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139 results for “dynamic signals”
Learning Dynamics of Electrophysiological Brain Signals During Human Fear Conditioning (Open Data and Open Materials)
<p><strong>Open Data and Open Materials of: Sperl, M. F. J., Wroblewski, A., Mueller, M., Straube, B., & Mueller, E. M. (2021). Learning Dynamics of Electrophysiological Brain Signals During Human Fear Conditioning. <em>NeuroImage</em>, <em>226</em>, 117569.</strong></p> <p>Electrophysiological studies in rodents allow recording neural activity during threats with high temporal and spatial precision. Although fMRI has helped translate insights about the anatomy of underlying brain circuits to humans, the temporal dynamics of neural fear processes remain opaque and require EEG. To date, studies on electrophysiological brain signals in humans have helped to elucidate underlying perceptual and attentional processes, but have widely ignored how fear memory traces <em>evolve</em> over time. The low signal-to-noise ratio of EEG demands aggregations across high numbers of trials, which will wash out transient neurobiological processes that are induced by learning and prone to habituation. Here, our goal was to unravel the plasticity and temporal emergence of EEG responses during fear conditioning. To this end, we developed a new sequential-set fear conditioning paradigm that comprises three successive acquisition and extinction phases, each with a novel CS+/CS- set. Each set consists of two different neutral faces on different background colors which serve as CS+ and CS-, respectively. Thereby, this design provides sufficient trials for EEG analyses while tripling the relative amount of trials that tap into more transient neurobiological processes. Consistent with prior studies on ERP components, data-driven topographic EEG analyses revealed that ERP amplitudes were potentiated during time periods from 33–60 ms, 108–200 ms, and 468–820 ms indicating that fear conditioning prioritizes early sensory processing in the brain, but also facilitates neural responding during later attentional and evaluative stages. Importantly, averaging across the three CS+/CS- sets allowed us to probe the temporal evolution of neural processes: Responses during each of the three time windows gradually increased from early to late fear conditioning, while long-latency (460–730 ms) electrocortical responses diminished throughout fear extinction. Our novel paradigm demonstrates how short-, mid-, and long-latency EEG responses change during fear conditioning and extinction, findings that enlighten the learning curve of neurophysiological responses to threat in humans.</p>
Paroxysmal Atrial Fibrillation Events Detection from Dynamic ECG Recordings - The 4th China Physiological Signal Challenge 2021
<p>This dataset is part of the available dataset for <em>Paroxysmal Atrial Fibrillation Events Detection from Dynamic ECG Recordings: The 4th China Physiological Signal Challenge 2021</em>, available at https://physionet.org/static/published-projects/cpsc2021/paroxysmal-atrial-fibrillation-events-detection-from-dynamic-ecg-recordings-the-4th-china-physiological-signal-challenge-2021-1.0.0.zip (last accessed today 2022-07-22).</p> <p>The dataset is licensed under Creative Commons Attribution 4.0 International Public License:</p> <p>Permissions:</p> <ul> <li>Share — copy and redistribute the material in any medium or format</li> <li>Adapt — remix, transform, and build upon the material for any purpose, even commercially.</li> </ul> <p>Conditions:</p> <ul> <li> <p>Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.</p> </li> </ul> <p>Limitations:</p> <ul> <li>No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.</li> </ul> <p>For more information about the license, check: https://creativecommons.org/licenses/by/4.0/</p> <p>The following modifications were made:</p> <ul> <li>Only the training and test set folders are used</li> <li>Only the files *.hea, *.dat and *.atr are used, being the *.dat and *.atr converted to CSV and compressed in .bz2 format</li> <li>Added the LICENSE.txt file as required.</li> </ul>
Engineering dynamic gates in binding pocket of penicillin G acylase to selectively degrade bacterial signaling molecules
<p>(01-mutants_design.tar.gz) Mutants design:</p> <ol> <li>Input structures of ecPGA from the PDB database (PDB IDs: 1GK9, 1GM7, and 1GM9), processed to resemble wild-type state, repaired by RepairPDB module of FoldX 4</li> <li>Double-point mutants preparation, analysis and filtering: <ol> <li>text files including configuration for FoldX 4</li> <li>inputs and outputs of CAVER 3.02 calculations on FoldX 4 PDB files of ecPGA double-point mutants</li> <li>input configuration file and TransportTools library 0.9.4 calculations outputs generated based on the inputs produced in step 01 and 02 above</li> <li>CSV files containing complete information about FoldX 4 stability prediction and geometrical properties from CAVER 3.02 and TransportTools library version 0.9.4 for ecPGA double-point mutants</li> </ol> </li> <li>Triple-point mutant preparation, analysis and filtering: <ol> <li>text files including configuration for FoldX 4</li> <li>inputs and outputs of CAVER 3.02 calculations on FoldX 4 PDB files of ecPGA triple-point mutants</li> <li>input configuration file and TransportTools library 0.9.4 calculations outputs generated based on the inputs