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124 results for “behavior prediction”
Open data repository, Knab et al., Prediction of stroke outcome in mice based on non-invasive MRI and behavioral testing
<p><strong>Open data repository, Knab et al., Prediction of stroke outcome in mice based on non-invasive MRI and behavioral testing</strong></p> <p><strong>Latest version of files: repository_v2.0.zip, Behavior Data_v2.0.xlsx and MRI IDs Testing&Replication Cohort.xlsx (please ignore repository.zip)</strong></p> <p>Open data repository Knab et al. Prediction of stroke outcome in mice based on non-invasvive MRI and behavioral testing</p> <p>Open code and documentation of prediction models available via <a href="https://github.com/major-s/mouse-mcao-outcome-predictor">https://github.com/major-s/mouse-mcao-outcome-predictor</a></p> <p><strong>Content:</strong></p> <p>README.txt</p> <p>This information</p> <p><strong>dat</strong></p> <p>Contains MRI data in NIFTI format and secondary data from atlas registration. For documentation of atlas registration files see https://pubmed.ncbi.nlm.nih.gov/28829217/<br>Files used for the manuscript:<br>t2.nii: t2 weighted image acquired 24 h post stroke<br>masklesion.nii: manually delineated lesion<br>x_masklesion.nii: lesion in atlas space<br>ix_ANO.nii: Allen brain atlas in native space (i.e. matching t2.nii)<br>Lesion volume was calculated by volume of voxels unequal 0 in x_masklesion.nii<br>Overlap of regions defined by ix_ANO.nii with masklesion.nii were used for calculating percent damage in each atlas region</p> <p><strong>prediction_models</strong></p> <p>Contains separated training and test data as xlsx and csv files with lesion volumes in cubic mm of the Allen brain atlas space, percent damage per atlas region and behavioral data. The training data was used as input for training prediction models in MATLAB, the results were created using the test data.<br>The files have following sturcture:<br>Column 1: animal ID<br>Columns 2-537: MRI regions (column title corresponds to the region number as used in the Allen common coordinate framework)<br>Column 538: lesion volume<br>Column 539: initial performance (subacute deficit) = mean performance/deficit on days 2-6<br>Column 540: mean performance/deficit on days 2-6 = initial performance (subacute deficit) - this column equals column 539 but has different header which was used to train the residual from initial deficit<br>Column 541: residual performance/deficit<br>Column 542: test or training group<br>Consecutive rows contain data for each animal specified by the animal id</p> <p>The repository also contains all trained models, prediction results for the test data and tables with resulting median absolute error (MedAE) and 5th, 25th, 75th and 95 absolute error quantiles for each model.<br>The model files end with '_models.mat' and contain 50 independently trained models each. Each model version is specified by number 1-50.<br>The result files end with '_test_results.mat' or '_test_results.xlsx', files with MedAE and quantiles end with '_test_errors.xlsx' or '_test_errors.csv. The common part of filenames specifies the used paradigm<br>Folder 'subacute deficit prediction' contains:<br> - initial_performance_from_lesion_volume: prediction of subacute deficit using lesion volume<br> - initial_performance_from_segmented_mri: prediction of subacute deficit using segmented mri<br>Folder 'long-term outcome prediction' contains:<br> - lesion_volume: prediction of residual deficit using lesion volume<br> - segmented_mri: prediction of residual deficit using segmented_mri<br> - initial_performance: prediction of residual deficit using subacute deficit<br>Folder 'mri_inc_oob_imp' contains models trained using increasing number of mri segments sorted according to the out-of-bag importance. The number of used segments is given in the file name. The models, results and errors are separated in subfolders.</p> <p>Files with equal file name and different extension always contain the same data</p> <p><strong>templates</strong><br>Allen atlas, template, brain mask, hemisphere masks, tissue probability masks in NIFTI format including annotations of region IDs and parameter.m file for use in MATLAB toolbox ANTx2<br> </p>
Behavior-relevant top-down cross-modal predictions in mouse neocortex
<p>Simultaneously recorded S1 and PPC neuronal population activity from awake mice during a texture discrimination task. Data acquired with two-photon calcium imaging.</p>
Realistic Ab Initio Predictions of Excimer Behavior under Collective Light-Matter Strong Coupling - Dataset
<p>Dataset complement to "Realistic Ab Initio Predictions of Excimer Behavior under Collective Light-Matter Strong Coupling" - includes outputs obtained using the <a href="https://etprogram.org/development-website/">eT program</a>, an open-source electronic (and molecular-polaritonic) structure program, and VIBROT (OpenMolcas).</p> <p> </p> <p>See the paper at <a href="https://journals.aps.org/prx/abstract/10.1103/PhysRevX.15.021040">https://journals.aps.org/prx/abstract/10.1103/PhysRevX.15.021040</a></p>
Data and code of "Post-trauma behavioral phenotype predicts the degree of vulnerability to fear relapse after extinction in male rats"
<p>This dataset contains behavioral and transcriptomic data, and the original code related to the following article:</p> <p>Post-trauma behavioral phenotype predicts the degree of vulnerability to fear relapse after extinction in male rats. Fanny Demars, Ralitsa Todorova, Gabriel Makdah, Antonin Forestier, Marie-Odile Krebs, Bill P Godsil, Thérèse M Jay, Sidney I Wiener, & Marco N Pompili (2022) Current Biology <em>32. https://doi.org/10.1016/j.cub.2022.05.050</em></p>
