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11,506 results for “Dynamics”
Sex and Age Impact CD4+ T Cell Susceptibility to HIV In Vitro Through Cell Activation Dynamics
<p>Cellular composition and the responsiveness of the immune system evolve upon aging and are influenced by biological sex. CD4+ T cells from women living with HIV exhibit a decreased viral replication ex vivo compared to men's. We, thus, hypothesized that these findings could be recapitulated in vitro and infected primary CD4+ T cells with HIV-based vectors pseudotyped with VSV-G or HIV envelopes. We used cells isolated from twenty donors to interrogate the effect of sex and age on permissiveness over a six-day activation kinetics. Our data identified an increased permissiveness to HIV between 24 and 72 h post-stimulation. Sex- and age-based analyses at these time points showed an increased susceptibility to HIV of the cells isolated from males and from donors over 50 years of age, respectively. A parallel assessment of surface markers' expression revealed higher frequencies of activation marker CD69 and of immune checkpoint inhibitors (PD-1 and CTLA-4) in the cells from highly permissive donors. Furthermore, positive correlations were identified between the expression kinetics of CD69, PD-1 and CTLA-4 and HIV expression kinetics. The cell population heterogeneity was assessed using a single-cell RNA-Seq analysis and no cell subtype enrichment was identified according to sex. Finally, transcriptomic analyses further highlighted the role of activation in those differences with enriched activation and cell cycle gene sets in male and older female cells. Altogether, this study brought further evidence about the individual features affecting HIV replication at the cellular level and should be considered in latency reactivation studies for an HIV cure.</p>
Unveiling the genetic networks: Exploring the dynamic interaction of photosynthetic phenotypes in woody plants across varied light gradients
<p><em>Background:</em></p> <p>Understanding the mechanisms by which genes control and regulate complex quantitative traits during periods of fluctuating resources remains a challenging and uncertain task in photosynthesis studies. Most studies have focused on the structure of photosynthesis, the photosynthetic response under stress, or the genetic mechanisms involved in photosynthetic effects and neglected the interactive genetic mechanism that governs various traits through significant quantitative trait loci (QTLs). Results In this study, we have developed a differential dynamic system that enables the identification of QTLs based on the photosynthetic phenotypic and genotypic data under varying levels of light intensity gradients. The framework not only allows for the assessment of the direct effects of QTLs on phenotypes but also captures how they influence interactions among phenotypes as light intensities change. We have analyzed the genetic effects and genetic variance, visualized the genetic network associated with photosynthesis interactions, and validated the effectiveness and stability of the DDS framework. Pivotal QTLs were identified individually to uncover the process and pattern of interaction. Through functional annotation, we made an intriguing discovery that seemingly unimportant QTLs can still have significant genetic effects on phenotypic changes through their regulation with other QTLs. Conclusions This finding emphasizes the significance of considering the interactive genetic architecture when seeking to understand the genetic interaction mechanism of photosynthesis in natural populations of woody plants. Moreover, our research provides a novel framework that can be extended to explore the interactive genetic architecture among organisms, contributing to a deeper understanding of stress resistance mechanisms in woody plants.</p>
Research data supporting: "Machine learning of microscopic structure-dynamics relationships in complex molecular systems"
<p>This repository contains the set of data and the code to reproduce the results shown in "Machine learning of microscopic structure-dynamics relationships in complex molecular systems" published on Machine Learning: Science and Technology (DOI: 10.1088/2632-2153/ad0fa5).</p>
Data from: A dynamical model of growth and maturation in Drosophila
