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opencc-by-4.0Jan 2024View details →

Task-driven neural network models predict neural dynamics of proprioception: Experimental data, activations and predictions of neural network models

############# Task-driven neural network models predict neural dynamics of proprioception, Cell 2024 ############# 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) Affiliation: EPFL Date: January, 2024 Link to the Cell article: <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> -------------------------------- Here we provide the neural data, activation and predictions for the best models and result dataframes of our article "Task-driven neural network models predict neural dynamics of proprioception". It contains the behavioral and neural experimental data (cuneate nucleus and somatosensory recordings from the Miller Lab, Northwestern University), the result dataframes for task-driven and untrained models, the activations and predictions for the *best models for all tasks* for active and passive movements and the predictions for linear models for active and passive movements.  Note, the predictions of other models can be computed from the network weights that were deposited for all trained models.  The overall structure of the data is: └── exp_analysis     ├── results                                                                - Contains the result dataframe of the predictions for all models, tasks and primates     ├── activations     │   ├── active                                                            - Contains activations related to active movements     │   └── passive                                                         - Contains activations related to passive movements     ├── predictions     │   ├── active                                                            - Contains predictions related to active movements     │   └── passive                                                         - Contains predictions related to passive movements     └── beh_exp_datasets         ├── matlab_data                                                 - Contains raw behavioral and neural data         ├── MonkeyAlignedDatasets_new                   - Contains padded test behavioral input for generating network activations         ├── MonkeyDatasets                                         - Contains not aligned padded test behavioral input for generating network activations         ├── MonkeySpikeRegressDatasets                 - Contains datasets for training data-driven models         ├── MonkeySpikeRegressDatasets_new        - Contains trial index for regression splits          └── new_beh_exp_dataframe                           - Contains pre-processed behavioral and neural data -------------------------------- The activations and predictions for the best 3 models and for all tasks are stored in experiments folder (in .h5 format) that follows the same name convention of the checkpoints. The checkpoints are stored in experiment folders (experiment_***) that follow this scheme: - Task:         shallow exp id,     deep TCNs exp id,     LSTM id. Experiment IDs for each task: - Untrained:                                                               15,         115,         45 - Classification:                                                        4015,   5015,   4045 - Torque:                                                                    8015,   8030,   8045 - Regress joint pos:                                                 17016,  17031,  17046 - Regress joint vel:                                                   17216,  17231,  17246 - Regress joint pos & vel::                                       17416,  17431,  17446 - Regress joint pos & vel & acc::                            20516,  20531,  20546 - Regress hand pos:                                                 4016,   5016,   4046 - Regress hand vel:                                                   17316,  17331,  17346 - Regress hand pos & vel:                                        17516,  17531,  17546 - Regress hand pos & vel & acc:                             20416,  17831,  17846 - Regress hand and elbow pos:                              20016,  20031,  20046 - Regress hand and elbow vel:                                20916,  20931,  20946 - Regress hand and elbow pos & vel:                     20616,  20631,  20646 - Regress hand and elbow pos & vel & acc:          20816,  20831,  20846 - Redundancy reduction:                                          10020,  10035,  10050 - Autoencoder                                                            20716 & 20717, 20731 & 20732,   X   The code to process the behavioral data is available at: <a href="https://github.com/amathislab/Task-driven-Proprioception/tree/master/exp_data_processing">https://github.com/amathislab/Task-driven-Proprioception/tree/master/exp_data_processing</a> The code to load and use the models to generate activations and predictions is available at: <a href="https://github.com/amathislab/Task-driven-Proprioception/tree/master/neural_prediction">https://github.com/amathislab/Task-driven-Proprioception/tree/master/neural_prediction</a> To reproduce the results, it is possible to reproduce the main figures using the result dataframe. See our repository for more details.  -------------------------------- The datasets, weights, activations and predictions are released with Creative Commons Attribution 4.0 license. 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> If you find our code, weights, predictions or ideas useful, please cite: @article{vargas2024task,   title={Task-driven neural network models predict neural dynamics of proprioception},   author={{Marin Vargas}, Alessandro and Bisi, Axel and Chiappa, Alberto S and Versteeg, Chris and Miller, Lee E and Mathis, Alexander},   journal={Cell},   year={2024},   publisher={Elsevier} }

opencc-zeroJan 2024View details →

Data for: Land use change and coastal water darkening drive synchronous dynamics in phytoplankton and fish phenology on centennial time scales