The theory of planned behavior and the prediction of pre-service biology teachers' intention to teach evolution
<p>We developed the project to identify and analyze variables that promote or hinder prospective biology teachers’ intentions to teach evolution. We adopted the model of the theory of planned behavior (TPB). We extended it to include additional variables described by teacher education research as key determinants of behavioral intention to teach evolution. We initially hypothesized that attitudes toward teaching evolution, subjective norms, perceived behavioral control, personal religious beliefs, perceived usefulness, and knowledge about evolution would determine a person’s behavioral intentions. To test the hypotheses, we developed an online questionnaire and conducted a quantitative cross-sectional survey in the field of teacher education. The data included information on <em>N</em> = 309 participants. Because we initially analyzed the data using a two-stage structural equation model (SEM), we uploaded two data files that were created in subprocesses of our original analyses (for more information, see the original publication). The dataset “data3” contains 77 variables and has missing values. Since we wanted to use complete data for the SEM, we trimmed the data set “data3” to include only the 67 variables necessary for the SEM, then applied an expectation-maximum (EM) algorithm with multiple imputations, and obtained the data set “data4”. </p>
Data for: Predicting age and mass at maturity from feeding behavior and diet in M. sexta: An empirical test of a life history model
<p>Feeding for most animals involves bouts of active ingestion alternating with bouts of no ingestion. In insects, the temporal patterning of bouts varies widely with resource quality and is known to affect growth, development time, and fitness. However, the precise impacts of resource quality and feeding behavior on insect life history traits is poorly understood. To explore and better understand the connections between feeding behavior, resource quality and insect life history traits, we combined laboratory experiments with a recently proposed mechanistic model of insect growth and development for a larval herbivore, <em>Manduca sexta</em>. We ran feeding trials for 4<sup>th</sup> and 5<sup>th</sup> instar larvae across different diet types (two hostplants and artificial diet) and used these data to parameterize a joint model of age and mass at maturity that incorporates both insect feeding behavior and hormonal activity. We found that the estimated durations of both feeding and non-feeding bouts were significantly shorter on low- than on high-quality diets. We then explored how well the fitted model predicted historical out-of-sample data on age and mass of <em>M</em>.<em> sexta</em>. We found that the model accurately described qualitative outcomes for the out-of-sample data, notably that a low-quality diet results in reduced mass and later age at maturity compared to high-quality diets. Our results clearly demonstrate the importance of diet quality on multiple components of insect feeding behavior (feeding and non-feeding), and partially validate a joint model of insect life history. We discuss the implications of these findings with respect to insect herbivory and discuss ways in which our model could be improved or extended to other systems.</p>
Cortex-wide neural dynamics predict behavioral states and provide a neural basis for resting-state dynamic functional connectivity
<p><strong>GENERAL INFORMATION</strong></p> <p>This data is described in the following publication: </p> <p><strong>Cortex-wide neural dynamics predict behavioral states and provide a neural basis for resting-state dynamic functional connectivity</strong>, Somayeh Shahsavarani<sup>1,2,5</sup>, David N. Thibodeaux<sup>1,5</sup>, Weihao Xu<sup>1</sup>, Sharon H. Kim<sup>1</sup>, Fatema Lodgher<sup>1</sup>, Chinwendu Nwokeabia<sup>1</sup>, Morgan Cambareri<sup>1</sup>, Alexis J. Yagielski<sup>1</sup>, Hanzhi T. Zhao<sup>1</sup>, Daniel A. Handwerker<sup>2</sup>, Javier Gonzalez-Castillo<sup>2</sup>, Peter A. Bandettini<sup>2,3</sup>, Elizabeth M. C. Hillman<sup>1,4,6,*</sup> Cell Reports (2023): <a href="https://doi.org/10.1016/j.celrep.2023.112527">https://doi.org/10.1016/j.celrep.2023.112527</a></p> <p><br> 1. Mortimer B. Zuckerman Mind Brain Behavior Institute and Department of Biomedical Engineering, Columbia University, New York, NY, USA<br> 2. Section on Functional Imaging Methods, Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA<br> 3. Functional MRI Core Facility, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA<br> 4. Department of Radiology, Columbia University Irving Medical Center, New York, NY, USA<br> 5. These authors contributed equally<br> 6. Lead contact<br> *Correspondence: elizabeth.hillman@columbia.edu</p> <p>Preprocessing and analysis code that generated / can be used with this data is posted at: <br> GitHub: <a href="https://doi.org/10.5281/zenodo.7860561">https://doi.org/10.5281/zenodo.7860561</a></p> <p><strong>DATA OVERVIEW </strong></p> <p>This dataset comprises simultaneous neuronal and hemodynamic data collected using wide-field optical mapping (WFOM) techniques. The data were obtained from head-fixed mice that were allowed to behave spontaneously without any external stimulation. For more detail, please refer to the Readme file.</p>
Data from: Prospection of potential actions during visual working memory starts early, is flexible, and predicts behavior.