<p>The decision to stop growing and mature into an adult is a critical point in development that determines adult body size, impacting multiple aspects of an adult's biology. In many animals, growth-cessation is a consequence of hormone release that appears to be tied to attainment of particular body size or condition. Nevertheless, the size-sensing mechanism animals use to initiate hormone synthesis is poorly understood. Here we develop a simple mathematical model of growth cessation in <em>Drosophila melanogaster</em>, which is ostensibly triggered by attainment of a critical weight early in the last instar. Attainment of critical weight is correlated with synthesis of the steroid hormone ecdysone, which causes a larva to stop growing, pupate and metamorphose into the adult form. Our model suggests that, contrary to expectation, the size-sensing mechanism that initiates metamorphosis occurs before the larva reaches critical weight; that is, the critical-weight phenomenon is a downstream consequence of an earlier size-dependent developmental decision, not a decision point itself. Further, this size-sensing mechanism does not require a direct assessment of body size, but emerges from the interactions between body size, ecdysone and nutritional signaling. Because many aspects of our model are evolutionarily conserved among all animals, the model may provide a general framework for understanding how animals commit to maturing from their juvenile to adult form.</p>
Climate and vegetation change in a coastal marsh: two snapshots of groundwater dynamics and tidal flooding at Piermont Marsh, NY spanning 20 years
<p>Groundwater hydrology plays an important role in coastal marsh biogeochemical function, in part because groundwater dynamics drive the zonation of macrophyte community distribution. Changes that occur over time, such as sea level rise and shifts in habitat structure are likely altering groundwater dynamics and eco-hydrological zonation. We examined tidal flooding and marsh water table dynamics in 1999 and 2019 and mapped shifts in plant distributions over time, at Piermont Marsh, a brackish tidal marsh located along the Hudson River Estuary near New York City. We found evidence that the marsh surface was flooded more frequently in 2019 than in 1999, and that tides were propagating further into the marsh in 2019, although marsh surface elevation gains were largely matching that of sea level rise. The changes in groundwater hydrology that we observed are likely due to the high tide rising at a rate that is greater than that of mean sea level. In addition, we reported on changes in plant cover by <em>P. australis</em>, which has displaced native marsh vegetation at Piermont Marsh. Although <em>P. australis</em> has increased in cover, wrack deposition and plant die off associated Superstorm Sandy allowed for native vegetation to rebound in part of our focus area. These results suggest that climate change and plant community composition may interact to shape ecohydrologic zonation. Considering these results, we recommend that habitat models consider tidal range expansion and groundwater hydrology as metrics when predicting the impact of sea level rise on marsh resilience.</p>
Native MS dataset for: "Insights into the pathogenesis of primary hyperoxaluria type I from the structural dynamics of alanine:glyoxylate aminotransferase variants"
<p>Native mass spectrometry dataset used in: <strong>Insights into the pathogenesis of primary hyperoxaluria type I from the structural dynamics of alanine:glyoxylate aminotransferase variants.</strong> Pavla Vankova, Juan Luis Pacheco-Garcia, Dmitry S. Loginov, Atanasio Gómez-Mulas, Alan Kádek, José Manuel Martín-Garcia, Eduardo Salido, Petr Man and Angel L. Pey. FEBS Letters (2024)</p> <p><strong>Description:</strong></p> <p>Native mass spectrometry (MS) analysis verifying the oligomeric state of alanine:glyoxylate aminotransferase (AGT) protein and its P11L and I340M (LM) polymorphism and LM G170R mutation variants in primary hyperoxaluria type I.