produced in step 01 and 02 above</li> <li>CSV files containing complete information about FoldX 4 stability prediction and geometrical properties from CAVER 3.02 and TransportTools library version 0.9.4 for ecPGA triple-point mutants</li> </ol> </li> </ol> <p>(02-docking.tar.gz) Preparation of protein-ligand complexes using molecular docking for wild-type ecPGA and 6 best designed triple-point mutants with 6 various bacterial signaling molecules:</p> <ol> <li>PDB files of ligand, PDBQT files of the receptor and PDB files of the complexes selected from docking experiment:</li> </ol> <p>Full names of presented protein variants:<br>ecPGA_wt, wild-type Escherichia coli penicillin G acylase<br>LAF, Phe138αLeu & Met142αAla & Ile177βPhe ecPGA variant internally referred as 1GK9_Repair_22<br>LSF, Phe138αLeu & Met142αSer & Ile177βPhe ecPGA variant internally referred as 1GK9_Repair_98<br>MAF, Phe138αMet & Met142αAla & Ile177βPhe ecPGA variant internally referred as 1GK9_Repair_23<br>MSF, Phe138αMet & Met142αSer & Ile177βPhe ecPGA variant internally referred as 1GK9_Repair_99<br>VAF, Phe138αVal & Met142αAla & Ile177βPhe ecPGA variant internally referred as 1GK9_Repair_30<br>YAF, Phe138αTyr & Met142αAla & Ile177βPhe ecPGA variant internally referred as 1GK9_Repair_33<br>Full names of presented AHLs:<br>C06, N-hexanoyl-L-homoserine lactone;<br>C06-3O, N-3-oxo-hexanoyl-L-homoserine lactone;<br>C08, N-octanoyl-L-homoserine lactone;<br>C08-3O, N-3-oxo-octanoyl-L-homoserine lactone;<br>C10, N-decanoyl-L-homoserine lactone;<br>C12-3O, N-3-oxo-dodecanoyl-L-homoserine lactone</p> <p>(03-protein_ligand_MDs.tar.gz) Ligand-enzyme complexes molecular dynamics for wild-type ecPGA and 6 best designed triple-point mutants with 6 various bacterial signaling molecules:</p> <ol> <li>Force field parameters in Amber format</li> <li>Input coordinates *.inpcrd, parameters *.parm7 and *.pdb files for each complex ready for simulation in Amber</li> <li>Amber input files *.in for minimization, equilibration and production runs</li> <li>Restart files for each stage of the minimization, equilibration and production runs in Amber *.rst format</li> <li>Simulation output files for each stage of the minimization, equilibration and production runs in Amber *.mdout format</li> <li>Output files generated during post-processing of production runs trajectories in a form of text files generated by cpptraj</li> </ol> <p>(04-free_enzymes_MDs.tar.gz) Free enzymes molecular dynamics of 3 best triple-point ecPGA (VAF, YAF and MSF) mutants prioritized based on protein-ligand molecular dynamics simulations and experimental assays:</p> <ol> <li>Force field parameters and input coordinates *.inpcrd, parameters *.parm7 and *.pdb files for each complex ready for simulation in Amber format</li> <li>Amber input files *.in for minimization, equilibration and production runs</li> <li>Restart files for each stage of the minimization, equilibration and production runs in Amber *.rst format</li> <li>Simulation output files for each stage of the minimization, equilibration and production runs in Amber *.mdout format</li> <li>Post-processing analysis of generated trajectories: <ol> <li>Text files with distances, CSV files containing result of PCA and clustering, PNG files with clustered PCA results</li> <li>Inputs and outputs of MDpocket analysis and visualization of the pocket frequency grid as an isomesh</li> <li>CAVER input configuration files in text format, CAVER output data including parsed CSV and text files for visualization of entrance opening time evolution and cavity profiles inspection</li> <li>cpptraj generated text files including RMSD, distances and chi1 angles measurements</li> </ol> </li> </ol> <p>All plots were generated using matplotlib or seaborn Python libraries. Figures containing structural representations were generated using PyMOL 2.0.1.</p> <p>(05-ecPGA_VAF_YAF_MSF_penG_MDs.tar.gz) PenG-enzyme complexes molecular dynamics for wild-type ecPGA and 3 best designed triple-point mutants (VAF, YAF, MSF):</p> <ol> <li>PenG force field parameters in Amber (GAFF) format</li> <li>Input coordinates *.inpcrd, parameters *.parm7 and *.pdb files for each complex ready for simulation in Amber</li> <li>Amber input files *.in for minimization, equilibration and production runs</li> <li>Restart files for each stage of the minimization, equilibration and production runs in Amber *.rst format</li> <li>Simulation output files for each stage of the minimization, equilibration and production runs in Amber *.mdout format and analysis output files generated during post-processing of production runs trajectories in a form of text files</li> <li>Reactive Stabilization Score [RSS] statistics summarized in CSV files</li> </ol>
Data from: Migratory singers dynamically overlap the signal space of a breeding warbler community
