinsky, G. J.); A reference will be provided here when the manuscript appears in a journal.</p> <p>Other references to be cited:</p> <p>- For the model code: Adeli, H., Vitu, F., & Zelinsky, G. J. (2017). A model of the superior colliculus predicts fixation locations during scene viewing and visual search. Journal of Neuroscience, 37(6), 1453-1467. http://www.jneurosci.org/content/37/6/1453</p> <p>- For FSC materials and data: Albrengues, C., Lavigne, F., Aguilar, C., Castet, E., & Vitu, F. (2019). Linguistic processes do not beat visuo-motor constraints, but they modulate where the eyes move regardless of word boundaries: Evidence against top-down word-based eye-movement control during reading. PLoS ONE 14(7): e0219666. https://doi.org/10.1371/journal.pone.0219666<br> </p>
Data and analysis for "A process-conditioned and spatially consistent method for reducing systematic biases in modeled streamflow"
<p>This contains all of the necessary data and code to reproduce the results of the manuscript submitted to the Journal of</p> <p>Hydrometeorology entitled "A process-conditioned and spatially consistent method for reducing systematic biases in modeled streamflow"</p>
Data for the manuscript entitled "AMOC variability and watermass transformations in the AWI climate model" by Sidorenko et al. 2021, submitted to JAMES
<p>Data is stored in a SHELVE persistent storage as produced in Python 3.7.4. The visualisation example is provided in a Jupyter Python Notebook.</p>
Dimensional reduction of phenotypes from 53,000 mouse models reveals a diverse landscape of gene function - data bundle
<p>This bundle is an archive of data files, configuration files, and scripts related to the manuscript "Dimensional reduction of phenotypes from 53,000 mouse models reveals a diverse landscape of gene function".</p> <p> </p>
Data from: Model selection analysis of temporal variation in benefit for an ant-tended treehopper
<p>Recent studies of mutualism have emphasized both that the net benefit to participants depends on the ecological context and that the density‐dependent pattern of benefit is key to understanding the population dynamics of mutualism. Indeed, changes in the ecological context are likely to drive changes in both the magnitude of benefit and the density‐dependent pattern of benefit. Despite the close linkage between these two areas of research, however, few studies have addressed the factors underlying variation in the density‐dependent pattern of benefit. Here I use model selection to evaluate how variation in the benefits of a mutualism drives temporal variation in the density‐dependent pattern of net benefit for the ant‐tended treehopper Publilia concava. In the interaction between ants and treehoppers in the genus <i>Publilia</i>, ants collect the sugary excretions of treehoppers as a food resource, and treehoppers benefit both directly (e.g., by feeding facilitation) and indirectly (e.g., by predator protection). Results presented here show that temporal changes in the relative magnitude of direct and indirect benefit components of ant tending, especially the effectiveness of predator protection by ants, qualitatively change the overall pattern of density‐dependent benefit between years with maximum benefit shifting from treehoppers in small to large aggregations. These results emphasize the need for empirical studies that evaluate the long‐term dynamics of mutualism and theoretical studies that consider the population dynamics consequences of variation in the density‐dependent pattern of benefit.</p>
Rosetta Loop Modeling Data for "A Systematic Approach for Evaluating the Role of Surface-Exposed Loops in Trypsin-like Serine Proteases: Analysis of the 170 loop in Coagulation Factor VIIa"
<p>Rosetta Loop Modeling data for the publication "A Systematic Approach for Evaluating the Role of Surface-Exposed Loops in Trypsin-like Serine Proteases: Analysis of the 170 loop in Coagulation Factor VIIa." See the included readme.txt for more details. Please cite the paper if you use these data.</p>
Data and model code for study: Mechanistic modelling of marsh seedling establishment provides a positive outlook for coastal wetland restoration under global climate change
<p>This folder will include data and model code for study: Mechanistic modelling of marsh seedling establishment provides a positive outlook for coastal wetland restoration under global climate change.</p>
Data set for "The effects of glycine to alanine mutations on the struc-ture of GPO collagen model proteins"
<p>Data set for "The effects of glycine to alanine mutations on the struc-ture of GPO collagen model proteins"</p> <p>The README files contain a description of all files and scripts in this repo.</p>
T-REX: computational model data
<p>Datasets generated by the computational neural mass network model of the brain during the study of " A multiscale brain network model links Alzheimer's disease-mediated neuronal hyperactivity to large-scale oscillatory slowing".</p> <p>Data includes raw files of simulated neurophysiology timeseries, generated by iterating the Brainnet coupled neural mass model in Brainwave, available from <a href="http://home.kpn.nl/stam7883/brainwave.html">http://home.kpn.nl/stam7883/brainwave.html</a>. </p> <p>Each file contains data of a single scenario and can be viewed using Brainwave.</p>
Implementing Riverine Biogeochemical Inputs in ECCO-Darwin: A Sensitivity Analysis of Terrestrial Fluxes in a Data-Assimilative Global Ocean Biogeochemistry Model
<p>Resolving riverine biogeochemical inputs in ocean biogeochemistry models is pivotal for capturing the spatiotemporal variability of nutrients and carbon in coastal regions and in the global ocean. ECCO-Darwin is a pioneering data-assimilative global-ocean biogeochemistry model, which, to date, has focused on the pelagic zone. In this work, we use an optimized version of ECCO-Darwin to perform a sensitivity analysis to quantify the response of the open ocean and coastal margins to lateral inputs of carbon and nutrients. We generate riverine inputs by combining point-source freshwater discharge from JRA55-do with the Global NEWS 2 watershed model, accounting for lateral inputs from 5171 watersheds worldwide. While adding carbon and nutrients along with freshwater improves biogeochemical skill in river plume regions and coastal waters, the open-ocean response may be overestimated due to an excess of carbon and nutrients advected offshore. This highlights the need for a more nuanced representation of land-to-ocean and nearshore processes for quantifying how global ocean primary production and carbon cycling respond to land-to-ocean inputs.</p>
ScienceDex guides
Understand access before you commit
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.