</p> <p><strong>Sample processing:</strong></p> <p>AGT protein as well as its LM and LM G130R mutants were buffer exchanged into 150 mM aqueous ammonium acetate solution (pH 7.5, MS-grade, Sigma-Aldrich) through six cycles of tenfold dilution and re-concentration using centrifugal concentrators Vivaspin 500 (30 kDa cut-off, <em>Sartorius</em>). Desalted proteins were introduced into a Synapt G2Si mass spectrometer (Waters) via static nanoelectrospray ionization from in-house prepared gold-coated borosilicate glass capillaries Kwik-Fil 1B120F-4 (<em>World Precision Instruments</em>). Protein concentration in samples was determined by 280 nm absorbance measurements using DeNovix DS-11 spectrophotometer. Samples were diluted in ammonium acetate and electrosprayed at 1 and 2 µM concentration. The mass spectrometer was carefully tuned for best signal quality and intensity, while keeping ion activation and unfolding minimal. Namely, electrospray voltage was kept at 1.3 kV, source desolvation temperature 80°C, sampling cone 80 V and 10 V collision voltage with 6 ml/min flow of argon in the trap region for thermalization of ions. Quadrupole was operated in a broadband transmission mode up to 8000 m/z while the spectra were acquired in mass range 500 – 20000 m/z. Spectra were externally mass recalibrated using known masses of caesium iodide clusters.</p> <p><strong>Data processing:</strong></p> <p>Raw mass spectra were averaged over 75 scans and further processed in Waters MassLynx 4.1. The averaged spectra were exported for ZENODO deposition as plain in plain m/z vs intensity .txt files as well uploaded as part of the .raw file format of the whole analysis (including initial metadata) with scan descriptions and parameter changes described in a stand-alone .txt descriptor file.</p>
Analysis of bacteria, inflammation, and exudation in epidermal suction blister wounds reveals dynamic changes during wound healing - Dataset
<p>Dataset for "<strong>Analysis of bacteria, inflammation, and exudation in epidermal suction blister wounds reveals dynamic changes during wound healing</strong>". Data were generated from samples collected to a biobank from suction blister wounds at various timepoints during a clinical trial (<a href="https://clinicaltrials.gov/study/NCT05378997?term=NCT05378997&rank=1"><strong>NCT05378997</strong></a>). Data include concentration of bacteria in swab and dressing fluid samples, neutrophil proteins (HNE, MPO, and HBP), cytokines (IFN-gamma, interleukin IL-1beta, IL-2, IL-4, IL-6, IL-8, IL-10, IL-12p70, IL-13, TNF-alpha) and total protein measured in dressing fluid samples, and bacterial species identified by MALDI-TOF in swab and dressing fluid samples.</p>
Dataset underlying the study "Enhanced Susceptibility to Tomato Chlorosis Virus (ToCV) in Hsp90- and Sgt1-Silenced Plants: Insights from Gene Expression Dynamics"
<p>This dataset is underlying the scientific publication titled "Enhanced Susceptibility to Tomato Chlorosis Virus (ToCV) in Hsp90- and Sgt1-Silenced Plants: Insights from Gene Expression Dynamics", published in the <a href="https://www.mdpi.com/1999-4915/15/12/2370">Viruses</a> journal. </p><p>The dataset includes a time-course transcriptome analysis using RNA-seq of naïve (no whitefly and no virus), mock (non-viruliferous whiteflies) and ToCV (ToCV_viruliferous whiteflies)-treated tomato samples at 2, 7, and 14 days post-infection (dpi) and viral small RNAs derived from Tomato plants infected with ToCV at 14 dpi. The dataset provided here has been deposited in full by the authors in the European Nucleotide Archive (ENA) at EMBL-EBI under accession number PRJEB67704 (<a href="https://www.ebi.ac.uk/ena/browser/view/PRJEB67704"><strong>https://www.ebi.ac.uk/ena/browser/view/PRJEB67704</strong></a><br><br>The provided information in the dataset are further discussed and interpreted in detail, as well as their subsequent results, in the scientific publication.</p><p>This research was conducted within the VIRTIGATION project, which is part of the EU Open Research Data pilot. This project has received funding from the European Union's Horizon 2020 research and innovation program under grant agreement No. 101000570.</p>
The role of tropical rainfall in driving range dynamics for a long-distance migratory bird
