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3,688 results for “Computer”
All simulation results, figures and code regarding the manuscript: Calibrating models of cancer invasion: parameter estimation using Approximate Bayesian Computation and gradient matching
<p>We present two different methods to estimate parameters within a partial differential equation (PDE) model of cancer invasion. The model describes the spatio-temporal evolution of three variables -- tumour cell density, extracellular matrix density and matrix degrading enzyme concentration -- in a one-dimensional tissue domain. The first method is a likelihood-free approach associated with Approximate Bayesian Computation (ABC); the second is a two-stage gradient matching method based on smoothing the data with a Generalized Additive Model (GAM) and matching gradients from the GAM to those from the model. Both methods performed well on simulated data. To increase realism, additionally we tested the gradient matching scheme with simulated measurement error and found that the ability to estimate some model parameters deteriorated rapidly as measurement error increased.</p>
Real-time benchmark dynamics of the Ohmic Spin-Boson Model computed with Time-Dependent Variational Matrix Product States. (TDVMPS) coupling strength and temperature parameter space
<p>Data describing the complete propagators (maps) for the evolution of the Ohmic Spin-Boson Model are made available, here. Using a time-dependent variotnal matrix product states (TDVMPS) respresentation of the complete spin-environment wave function, non -perturbative results are presented over a wide range of coupling strengths, temperatures and initial conditions. The results in this repository are associated with the article: </p> <p>https://www.preprints.org/manuscript/202012.0016/v1 </p> <p>A mathematica notebook that allows the data to be visualised and manipulated is also provided. </p>
Computational exploration of treadmilling and protrusion growth observed in fire ant rafts
<p><span>Condensed active matter systems regularly achieve cooperative emergent functions that individual constituents could not accomplish alone. The rafts of fire ants (<em>Solenopsis invicta</em>) are often studied in this context for their ability to create structures comprised entirely of their own bodies, including tether-like protrusions that facilitate exploration of flooded environments. While similar protrusions are observed in cytoskeletons and cellular aggregates, they are generally dependent on morphogens or external gradients leaving the isolated role of local interactions poorly understood. Here we demonstrate through an ant-inspired, agent-based numerical model how protrusions in ant rafts may emerge spontaneously due to local interactions and how phases of exploratory protrusion growth may be induced by increased ant activity. These results provide an example in which functional morphogenesis of condensed active matter may emerge purely from locally-driven collective motion and may provide a source of inspiration for the development of autonomous active matter and swarm robotics.</span></p>
Computation is woven
<p>Evidence that computation is woven, and weaving is computation. The first computers were looms, and if we look closely enough, we can find the remaining legacy of this history. Here we visualise the contents of a Z80 processor register memory after each instruction as it runs a handful of example programs. To this day, the majority of low level machine code instructions on the computers we use are not explicitly concerned with numerical values, but rather in the manipulation of patterns (shifting, rotating, masking and composing). That these instructions are given priority in the allocation of transistors seems an appropriate but quiet recognition of the importance of weaving in contemporary digital technology.</p>
Data from: Bayesian quantification of ecological determinants of outcrossing in natural plant populations: computer simulations and the case study of biparental inbreeding in English yew
The mating system is a central parameter of plant biology because it shapes their ecological and evolutionary properties. Therefore, determining ecological variables that influence the mating system is important for a deeper understanding of the functioning of plant populations. Here, using old concepts and recent statistical developments, we propose a new statistical tool to make inferences about ecological determinants of outcrossing in natural plant populations. The method requires co-dominant genotypes of seeds collected from maternal plants within different locations. Using extensive computer simulations, we demonstrated that the method is robust to the issues expected for real-world data, including the Wahlund effect, inbreeding and genotyping errors such as allele dropout and allele misclassification. Furthermore, we showed that the estimates of ecological effects and outcrossing rates can be severely biased if genotyping errors and genetic differentiation are not treated explicitly. Application of the new method to the case study of a dioecious tree (Taxus baccata) allowed revealing that female trees that grow in lower local densities have a greater tendency towards mating with relatives. Moreover, we also demonstrated that biparental inbreeding is higher in populations that are characterised by a longer mean distance between trees and a smaller mean trunk perimeter. We found these results to agree with both the theoretical predictions and the history of English yew.