<p>Migratory species inhabit many communities along their migratory routes. Across taxa, these species repeatedly move into and out of communities, interacting with each other and locally breeding species and competing for resources and niche space. However, their influence is rarely considered in analyses of ecological processes within the communities they temporarily occupy. Here, we explore the impact of migratory species on a breeding community using the framework of acoustic signal space, a limited resource in which sounds of species within communities co-exist. Migrating New World warblers (Parulidae, hereafter referred to as migrant species) often sing during refueling stops in areas and at times during which locally breeding warbler species (hereafter breeding species) are singing to establish territories and attract mates. We used eBird data to determine co-occurrence of 19 migrant and 11 breeding warbler species across spring migration in SW Michigan, generated a signal space from song recordings of these species, and examined patterns of signaling overlap experienced by breeding species as migrants moved through the community. Migrant species were present for two-thirds of the breeding season of local species, including periods when breeding species established territories and attracted mates. Signaling niche overlap experienced by individual breeding species was idiosyncratic and varied over time, yet niche overlap between migrant and breeding species occurred more commonly than between breeding species or between migrant species. Nevertheless, the proportion of niche overlap between migrant and breeding warblers was similar to overlap among breeding species. Our findings showed that singing by migrant species overlapped the signals of many breeding species, suggesting that migrants could have unexplored impacts on communication in breeding species, potentially affecting song detection and song evolution. Our study contributes to a growing body of research documenting impacts of migratory species on communities and ecosystems.</p>
Microscopic understanding of NMR signals by dynamic mean-field theory for spins
<p>Data collection for several plots of the article <a href="https://doi.org/10.1016/j.ssnmr.2024.101936">Microscopic understanding of NMR signals by dynamic mean-field theory for spins</a>. Each hdf5-file contains one or several datasets of a specific figure. The datasets are described by the attribute "description".</p>
Structure and dynamics of plasma irregularities over the equatorial ionospheric region: A study using spaced receiver technique employing geostationary satellites' radio signals-Data set
<p>The study investigates the characteristic features of the ionospheric irregularities using spaced receiver technique. In the spaced receiver technique, we have used a trio of receivers separated by 40 and 100 m from each other. These receivers monitor scintillations patterns of the L1 signals transmitted by the geostationary satellites. The cross-correlation of the signals and the power spectral analysis yields the measure of characteristic features of the irregularities. The data folder contains the S4 index, drift velocity of the irregularities, powerspectral slopes and size of the irregularities observed on four days. The folder also contains the gnuscript used for plotting. </p> <p> </p> <p> </p>
Method to assess the functional role of noisy brain signals by mining envelope dynamics
<p>Preprocessed envelope EEG features based on a spatial filter approach. The features were computed across multiple within-trial SVIPT events for a large hyperparameter space on data of an exemplary subject.</p> <p>The file "components.bsv" contains the preprocessed envelope features of all investigated configurations and provides underlying parameters as well as a relative path for the key ``record_dir'' to additional component information. Specifically, for each configuration the spatial filter, spatial activity pattern and the time-resolved within-trial envelope signal is provided under "records/". </p>
Computational analyses of dynamic visual courtship display reveal diet-dependent and plastic male signaling in Rabidosa rabida wolf spiders
<p>It has long been a challenge to quantify the variation in dynamic motions to understand how those displays function in animal communication. The traditional approach is dependent on labor-intensive manual identification/annotation by experts. However, the recent progress in computational techniques provides researchers with toolsets for rapid, objective, and reproducible quantification of dynamic visual displays. In the present study, we investigated the effects of diet manipulation on dynamic visual components of male courtship displays of <em>Rabidosa</em> <em>rabida</em> wolf spiders using machine learning algorithms. Our results suggest that (i) the computational approach can provide an insight into the variation in the dynamic visual display between high- and low-diet males which is not clearly shown with the traditional approach and (ii) males may plastically alter their courtship display according to the body size of females they encounter. Through the present study, we add an example of the utilization of recent computational techniques for understanding the evolution of animal behaviors.</p>
Data from: Migratory singers dynamically overlap the signal space of a breeding warbler community
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Modeling single-cell heterogeneity in signaling dynamics of macrophages reveals principles of information transmission
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Data and code from: Computational analyses of dynamic visual courtship display reveal diet-dependent male signaling in <em>Rabidosa rabida</em> wolf spiders
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Computational analyses of dynamic visual courtship display reveal diet-dependent and plastic male signaling in Rabidosa rabida wolf spiders