<p>Predicting how the range dynamics of migratory species will respond to climate change requires a mechanistic understanding of the factors that operate across the annual cycle to control the distribution and abundance of a species. Here we use multiple lines of evidence to reveal that environmental conditions during the nonbreeding season influence range dynamics across the lifecycle of a migratory songbird, the American redstart (<em>Setophaga ruticilla</em>). Using long-term data from the nonbreeding grounds and breeding origin estimated from stable hydrogen isotopes in tail feathers, we found that the relationship between nonbreeding season survival and migration distance is mediated by precipitation, but only during dry years. A long-term drying trend throughout the Caribbean is associated with higher mortality for individuals from the northern portion of the species' breeding range, resulting in an approximate 500 km southward shift in breeding origins of this Jamaican population over the past 30 years. This shift in connectivity is mirrored by changes in the redstarts breeding distribution of abundance. These results demonstrate that the climatic effects on demographic processes originating during the tropical nonbreeding season is actively shaping range dynamics in a migratory bird.</p>
Greenhouse gas dynamics in river networks fragmented by drying and damming
<p>River fragmentation by drying and damming is occurring more frequently in the Anthropocene, yet there is limited research about its effects on greenhouse gas (GHG) fluxes. These fragmented rivers have the potential to be important sources of GHGs to the atmosphere through both similar and dissimilar mechanisms. Our objective was to review the literature of the individual and the interactive effects of fragmentation by drying and damming on GHG fluxes in river networks, identifying the magnitudes and drivers of CO<sub>2</sub>, methane (CH<sub>4</sub>), and N<sub>2</sub>O flux rates. We conducted a systematic search of studies addressing the separate and interactive effects of drying and damming on GHG fluxes from running waters. The search was primarily conducted using Web of Science for studies published from 1900 to January 2021. For the 42 studies about rivers impacted by drying, 54 about damming, and 6 about their interactive effects, we collected a suite of qualitative and quantitative information. The major proximal drivers of GHG emissions in river networks impacted by drying were sediment moisture, sediment temperature, sediment organic matter content and sediment texture. In networks impacted by damming, the major proximal drivers were water temperature, dissolved oxygen, and chlorophyll ɑ. We found research lacking in non-arid climates for drying, and on small water retention structures for damming. We propose a conceptual model where the spatial distribution of fragmentation is the principle driver of GHG fluxes at the network scale. </p>
Bacterial pathogens dynamic during multi-species infections
<p>Illumina gapA sequences of synthetic communities of plant bacterial pathogens: Pectobacterium and Dickeya genus. Sequencing was performed after growth on TSB synthetic medium (2 days post inoculation) or growth on potato tubers (5 days post infection).</p> <p> </p> <p>The following files are available:</p> <p>PT_table.txt: description of the potato tubers samples</p> <p>TSB_table.txt: description of samples in synthetic medium (TSB)</p> <p>gapA_PT.fasta.gz: Illumina fasta sequences after potato tubers infection (35,000 reads)</p> <p>gapA_TSB.fasta.gz: Illumina fasta sequences after synthetic medium inoculation (35,000 reads)</p> <p>gapA_without_primers.fasta: gapA sequences (without primers) of Pectobacterium and Dickeya strains used in this study (27 strains)</p> <p>species.txt: list of bacterial species used in this study (9 species)</p> <p>strains.txt: list of bacterial strains used in this study (27 strains)</p> <p>count.py: python3 script used to analyse the output of blastn</p> <p>R_script_FigureS1.R: R script for statistical analysis</p> <p>R_script_Figure2b.R: R script for statistical analysis</p> <p>R_script_Figure2a.R: R script for statistical analysis</p> <p> </p> <p>Method (examplified with the gapA_TSB sequences at the species level):</p> <p>• gapA sequences were blasted (blastn) against gapA sequences of Pectobacterium and Dickeya strains used in this study:</p> <p>makeblastdb -in gapA_without_primers.fasta -dbtype nucl -out dbblastn</p> <p>blastn -db dbblastn -query gapA_TSB.fasta -outfmt 6 -out blast.blastn -num_threads 12 -evalue 0.00001 -num_alignments 1</p> <p>• Reads count. Reads matching (100% identity) with gapA sequences of Pectobacterium and Dickeya strains used in this study were counted using the count.py python script. The output is a tab-separated values (.tsv) file:</p> <p>python3 count.py species.txt blast.blastn</p>
Experimental data for "Exact inversion of partially coherent dynamical electron scattering for picometric structure retrieval"
Open the record for dataset details and reuse information.