Data from: Quartet-based computations of internode certainty provide robust measures of phylogenetic incongruence
Incongruence, or topological conflict, is prevalent in genome-scale data sets. Internode Certainty (IC) and related measures were recently introduced to explicitly quantify the level of incongruence of a given internal branch among a set of phylogenetic trees and complement regular branch support measures (e.g., bootstrap, posterior probability) that instead assess the statistical confidence of inference. Since most phylogenomic studies contain data partitions (e.g., genes) with missing taxa and IC scores stem from the frequencies of bipartitions (or splits) on a set of trees, IC score calculation typically requires adjusting the frequencies of bipartitions from these partial gene trees. However, when the proportion of missing taxa is high, the scores yielded by current approaches that adjust bipartition frequencies in partial gene trees differ substantially from each other and tend to be overestimates. To overcome these issues, we developed three new IC measures based on the frequencies of quartets, which naturally apply to both complete and partial trees. Comparison of our new quartet-based measures to previous bipartition-based measures on simulated data shows that: 1) on complete data sets, both quartet-based and bipartition-based measures yield very similar IC scores; 2) IC scores of quartet-based measures on a given data set with and without missing taxa are more similar than the scores of bipartition-based measures; and 3) quartet-based measures are more robust to the absence of phylogenetic signal and errors in phylogenetic inference than bipartition-based measures. Additionally, the analysis of an empirical mammalian phylogenomic data set using our quartet-based measures reveals the presence of substantial levels of incongruence for numerous internal branches. An efficient open-source implementation of these quartet-based measures is freely available in the program QuartetScores (https://github.com/lutteropp/QuartetScores).
Project Colossus - Apollo Guidance Computer
A model of the Apollo Guidance Computer (block II) main body, the DSKEY input unit and a sample logic board module for the computer. The name, 'Colossus' refers to the in-house name for the program the computer runs on. This project's aim was to focus on my presentation, and I decided to set it out like a museum exhibit. All the info for the annotations sourced from: https://en.wikipedia.org/wiki/Apollo_Guidance_Computer https://en.wikipedia.org/wiki/Core_rope_memory This isn't meant to be an exhaustively studied or accurate rendition, so take it with a grain of salt. Source: Objaverse 1.0 / Sketchfab
Computer use and mathematics achievement in TIMSS
<p>This dataset contains country-level data on computer use and mathematics achievement of 8th grade students from TIMSS 2003, 2007 and 2011.</p>
Knowledge Freedom in computational science: a two stage peer-review process with KF Eligibility Access Review
<p>What is explained below is the <em>peer review process</em> applied by <em>Notes on Transdisciplinar</em><em>y Modelling for Environment </em>(NTMe). Authors and readers are encouraged to understand not only the process, but also the rationale behind the process, which is closely connected with the peculiar challenges faced by the scientific problems (computational-science modelling under uncertainty, in broad and heterogeneous contexts) in the scope of the journal. </p> <p> </p> <p><span class="math-tex">\(\mathsf{\Large\text{The rationale behind the peer-review process}}\)</span></p> <p><strong>Computational research problems for more than one discipline. </strong>Research specific to a particular disciplinary domain is typically authored, and then studied, by experts in that domain. Several conventions, assumptions, fundamental protocols and methodology practices, are shared by domain experts as a common ground. Given that proficiency in these aspects is a precondition for domain experts, this kind of knowledge is often implicit, and not well communicated within domain-specific literature. "Typical" data preprocessing, model settings, quality-assessment assumptions (and their "default" simplifications and shortcuts), in this literature are often minimally reported or omitted, because the domain-specific community of researchers and practitioners knows them so well that they may resemble a sort of acquired conditioned response. However, when in a wider research more than one disciplinary domain is connected among each other, then implicit unexpressed knowledge may lead to ambiguity, misuse of results, and avoidable errors - sometimes challengly difficult to detect. The more and more diverse the domains, the higher this risk might be.