<p>Raw data (EEG and behavior) reported in the manuscript "Prospection of potential actions in visual working memory starts early, is flexible, and predicts behavior" by Rose Nasrawi, Sage E.P. Boettcher, and Freek van Ede</p>
Data and code from: A timid choice: Risk-taking behavior predicts individualized niche in a varying landscape of safety
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Evaluating the usefulness of Protection Motivation Theory for predicting climate change mitigation behavioral intentions among a US sample of climate change deniers and acknowledgers
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Genetic testing predicts appearance but not behavior in dogs
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Hippocampal firing fields anchored to a moving object predict homing direction during path-integration-based behavior
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Data for: Predicting age and mass at maturity from feeding behavior and diet in M. sexta: An empirical test of a life history model
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With or without you: Gut microbiota does not predict aggregation behavior in European earwig females
<p>The reasons why some individuals are solitary and others gregarious are the subject of ongoing debate as we seek to understand the emergence of sociality. Recent studies suggest that the expression of aggregation behaviors may be linked to the gut microbiota of the host. Here, we tested this hypothesis in females of the European earwig. This insect is ideal for addressing this question, as adults both naturally vary in the degree to which they live in groups and show inter-individual variation in their gut microbial communities. We video-tracked 320 field-sampled females to quantify their natural variation in aggregation and then tested whether the most and least gregarious females had different gut microbiota. We also compared the general activity, boldness, body size, and body condition of these females and examined the association between each of these traits and the gut microbiota. Contrary to our predictions, we found no difference in the gut microbiota between the most and least gregarious females. There was also no difference in activity, boldness, and body condition between these two types of females. Independent of aggregation, gut microbiota was overall associated with female body condition, but not with any of our other measurements. Overall, these results demonstrate that a host's gut microbiota is not necessarily a major driver or a consequence of aggregation behavior in species with inter-individual variation in group living and call for future studies to investigate the determinants and role of gut microbiota in earwigs.</p>
Beyond sex and aggression: Testosterone rapidly matches behavioral responses to social context and tries to predict the future
<p>Although androgens are widely studied in the context of aggression, androgenic influences on prosocial behaviors have been less explored. We examined testosterone's (T) influence on prosocial and aggressive responses in a positively-valenced social context (interacting with a pairbond partner) and a negatively-valenced context (interacting with an intruder) in socially monogamous Mongolian gerbils. T increased and decreased prosocial responses in the same individuals towards a pairbond partner and an intruder, respectively, both within 30 minutes, but did not affect aggression. T also had persistent effects on prosocial behavior; males in which T initially increased prosocial responses towards a partner continued to exhibit elevated prosocial responses towards an intruder male days later until a second T injection rapidly eliminated those responses. Thus, T surges can rapidly match behavior to current social context, as well as prime animals for positive social interactions in the future. Neuroanatomically, T rapidly increased hypothalamic oxytocin, but not vasopressin, cellular responses during interactions with a partner. Together, our results indicate that T can facilitate and inhibit prosocial behaviors depending on social context, that it can influence prosocial responses across rapid and prolonged time scales, and that it affects oxytocin signaling mechanisms that could mediate its context-dependent behavioral influences.</p>
Data for: Telomere length predicts timing and intensity of migratory behavior in a nomadic songbird
<p>Our understanding of state-dependent behavior is reliant on identifying physiological indicators of condition. Telomeres are of growing interest for understanding behavior as they capture differences in biological state and residual lifespan. To understand the significance of variable telomere lengths for behavior and test two hypotheses describing the relationship between telomeres and behavior (i.e., the causation and the selective adoption hypotheses), we assessed if telomere lengths are longitudinally repeatable traits related to spring migratory behavior in captive pine siskins (<em>Spinus pinus</em>). Pine siskins are nomadic songbirds that exhibit highly flexible, facultative migrations, including a period of spring nomadism. Captive individuals exhibit extensive variation in spring migratory restlessness and are an excellent system for mechanistic studies of migratory behavior. Telomere lengths were found to be significantly repeatable (R = 0.51) over 4 months, and shorter pre-migratory telomeres were associated with earlier and more intense expression of spring nocturnal migratory restlessness. Telomere dynamics did not vary with migratory behavior. Our results describe the relationship between telomere length and migratory behavior and provide support for the selective adoption hypothesis. More broadly, we provide a novel perspective on the significance of variable telomere lengths for animal behavior and the timing of annual cycle events.</p>