Molecular dynamics simulation of human ρ1 GABAA receptor with neurosteriod pregnenolone sulfate
<p>Molecular dynamics simulation trajectory, parameter files for the systems of human ρ1 GABAA receptor with neurosteriod pregnenolone sulfate. Pregnenolone sulfate was tested with two different poses, either sulfate group "up" or "down".</p> <p> </p>
Eco-evolutionary dynamics of anthelmintic resistance in soil-transmitted helminths
<p>Anthelmintic resistance (AR) of helminth parasites against the most widely available drugs is an ongoing concern for both human and livestock-infecting species. Indeed, there has been substantial evidence of AR in livestock but less in humans, which may be due to a variety of reasons. In this paper, we develop an eco-evolutionary model that couples the life cycle of these parasites with their underlying evolution in a single biallelic genetic locus that confers resistance to treatment drugs. We determine the critical treatment frequency needed to effectively eliminate the population, for a fixed drug efficacy (without evolution) and use this to classify three qualitative distinct behaviors of the eco-evolutionary model. Then, we describe how aspects of the life cycle influence which qualitative outcome is achieved and the spread of the resistance allele, comparing across human- and livestock- infecting species. For all but one species, we find that lower fecundity rates and lower contact rates speed the spread of resistance, while lower larval death slows it down. The life cycle parameters of <em>Ancylostoma duodenale</em> and <em>Ostertagia circumcincta</em> are associated with the fastest and slowest spread of resistance, respectively. We discuss the mechanistic reason for these results.</p>
Year 1 Tanzanian ponds snail-parasite dynamics
<div> <div> <div> <div> <p>Different populations of hosts and parasites experience distinct seasonality in environmental factors, depending on local-scale biotic and abiotic factors. This can lead to highly heterogeneous disease outcomes across host ranges. Variable seasonality characterizes urogenital schistosomiasis, a neglected tropical disease caused by parasitic trematodes (<em>Schistosoma</em> <em>haematobium</em>). Their intermediate hosts are aquatic <em>Bulinus</em> snails that are highly adapted to extreme rainfall seasonality, undergoing prolonged dormancy yearly. While <em>Bulinus</em> snails have a remarkable capacity for rebounding following dormancy, we investigated the extent to which parasite survival within snails is diminished. We conducted an investigation of seasonal snail-schistosome dynamics in 109 ponds of variable ephemerality in Tanzania from August 2021 to July 2022. First, we found that ponds have two synchronized peaks of schistosome infection prevalence and observed cercariae, though of lower magnitude in the fully-desiccating than non-desiccating ponds. Second, we evaluated total yearly schistosome prevalence across an ephemerality gradient, finding ponds with intermediate ephemerality to have the highest infection rates. We also investigated dynamics of non-schistosome trematodes, which lacked synonymity with schistosome patterns. We found peak schistosome transmission risk at intermediate pond ephemerality, thus the impacts of anticipated increases in landscape desiccation could result in increases or decreases in transmission risk with global change.</p> </div> </div> </div> </div>
Data from: Parasite-mediated changes in host traits alter food web dynamics
<p><span>Parasites commonly alter the phenotype of their host, thereby influencing competitive and consumer-resource interactions. This could trigger a cascade effect on the dynamics of biological communities, but the role of parasites in ecosystem processes is poorly understood. In this study, we investigate how parasite-induced trait modifications shape the dynamics of a complex lake food web using an allometric trophic network model (ATN). We simulated infections of stage-structured fish host populations via increased maintenance costs and predation risk. Our results show that host trait modifications can significantly impact host demography, with stage-specific biomass declines up to 60%. However, less severely affected host stages buffered these effects and sustained the population. Importantly, host biomass decline altered the dynamics of species interactions and these effects cascaded through the entire community, with biomass changes observed at all trophic levels. Our findings emphasize the importance of incorporating both indirect parasite effects and host life history in ecological network studies for more realistic simulations of community dynamics.</span></p>
Bridging length scales in organic mixed ionic-electronic conductors through internal strain and mesoscale dynamics