</p> <p><strong>Useful cross-domain building blocks. </strong>"Transdisciplinary" research may risk being misinterpreted as just the final summary list of results grabbed by autonomous disciplinary silos run in parallel. However, a poor ability to communicate computational methods and data - and their limitations - between multiple disciplinary domains would jeopardise the collective (cross-domain) ability to distill truly integrated computational science. Computational science for transdisciplinary problems requires a pragmatic, engineered, but reasonably simple and modular approach to break and connect disciplinary silos - when appropriate for the problems investigated. Publishing <em>useful</em> cross-domain building blocks of this approach is the aim of the peer-review process in NTMe.</p> <p><strong>Connecting disciplines, space and time scales under uncertainty: the need for a shared semantics. </strong>Wide-scale transdisciplinary modelling (WSTM) relies on methods proper to computational science for connecting multiple scientific disciplines, and shedding light on broad, complex problems. Several of the most pressing problems we face as a human society are only partially known in their chain of consequences, and hopelessly difficult to address by a single discipline and a narrow perspective. Some of these problems capture the specific interest by particularly exposed regions, but their mechanism is more general, with essential knowledge often lying in other spatial areas - or even other time periods - hence calling for a wider perspective. Multiple spatial and temporal scales, with dissimilar data resolution, are frequent in WSTM problems, since they are often dictated by the complexity of reality and the available data. A wide-scale extent typically implies uneven quality and availability of data, and many sources of uncertainty - which increases when assumptions, methods and semantics by different disciplines or research institutions do not easily merge. A truly transdisciplinary communication of this essential semantics requires the <em>freedom </em>to communicate scientific knowledge, accurately and transparently, between disciplinary and corporate barriers.</p> <p><strong>Real knowledge sharing in computational science. </strong>As a consequence, wide-scale transdisciplinary modelling demands a focus on reproducible research and real scientific knowledge freedom. Data and software freedom are essential aspects of knowledge freedom in computational science. Therefore, ideally published articles should also provide the readers with the data and source code of the described mathematical modelling. To maximise transparency, replicability, reproducibility and reusability, published data should be made available as open data while source code should be made available as free software. Communicating semantics even to non-experts in a given domain requires that mathematical assumptions, otherwise obvious within a specific discipline, are duly annotated in a portable and concise way. Accordingly, brief but semantically clear documentation of data, methods and software is a key precondition. Here, a two-stage peer review process is described in which scientific knowledge freedom is considered with a dedicated Eligibility Access Review. This new peer review process is applied by <em>Notes on Transdisciplinary Modelling for Environment</em> with a focus on WSTM for environment.</p> <p> </p> <p><span class="math-tex">\(\mathsf{\Large\text{The peer-review process}}\)</span></p> <p><strong>A two-stage peer review process to avoid single-use disposable computational science. </strong>The two-stage peer review process requires discussion papers to be published so as to receive feedback from the scientific community before their possible finalisation. Initial manuscript submission is subject to the soundness review outlined above, also ensuring eligibility criteria to be fulfilled so as to support scientific knowledge freedom. Although this concept is multifaceted, some few dimensions might be emphasised which broadly apply in computational science and engineering (CSE). Among the many possible eligibility criteria in CSE, it should be highlighted at least the need for: </p> <ul> <li>free software to have been published so as for it to be persistently available;</li> <li>appropriate licensing and source code review to have been done (portable modularisation, with semantics of mathematical data-transformation methods clearly annotated);</li> <li>free data to have been published so as for it to be persistently available (with semantics of quantities clearly annotated);</li> <li>a minimal share of free-access core references to be selected in order for scientists and research organisations not to be discriminated on the basis of their funding availability, when they try to access the core literature cited in the manuscript.