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Eavesdropping micropredators as dynamic limiters of sexual signal elaboration and intrasexual competition
<p>To thoroughly understand the drivers of dynamic signal elaboration requires assessing the direct and indirect effects of naturally interacting factors. Here, we use structural equation modeling (SEM) to test multivariate data from <i>in situ</i> observations of sexual signal production against a model of causal processes hypothesized to drive signal elaboration. We assess direct and indirect effects, and relative impacts, of male-male competition and attacks by eavesdropping frog-biting midges (Diptera: Corethrellidae) on call elaboration of male túngara frogs (<i>Engystomops pustulosus</i>). We find that the intensity of attacks by these micropredator flies drives the extent to which frogs elaborate their calls, likely due to a temporal trade-off between signaling and anti-micropredator defense. Micropredator attacks appear to dynamically limit a male's call rate and complexity and consequently dampen the effects of intrasexual competition. In accounting for naturally interacting drivers of signal elaboration, this study presents a counterpoint to the mechanisms traditionally thought to drive sexual selection in this system. Moreover, the results shed light on the relatively unexamined and potentially influential role of eavesdropping micropredators in the evolution of sexual communication systems.</p>
Imaging the onset of oscillatory signaling dynamics during mouse embryo gastrulation
<p>A fundamental requirement for embryonic development is the coordination of signaling activities in space and time. A notable example in vertebrate embryos is found during somitogenesis, where gene expression oscillations linked to the segmentation clock are synchronized across cells in the presomitic mesoderm (PSM) and result in tissue-level wave patterns. To examine their onset during mouse embryo development, we studied the dynamics of the segmentation clock gene Lfng during gastrulation. To this end, we established an imaging setup using selective plane illumination microscopy (SPIM) that enables culture and simultaneous imaging of up to four embryos (SPIM-for- 4). Using SPIM-for-4, combined with genetically encoded signaling reporters, we detected the onset of Lfng oscillations within newly formed mesoderm at presomite stages. Functionally, using chemical inhibition and genetic mutants, we found that initial synchrony and first ~6-8 oscillation cycles occurred even when Notch-signaling was impaired, revealing similarities to previous findings made in zebrafish embryos. Finally, we show that a spatial period gradient is already present at the onset of oscillatory activity, providing a potential mechanism accounting for our observation that wave patterns build up gradually over the first oscillation cycles.</p>
Dataset associated with "Constraints on the subsecond modulation of striatal dynamics by physiological dopamine signaling"
<p>This repository contains behavioral data, dLight photometry measurements, smoothed spiking data from recorded striatal neurons, and miniscope recordings. Text files with further explanation are provided to assist with replication of the main analyses. Matlab code to perform key analyses can be found in the accompanying GitHub repository (https://github.com/sotmasman/Dopamine-constraints)</p>
Molecular Dynamics Simulation and Docking Studies Reveals Inhibition of NF-kB signaling as a Promising Therapeutic Drug Target for reduction in Cytokines Storms
<p><span>The complexes of the top identified molecules with NF-kB-kB site, as well as all the designed molecules used in the screening process. </span></p>
Data and code from: Dynamics of cortical contrast adaptation predict perception of signals in noise
<p>Neurons throughout the sensory pathway adapt their responses depending on the statistical structure of the sensory environment. Contrast gain control is a form of adaptation in the auditory cortex, but it is unclear whether the dynamics of gain control reflect efficient adaptation, and whether they shape behavioral perception. Here, we trained mice to detect a target presented in background noise shortly after a change in the contrast of the background. The observed changes in cortical gain and behavioral detection followed the dynamics of a normative model of efficient contrast gain control; specifically, target detection and sensitivity improved slowly in low contrast, but degraded rapidly in high contrast. Auditory cortex was required for this task, and cortical responses were not only similarly affected by contrast but predicted variability in behavioral performance. Combined, our results demonstrate that dynamic gain adaptation supports efficient coding in auditory cortex and predicts the perception of sounds in noise.</p>
Data from: Colourful network: Pair-bonding temporal dynamics involve sexual signals and impact reproduction
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Data and code from: Dynamics of cortical contrast adaptation predict perception of signals in noise
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Eavesdropping micropredators as dynamic limiters of sexual signal elaboration and intrasexual competition
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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.