<p>Understanding structural and dynamic properties of inherently disordered systems at the mesoscale is crucial. This is particularly important in organic mixed ionic-electronic conductors (OMIECs), which undergo significant and complex structural changes when operated in electrolyte. In this study, we investigate the mesoscale strain, reversibility, and dynamics of a model OMIEC material under external electrochemical potential using operando X-ray photon correlation spectroscopy. Our results reveal mesoscale strain and structural hysteresis that depend on the sample's cycling history, establishing a comprehensive kinetic sequence bridging the macroscopic and microscopic behaviors of OMIECs. Furthermore, we uncover equilibrium and non-equilibrium dynamics of charge carriers and material doping states, highlighting the unexpected coupling between charge carrier dynamics and mesoscale order. These findings advance our understanding of the structure-dynamics-function relationships in OMIECs, opening pathways for designing and engineering materials with improved performance and functionality in non-equilibrium states during device operation.</p>
An integrated population model reveals source-sink dynamics for competitively subordinate African wild dogs linked to anthropogenic prey depletion
<ol> <li>Many African large carnivore populations are declining due to decline of the herbivore populations on which they depend. The densities of apex carnivores like the lion and spotted hyena correlate strongly with prey density, but competitive subordinates like the African wild dog benefit from competitive release when the density of apex carnivores is low, so the expected effect of a simultaneous decrease in resources and dominant competitors is not obvious. </li> <li>Wild dogs in Zambia's Luangwa Valley Ecosystem occupy four ecologically similar areas with well-described differences in the densities of prey and dominant competitors, due to spatial variation in illegal offtake.</li> <li>We used long-term data to fit a Bayesian integrated population model (IPM) of the demography and dynamics of wild dogs in these four regions. The IPM used Leslie projection to link a Cormack-Jolly-Seber model of area-specific survival (allowing for individual heterogeneity in detection), a zero-inflated Poisson model of area-specific fecundity, and a state-space model of population size that used estimates from a closed mark-capture model as the counts from which (latent) population size was estimated.</li> <li>The IPM showed that both survival and reproduction were lowest in the region with the lowest density of preferred prey (puku, <em>Kobus vardonii</em>, and impala, <em>Aepyceros</em> <em>melampus</em>), despite little use of this area by lions. Survival and reproduction were highest in the region with the highest prey density, and intermediate in the two regions with intermediate prey density. The population growth rate (λ) was positive for the population as a whole, strongly positive in the region with the highest prey density, and strongly negative in the region with the lowest prey density.</li> <li>It has long been thought that the benefits of competitive release protect African wild dogs from the costs of low prey density. Our results show that the costs of prey depletion overwhelm the benefits of competitive release and cause local population decline where anthropogenic prey depletion is strong. Because competition is important in many guilds and humans are affecting resources of many types, it is likely that similarly fundamental shifts in population limitation are arising in many systems.</li> </ol>
Task-driven neural network models predict neural dynamics of proprioception: Synthetic muscle spindle datasets
<p>#############</p> <p>Task-driven neural network models predict neural dynamics of proprioception, Cell 2024</p> <p>#############</p> <p>Authors: Marin Vargas, Alessandro (orcid=0000-0001-7073-4120) and Bisi, Axel (orcid=0009-0006-8602-7555) and Chiappa, Alberto Silvio (orcid=0009-0001-2764-6552) and Versteeg, Christopher (orcid=0000-0002-4269-5109) and Miller, Lee E. (orcid=0000-0001-8675-7140) and Mathis, Alexander (orcid=0000-0002-3777-2202)</p> <p>Affiliation: EPFL</p> <p>Date: January, 2024</p> <p>Link to the Cell article: </p> <p><a href="https://www.cell.com/cell/pdf/S0092-8674(24)00239-3.pdf">https://www.cell.com/cell/pdf/S0092-8674(24)00239-3.pdf</a></p> <p>--------------------------------</p> <p>Here we provide the synthetic spindle datasets of our article "Task-driven neural network models predict neural dynamics of proprioception". It contains the synthetic generated training dataset of simulated muscle spindles during arm passive movements generated with either character writing (PCR) or with 3D target reaching using reinforcement learning (RL).