At high latitudes, the suitable window for timing reproductive events is particularly narrow, promoting tight synchrony between trophic levels. Climate change may disrupt this synchrony due to diverging responses to temperature between e.g. the early life stages of higher trophic levels and their food resources. Evidence for this is equivocal, and the role of compensatory mechanisms are poorly understood. Here, we show how a combination of ocean warming and coastal water darkening drive long-term changes in phytoplankton spring bloom timing in Lofoten Norway, and how spawning time of Northeast Arctic cod responds in synchrony. Spring bloom timing was derived from hydrographical observations dating back to 1936, while cod spawning time was estimated from weekly fisheries catch and roe landing data since 1877. Our results suggest that land use change causing coastal water darkening has gradually delayed the spring bloom up to 1990 after which ocean warming has caused it to advance. The cod appear to track phytoplankton dynamics by timing gonadal development and spawning to maximize overlap between offspring hatch date and predicted resource availability. This finding emphasises the importance of land-ocean coupling for coastal ecosystem functioning, and the potential for fish to adapt through phenotypic plasticity.

opencc-zeroFeb 2024View details →

Dynamic 1D search and processive nucleosome translocations by RSC and ISW2 chromatin remodelers

Eukaryotic gene expression is linked to chromatin structure and nucleosome positioning by ATP-dependent chromatin remodelers that establish and maintain nucleosome-depleted regions (NDRs) near transcription start-sites. Conserved yeast RSC and ISW2 remodelers exert antagonistic effects on nucleosomes flanking NDRs, but the temporal dynamics of remodeler search, engagement and directional nucleosome mobilization for promoter accessibility are unknown. Using optical tweezers and 2-color single-particle imaging, we investigated the Brownian diffusion of RSC and ISW2 on free DNA and sparse nucleosome arrays. RSC and ISW2 rapidly scan DNA by one-dimensional hopping and sliding respectively, with dynamic collisions between remodelers followed by recoil or apparent co-diffusion. Static nucleosomes block remodeler diffusion resulting in remodeler recoil or sequestration. Remarkably, both RSC and ISW2 use ATP hydrolysis to translocate mono-nucleosomes processively at ~30 bp/sec for surprising distances on extended linear DNA. Processivity and opposing push-pull directionalities of nucleosome translocation shown by RSC and ISW2 shape the distinctive landscape of promoter chromatin.

opencc-zeroFeb 2024View details →

Data from: Ancient and modern genomes reveal microsatellites maintain a dynamic equilibrium through deep time

Microsatellites are widely used in population genetics, but their evolutionary dynamics remain poorly understood. It is unclear whether microsatellite loci drift in length over time. This is important because the mutation processes that underlie these important genetic markers are central to the evolutionary models that employ microsatellites. We identify more than 27 million microsatellites using a novel and unique dataset of modern and ancient Adélie penguin genomes along with data from 63 published chordate genomes. We investigate microsatellite evolutionary dynamics over two time scales: one based on Adélie penguin samples dating to approximately 46.5 kya, the other dating to the diversification of chordates more than 500 Mya. We show that the process of microsatellite allele length evolution is at dynamic equilibrium; while there is length polymorphism among individuals, the length distribution for a given locus remains stable. Many microsatellites persist over very long time scales, particularly in exons and regulatory sequences. These often retain length variability, suggesting that they may play a role in maintaining phenotypic variation within populations.

Dynamical Parameters and Clustering Results for Four-hundred Very Metal-Poor Stars Studied with LAMOST and Subaru

This is the data associated with the paper "Four-hundred Very Metal-Poor Stars Studied with LAMOST and Subaru. III. Dynamically Tagged Groups and Chemodynamical Properties" by Zhang, Matsuno, Li et al. 2024. Table "LSVMP_HRdata_dynamics.csv" contains the dynamical parameters and clustering results of the HR sample in this paper. File "readme.txt" describes the meaning of each column in the table and the notes for the flag of stars.  This sample is obtained by the LAMOST/Subaru joint project. See our paper I (DOI: 10.3847/1538-4357/ac6515) for detailed descriptions of target selection and observations, paper II (DOI: 10.3847/1538-4357/ac6514) for the chemical abundance analysis, and paper III (DOI: 10.3847/1538-4357/ad31a6) for clustering and chemodynamical analysis. If you have any questions about this data, please contact lhn@nao.cas.cn or rz.richie.zhang@gmail.com for more information.

opencc-by-4.0Nov 2023View details →

Temporal dynamics of invertebrate community assembly in Lake Victoria since the Late Pleistocene based on chitinous remains