</li> </ul> <p>Before acceptance for discussion, a manuscript (and its potential data, parameters and software) may be revised, without exposing to the public immature versions, until it becomes able to fulfil the eligibility criteria. These iterations between author(s) and editors/reviewers remain confidential, and a potential manuscript rejection does not preclude resubmission. Acceptance of the manuscript to the discussion stage is followed by the permanent publication of the accepted version. This does not preclude, and actually encourages, further revised versions to be resubmitted. Any new revision is subject to eligibility access review, which takes into account the submission history of the manuscript and the already accepted public older versions.</p> <p><strong>Not a static publication. </strong>The discussion stage of the peer review process allows short comments to be submitted by referees and the scientific community, while authors are encouraged to interact with pending comments by providing their responses. During this stage, the paper accepted for discussion is already citable. Depending on the specific goals of each research problem, the discussion may remain open for a short time interval, or instead for a noticeably longer period of time (even indefinitely, if appropriate: for example, whenever authors do consider publishing cumulative milestone versions as important). There is not an a-priori limit to the duration of this first stage, and to the number of intermediate public revisions (which are optional), for a paper accepted for discussion. The second stage of peer review concludes the discussion stage with the submission of a revised manuscript, with final review and corrections. Fulfilment of the eligibility criteria is required over all the publication stages.<br> The published materials might be updated from time to time (at the authors' discretion), and - after peer-reviewing the changes - published so that the evolution is clear and available to others. Although preferred and encouraged in the discussion stage, updates are possible even after the final stage. Revisions offering a noticeably different content, compared with the previous versions, might sometime be recommended by editors/reviewers as deserving the status of a new publication - not to confuse the readers. This implies the full two-stage review process has to be applied to the new publication (as an independent publication), while the previous accepted publication is considered as the final permanent version. Recalling an analogy with the typical evolution of free-software, a software package is frequently subject to future improvements and corresponding new versions. If a new version is too different from the original package, it may become a new independent package. </p> <p><strong>Scientific opinions, perspectives, and overviews.</strong> Manuscripts focusing on computational science methods, data, parameters, and software are expected to contribute practical components of scientific knowledge which can be adapted, modified, or generally integrated within the future body of knowledge - potentially in unexpected ways. Therefore, the aforementioned two-stage review is, overall, meant to ease the future invention of derivative works. On the other hand, manuscripts offering expert opinions on these topics do not contribute "practical" components to be directly modified. Instead, they contribute organised ideas to support the evolution of scientific knowledge. Therefore, the peer review process for this typology of manuscripts focuses on:</p> <ul> <li>the broad understandability and potential interest of the expert opinions, and</li> <li>the factual correctness of the objective elements included in the opinion (with adequate bibliographic, tabular, visual support where appropriate). </li> </ul> <p><strong>Preregistration, protocols and methods. </strong>NTMe accepts a third typology of manuscripts, focusing on anticipated results (hence not yet computed) which are expected following a modelling procedure to transform input data and parameters into the desired output. As data and software are only anticipated in this typology of manuscripts, the peer-review process focuses on:</p> <ul> <li>the broad understandability and potential interest of the proposed protocol or methodology,</li> <li>the correctness and clarity of the mathematical formulation of the proposed computational-modelling steps (data-transformation modules),</li> <li>the discussion of anticipated results, pitfalls, sources of uncertainty and their proper management, bifurcations of the methodology depending on the potential variants that a user may desire to apply (depending on available data and their quality, and on the desired specialisation of the proposed general method), and</li> <li>the adequacy of bibliographic, tabular, visual supports where appropriate. </li> </ul> <p><strong>Abstract, and plain language summary. </strong>Each article includes a technical abstract. Although the topics of published content might deal with domain-specific aspects of computational/environmental science, their focused analysis is expected to support wider research in a transdisciplinary context. Therefore, the abstract is expected to be accessible beyond the domain-specific research community. Each article, either in the discussion or in the final stage, in addition to a technical abstract needs a <em>plain language summary</em> so that non-experts and readers with a basic scientific and technical literacy can understand the main contributions of the article. The aim of the plain language summary is to support educational dissemination. The summary is not a simpler abstract, and typically offers a longer, more comprehensive description. It is realised with an editorial support to authors, so as to respect a general structure (unless otherwise agreed):</p> <ul> <li>first, the general context of the work is presented (the general topics in which the work is situated);</li> <li>second, the general open questions are introduced to which the work aims to contribute;</li> <li>third, the specific way is described in which the work contributes to progress on the general open questions;</li> <li>fourth, the implications, new opportunities or suggested lines of research, and potential limitations and unaswered questions are summarised.</li> </ul> <p><strong>Constructive peer review.</strong> The ultimate aim of the peer review process is to support authors, and future readers, in sharing useful, durable, and understandable notes of transdisciplinary knowledge. Given the very nature of the topics in NTMe, the need for a cogent peer review on a multiplicity of expertise fields is essential. Rarely a single reviewer is able to cover all the aspects of transdiciplinary computational science. Even so, different opinions by different reviewers may emerge on specific points. Therefore, a <em>constructive </em>approach is promoted during each step of the peer review process, so that authors are guided to understand the peer review, and a compendium of recommandations may be presented in a consistent way.</p> <p> </p> <p><sup>© 2012-2020 Daniele de Rigo. This work is licensed under a </sup><a href="http://creativecommons.org/licenses/by-nd/4.0/legalcode"><sup>Creative Commons Attribution No Derivatives 4.0 International</sup></a><sup> license. Please, cite as<br> de Rigo, D., 2012. </sup><strong><sup>Knowledge Freedom in computational science: a two stage peer-review process with KF eligibility access review</sup></strong><sup>. </sup><em><sup>Zenodo, </sup></em><sup>CERN. </sup><a href="https://doi.org/10.5281/zenodo.7578"><sup>https://doi.org/10.5281/zenodo.7578</sup></a><sup> </sup></p> <p> </p>
The Software Sustainability Institute's Collaborations Workshop 2015 (CW15) attendees computational tools word-cloud
<p>Word cloud representing the computational tools used by those attending the Software Sustainability Institute's Collaborations Workshop 2015 (CW15).</p> <p>For more information see www.software.ac.uk/cw15</p> <p>Please note there is an ERROR in the diagram for some reason wordle.net did not pickup 'R' in the dataset - http://dx.doi.org/10.5281/zenodo.19828 - i.e. the usage of R in research software in the people who attended CW15 is not represented in this diagram.</p>
HPC-GAP: Engineering a 21st-Century High-Performance Computer Algebra System
<p>Data for the experiments conducted in the paper</p>
Determination of ti-6242 α and β slip properties using micro-pillar test and computational crystal plasticity