</p> <p>The overall structure of the data is:</p> <p>└── spindle_datasets<br> ├── pcr_dataset - Contains PCR synthetic training dataset<br> └── rl_dataset - Contains RL-generated synthetic training dataset</p> <p>The code to generate the PCR synthetic spindle dataset is available at: <a href="https://github.com/amathislab/Task-driven-Proprioception/tree/master/PCR-data-generation">https://github.com/amathislab/Task-driven-Proprioception/tree/master/PCR-data-generation</a></p> <p>The code to generate the RL-generated synthetic spindle dataset is available at: <a href="https://github.com/amathislab/Task-driven-Proprioception/tree/master/RL-data-generation">https://github.com/amathislab/Task-driven-Proprioception/tree/master/RL-data-generation</a></p> <p>--------------------------------</p> <p>The datasets, weights, activations and predictions are released with Creative Commons Attribution 4.0 license.</p> <p>The code is released under the MIT license, see <a href="https://github.com/amathislab/Task-driven-Proprioception">https://github.com/amathislab/Task-driven-Proprioception</a></p> <p>If you find our code, weights, predictions or ideas useful, please cite:</p> <p>@article{vargas2024task,<br> title={Task-driven neural network models predict neural dynamics of proprioception},<br> author={{Marin Vargas}, Alessandro and Bisi, Axel and Chiappa, Alberto S and Versteeg, Chris and Miller, Lee E and Mathis, Alexander},<br> journal={Cell},<br> year={2024},<br> publisher={Elsevier}<br>}</p>
Task-driven neural network models predict neural dynamics of proprioception: Neural network model weights
<p>#############</p> <p>Task-driven neural network models predict neural dynamics of proprioception, Cell 2024</p> <p>#############</p> <p>Authors: Marin Vargas, Alessandro (orcid=0000-0001-7073-4120) and Bisi, Axel (orcid=0009-0006-8602-7555) and Chiappa, Alberto Silvio (orcid=0009-0001-2764-6552) and Versteeg, Christopher (orcid=0000-0002-4269-5109) and Miller, Lee E. (orcid=0000-0001-8675-7140) and Mathis, Alexander (orcid=0000-0002-3777-2202)</p> <p>Affiliation: EPFL</p> <p>Date: January, 2024</p> <p>Link to the Cell article: </p> <p><a href="https://www.cell.com/cell/pdf/S0092-8674(24)00239-3.pdf">https://www.cell.com/cell/pdf/S0092-8674(24)00239-3.pdf</a></p> <p>--------------------------------</p> <p>Here we provide the trained model checkpoints for all tasks of our article "Task-driven neural network models predict neural dynamics of proprioception". It contains 300 temporal convolutional networks (TCNs) and 50 LSTM models trained on 16 tasks as well as the untrained initialization. </p> <p>The overall structure of the data is:</p> <p>└── models<br> ├── deepdraw_models - Contains networks hyperparameters<br> │ ├── template_models - Contains the default parameters<br> │ ├── torque - Contains network hyperparameters for the torque task<br> │ └── ... <br> ├── experiment_*** - Contains checkpoint of trained and untrained models <br> ├── ... <br> └── ... </p> <p>--------------------------------</p> <p>The checkpoints are stored in experiment folders (experiment_***) that follow this scheme:<br>- Task: shallow exp id, deep TCNs exp id, LSTM id.</p> <p>Experiment IDs for each task:</p> <p>- Untrained: 15, 115, 45<br>- Classification: 4015, 5015, 4045</p> <p>- Torque: 8015, 8030, 8045</p> <p>- Regress joint pos: 17016, 17031, 17046<br>- Regress joint vel: 17216, 17231, 17246<br>- Regress joint pos & vel:: 17416, 17431, 17446<br>- Regress joint pos & vel & acc:: 20516, 20531, 20546</p> <p>- Regress hand pos: 4016, 5016, 4046<br>- Regress hand vel: 17316, 17331, 17346<br>- Regress hand pos & vel: 17516, 17531, 17546<br>- Regress hand pos & vel & acc: 20416, 17831, 17846</p> <p>- Regress hand and elbow pos: 20016, 20031, 20046<br>- Regress hand and elbow vel: 20916, 20931, 20946<br>- Regress hand and elbow pos & vel: 20616, 20631, 20646<br>- Regress hand and elbow pos & vel & acc: 20816, 20831, 20846</p> <p>- Redundancy reduction - task transfer (AR): 10020, 10035, 10050<br>- Redundancy reduction - task transfer (HP): 10021, 10036, 10051<br>- Autoencoder 20716 & 20717, 20731 & 20732, X</p> <p>The code to load, evaluate and train the models is available at: <a href="https://github.com/amathislab/Task-driven-Proprioception/tree/master/nn-training">https://github.com/amathislab/Task-driven-Proprioception/tree/master/nn-training</a></p> <p>--------------------------------</p> <p>The datasets, weights, activations and predictions are released with Creative Commons Attribution 4.0 license.</p> <p>The code is released under the MIT license, see <a href="https://github.com/amathislab/Task-driven-Proprioception">https://github.com/amathislab/Task-driven-Proprioception</a></p> <p>If you find our code, weights, predictions or ideas useful, please cite:</p> <p>@article{vargas2024task,<br> title={Task-driven neural network models predict neural dynamics of proprioception},<br> author={{Marin Vargas}, Alessandro and Bisi, Axel and Chiappa, Alberto S and Versteeg, Chris and Miller, Lee E and Mathis, Alexander},<br> journal={Cell},<br> year={2024},<br> publisher={Elsevier}<br>}</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.