Habitat structural complexity predicts cognitive performance and behavior in western mosquitofish
<p>Urbanization and stream order alter freshwater habitat complexity (defined as the degree of variation in physical habitat structure). More complex habitats have more variation in habitat structure. Habitat complexity affects species composition and shapes animal ecology, behavior, and cognition. We used a delayed detour test to measure whether motor self-regulation and behavior of Western mosquitofish, <em>Gambusia affinis, </em>varied with habitat structural complexity that was quantified for nine populations. We predicted that motor self-regulation, motivation, and risk-taking behavior would increase with increasing habitat complexity, yet we found the opposite relationship. Lower complexity habitats offer less refuge which could increase predation pressure and select for greater risk-taking by fish with greater motor self-regulation. Our findings provide insight into how habitat complexity is related to cognitive processes and behavioral outcomes, and provide an explanation for why some species have a higher tolerance for urbanized environments.</p>
Data for: Ecology and behavior predict an evolutionary trade-off between song complexity and elaborate plumages in antwrens (Aves, Thamnophilidae)
<p>The environment can impose constraints on signal transmission properties such that signals should evolve in predictable directions (Sensory Drive Hypothesis). However, behavioral and ecological factors can limit investment in more than one sensory modality leading to a trade-off in use of different signals (Transfer Hypothesis). In birds, there is mixed evidence for both sensory drive and transfer hypothesis. Few studies have tested sensory drive while also evaluating the transfer hypothesis, limiting understanding of the relative roles of these processes in signal evolution. Here, we assessed both hypotheses using acoustic and visual signals in male and female antwrens (Thamnophilidae), a species-rich group that inhabits diverse environments and exhibits behaviors, such as mixed-species flocking, that could limit investment in different signal modalities. We uncovered significant effects of habitat (sensory drive) and mixed-species flocking behavior on both sensory modalities, and we revealed evolutionary trade-offs between song and plumage complexity, consistent with the transfer hypothesis. We also showed sex- and trait-specific responses in visual signals that suggest both natural and social selection play an important role in the evolution of sexual dimorphism. Altogether, these results support the idea that environmental (sensory drive) and behavioral pressures (social selection) shape signal evolution in antwrens.</p>
The predator activity landscape predicts the anti‐predator behavior and distribution of prey in a tundra community
<p>Predation shapes communities through consumptive and non-consumptive effects. In the latter case, prey respond to perceived predation risk through proactive or reactive risk management strategies occurring at different spatial and temporal scales. The predator-prey space race and landscape of fear concepts are useful to better understand how predation risk affects prey behavioral decisions and distribution. We assessed predation-risk effects in a terrestrial Arctic community, where the arctic fox is the main predator of ground-nesting birds. Using high frequency GPS data, we estimated a predator activity landscape corresponding to fox space use patterns, and validated with an artificial prey experiment that this predator activity landscape correlated with the predation risk landscape. We then investigated the effects of the fox activity landscape on multiple prey species, by assessing the anti-predator behavior of a main prey (snow goose) actively searched for by foxes, and the nest distribution of several incidental prey species. We first found that snow geese showed a stronger level of nest defense in areas highly used by foxes, possibly responding with a reactive strategy to variation in predation risk. Then, nests of incidental prey reproducing in habitats easily accessed by foxes had a lower probability of occurrence in areas highly used by foxes, suggesting these birds may use a proactive risk management strategy by shifting their distribution away from risky areas. For incidental prey species nesting in microhabitat refuges difficult to access by foxes, probability of nest occurrence was independent of predation risk in the surrounding area, as they avoid risk at a finer spatial scale. By tracking all individuals of the dominant predator species in our study area, we demonstrated the value of using predator space use patterns to infer spatial variation in predation risk. Overall, we highlight the diversity of risk management strategies in prey sharing a common predator, hence refining our understanding of the mechanisms driving species distribution and community structure.</p>
Action Prediction Error: a value-free dopaminergic teaching signal that drives stable learning - Behavioral dataset
<p>Behavioral data to reproduce figures of this paper: https://doi.org/10.1101/2022.09.12.507572</p> <p>See Github repository: https://github.com/HernandoMV/APE_paper</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.