<p>Data for "Determination of ti-6242 α and β slip properties using micro-pillar test and computational crystal plasticity"<br /> http://dx.doi.org/10.1016/j.jmps.2016.06.007</p> <p><br /> Zhen Zhang, Tea-Sung Jun, T. Benjamin Britton and Fionn P.E. Dunne<br /> Department of Materials, Imperial College London, Prince consort Road, London, SW7 2AZ, UK</p> <p>--</p> <p>This experimental data folder contains 3 subfolders:<br /> (1) Micropillar compression videos<br /> (2) Simulation data</p> <p>(3) Data for Figure 4<br /> (4) Data for Figure 6</p> <p>--</p> <p>The simulation data in (2) is ABAQUS input deck containing an example finite element representation of an alpha-beta titanium micropillar subjected to compression loading. This model was calibrated against the experimental data using the first 60s of the stress relaxation period.</p> <p>--</p> <p>If readers need further information, please feel free to contact: zhen.zhang@imperial.ac.uk</p>
Computational Studies of Human Class V Alcohol Dehydrogenase - The Odd Sibling
<p>A number of class I-VI ADH protein sequences were obtained from the UniProt, NCBI protein database, and Ensembl databases in October 2015. The sequences were aligned using the L-INS-i approach of MAFFT 7.266.</p> <p>The tree was generated using Phyml release 20151210. In the published figure, the tree was visualised as a radial phylogram in Dendroscope 3.</p>
Shadow Detection/Texture Segmentation Computer Vision Dataset
<p>A simple computer vision dataset for shadow detection and texture analysis, specifically created to help test shadow detection algorithms (and texture segmentation algorithms) for mobile robots - that is, shadow detection with an <em>active (moving) camera</em>.</p> <p>The dataset is focused around texture analysis, so each image sequence contains shadows moving in front of a number of various textured surfaces. The dataset contains four main subfolders: "active", "artificial", "kondo", and "static". The "static" folder contains ground-truthed image sequences of textured surfaces with shadows moving over them, and the "active" folder contains ground-truthed image sequences of a camera travelling over textured surfaces. The "artificial" folder contains a computer-generated 3D scene with computer-generated ground truth, but note that texture is absent from all images within. Finally, the "kondo" folder contains a series of extremely challenging images captured from a webcam mounted to a Kondo bipedal robot. This final dataset is challenging because it contains a high level of noise, flicker and interference from electrical lighting, and the poor lighting conditions make for complex shadows with large penumbrae.</p>
Scheduling success ratios and computational cost of the mechanism
<p>The .xls spreadsheet contains scheduling success ratios and computational cost of the mechanism related to the publication "Seeking Time-Composable Partitions of Tasks for COTS Multicore Processors".</p>
Biology and Computational Biology Papers in Pubmed, 1997-2014
<p>Downloaded from Pubmed on 12 February, 2016</p> <p>Bio:<br /> ("Biology"[Mesh]) NOT (Review[ptyp] OR Comment[ptyp] OR Editorial[ptyp] OR Letter[ptyp] OR Case Reports[ptyp] OR News[ptyp] OR "Biography" [Publication Type]) AND ("1997/01/01"[PDAT] : "2014/12/31"[PDAT]) AND english[language]</p> <p>Comp:<br /> ("Computational Biology"[Majr]) NOT (Review[ptyp] OR Comment[ptyp] OR Editorial[ptyp] OR Letter[ptyp] OR Case Reports[ptyp] OR News[ptyp] OR "Biography" [Publication Type]) AND ("1997/01/01"[PDAT] : "2014/12/31"[PDAT]) AND english[language]</p>
Output data computed for the solution of Maxwell's equations on a distributed system using the FDTD method
<p>This is an example output dataset from the distributed computation to solve Maxwell's equations using the FDTD method. This is an example from the report describing the implementation of the computer program - Gillan and Fusco (1998). The example is based on the work reported in the book by Kunz and Leubbers on the FDTD method. It consists of scattering a Gaussian pulse from a sphere of dielectric defined with a 3D cube of size 34x34x34 Yee cells. </p>
EEG Data for: "Learning from Label Proportions in Brain-Computer Interfaces"
<p>Data about two experiments is contained in this repository. An EEG experiment utilizing visual event-related potentials (ERPs) with N=13 healthy subjects was conducted in addition to a smaller study with N=5 subjects performing both an auditory and a visual ERP paradigm. </p> <p>The dataset is used and described in the following journal article:</p> <p><em>Hübner, D., Verhoeven, T., Schmid, K., Müller, K. R., Tangermann, M., & Kindermans, P. J. (2017). Learning from label proportions in brain-computer interfaces: online unsupervised learning with guarantees. PloS one, 12(4), e0175856.</em></p> <p><strong>Please cite the above article when using the data.</strong></p> <p>The larger data set with N=13 is different to ordinary ERP datasets in the sense that the train of stimuli to spell one character (68) is divided into repetitions of two interleaved sequences with length 8 and 18, respectively. We added '#' symbols to the spelling matrix which should never be attended by the subject and hence, are non-targets by definition. The first, shorter sequence, now highlights only ordinary characters, while the second sequence also highlights '#' -- visual blank symbols. By construction, sequence 1 has a higher target ratio than sequence 2. These known, but different target and non-target proportions are then used to reconstruct the target and non-target class means. This approach which does not need explicit class labels is termed Learning from Label Proportions (LLP). It can be used to decode brain signals without prior calibration session. More details can be found in the article.</p> <p>In another study, the above data set was used to simulate a new unsupervised mixture approach which combines the mean estimation of the unsupervised expectation-maximization algorithm by Kindermans et al. (2012, PLoS One) with the means obtained with the LLP approach. This leads to an unsupervised solution for which the performance is as good as in the supervised scenario. Please find more details in the following article:</p> <p><em>Verhoeven, T., Hübner, D., Tangermann, M., Müller, K. R., Dambre, J., & Kindermans, P. J. (2017). Improving zero-training brain-computer interfaces by mixing model estimators. Journal of neural engineering, 14(3), 036021.</em></p> <p>The following files are available:</p> <p>description.pdf: <strong>Full description of the dataset</strong><br> offline_auditory.zip: <strong>Data from the auditory offline study with N=5 subjects</strong><br> offline_visual.zip: <strong>Data from the visual offline study with N=5 subjects</strong><br> online_study_1-7.zip: <strong>Data from the online study for subjects 1-7</strong><br> online_study_8-13.zip: <strong>Data from the online study for subjects 8-13</strong><br> sequence.mat: <strong>Sequence data necessary for applying LLP to the online study. It is the same for all subjects</strong></p> <p>We will create a git repository with example code soon.</p>
Computing Eddy-Driven Effective Diffusivity Using Lagrangian Particles Dataset
<p>This archive contains netCDF files corresponding to datasets used in the<br> Ocean Modelling paper entitled<br> "Computing Eddy-Driven Effective Diffusivity Using Lagrangian Particles" by<br> Phillip J. Wolfram and Todd D. Ringler.</p> <p>Archives are presented for particle reset times of 3, 5, 10, and 15 days,<br> corresponding to data sources used to produce figures in the manuscript. </p> <p>The data is in standard netCDF file format, which is readily readable using<br> standard netCDF tools or via the python libraries netCDF4 and xarray.</p> <p>Please see the README.md (with updates at https://gist.github.com/pwolfram/c9f3d8b6c37385732bd1b105b5267e6a).</p> <p> </p>
Computer Generated-Human Morph Stimuli
<p>This stimulus set contains images of human faces (from the Radboud Faces Database; Langner et al., 2010) morphed with computer-generated versions of the same faces, made with FaceGen Modeller (Singular Inversions, Toronto, Canada). Morph continua are provided at 10% intervals (11 total images per morph) and 2% intervals (50 total images per morph). 16 total morphs are provided in the stimulus set, comprising 4 female faces with neutral expressions (labelled FN), 4 female faces with happy expressions (FH), 4 male faces with neutral expressions (MN) and 4 male faces with happy expressions (MH). All faces are Caucasian, and are photographed as a frontal view, with external features covered by an oval frame.</p> <p>For more information about this stimulus set, please contact n.bowling@gold.ac.uk</p> <p>Radboud Faces Database:</p> <p>Langner, O., Dotsch, R., Bijlstra, G., Wigboldus, D. H. J., Hawk, S. T., & van Knippenberg, A. (2010). Presentation and validation of the Radboud Faces Database. <em>Cognition & Emotion, 24</em>(8), 1377-1388.</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.