Preserved assemblages of invertebrate remains in lacustrine sediment reveal temporal variations of community composition and environmental conditions. However, records for large tropical lakes are scarce. Lake Victoria, the largest tropical lake, has a dynamic history of changes in water level, biogeochemistry, and fish community composition over the past ~17,000 cal yr BP. In order to quantify changes in the invertebrate assemblage of Lake Victoria from the Late Pleistocene throughout the Holocene, we examined chitinous remains of Cladocera and larval dipterans (Chironomidae and Chaoboridae) from a sediment core (37 m water depth) dated from ~13,700 cal yr BP to present. We identified four major phases in the invertebrate assemblage throughout this period of lake history. First, Chironomidae and Chaoboridae appeared at low abundances during the earliest stages of the lake inundation in the late Pleistocene, at a time when Cladocera were notably absent. Second, chaoborids and chironomids increased in abundance during the Mid Holocene, which coincided with high diatom production towards the end of the Holocene African Humid Period. Third, starting ~4,700 cal yr BP, Alona, a predominantly littoral cladoceran genus, consistently appeared in the invertebrate assemblage alongside changes in mixing regimes and persisted throughout the Late Holocene to present. Fourth, the arrival of both Chydorus and Bosmina longirostris marked the establishment of an abundant cladoceran assemblage at ~1,350 cal yr BP. The assemblage then gradually shifted toward the increasing dominance of B. longirostris, a planktonic cladoceran. This study provides the first multi-millennial record of sedimentary invertebrate assemblages in Lake Victoria, and elucidates some of the temporal development of these communities throughout most of the modern ecosystem's dynamic history. Overall, we provide novel insights into the temporal dynamics of invertebrate community assembly in relation to climatic and environmental variability in tropical lakes.

opencc-zeroMar 2024View details →

The impact of within-host coinfection interactions on between-host parasite transmission dynamics varies with spatial scale

Within-host interactions among coinfecting parasites can have major consequences for individual infection risk and disease severity. However, the impact of these within-host interactions on between-host parasite transmission, and the spatial scales over which they occur, remain unknown. We developed and applied a novel spatially explicit analysis to parasite infection data from a wild wood mouse (Apodemus sylvaticus) population. We previously demonstrated a strong within-host negative interaction between two wood mouse gastrointestinal parasites, the nematode Heligmosomoides polygyrus, and the coccidian Eimeria hungaryensis, using drug-treatment experiments. Here, we show this negative within-host interaction can significantly alter the between-host transmission dynamics of E. hungaryensis, but only within spatially-restricted neighbourhoods around each host. However, for the closely related species E. apionodes, which experiments show does not interact strongly with H. polygyrus, we did not find any effect on transmission over any spatial scale. Our results demonstrate that the effects of within-host coinfection interactions can ripple out beyond each host to alter the transmission dynamics of the parasites, but only over local scales that likely reflect the spatial dimension of transmission. Hence there may be knock-on consequences of drug treatments impacting the transmission of non-target parasites, altering infection risks even for non-treated individuals in the wider neighbourhood.

Figure 10 in Effect of three different land use types on the temporal dynamics of microarthropod abundance in the high Guinean savanna of Ngaoundéré (Adamawa, Cameroon)

Figure 10: PCA biplot of environmental parameters and abundance of microarthropods with month as grouping factor. sav ctrl: savanna; mb: maize bare; mbnpk: maize with chemical NPK fertilizer; mmdom: maize with dead organic matter.

Figure 9 in Effect of three different land use types on the temporal dynamics of microarthropod abundance in the high Guinean savanna of Ngaoundéré (Adamawa, Cameroon)

Figure 9. PCA biplot of environmental parameters and abundance of microarthropods with treatment as grouping factor. sav ctrl: savanna, mb: maize bare, mbnpk: maize with chemical NPK fertilizer, mmdom: maize with dead organic matter.

Figure 8 in Effect of three different land use types on the temporal dynamics of microarthropod abundance in the high Guinean savanna of Ngaoundéré (Adamawa, Cameroon)

Figure 8. Oribatida and Gamasina abundance (tsd. ind./m2) in plots (mb: maize bare, mmdom: maize with DOM). Abundances being significantly different from each other are marked by different letters for each microarthropod group (Wilcoxon signed rank test [p ˂ 0.05]). Error bars = standard error.

Figure 7 in Effect of three different land use types on the temporal dynamics of microarthropod abundance in the high Guinean savanna of Ngaoundéré (Adamawa, Cameroon)

Figure 7. Collembola, Oribatida and Gamasina abundance (tsd. ind./m2) in plots (mb: maize bare, mbnpk: maize with chemical NPK). Abundances being significantly different from each other are marked by different letters (Wilcoxon signed rank test [p ˂ 0.05]). Error bars = standard error.

Figure 6 in Effect of three different land use types on the temporal dynamics of microarthropod abundance in the high Guinean savanna of Ngaoundéré (Adamawa, Cameroon)

Figure 6. Effect of Maize cultivation on Collembola, Oribatida and Gamasina in control plots (sav ctrl: savanna, mb: maize bare). Abundances being significantly different from each other are marked by different letters for each microarthropod group (Wilcoxon signedrank test [p ˂ 0.05]). Error bars = standard error.

Figure 5 in Effect of three different land use types on the temporal dynamics of microarthropod abundance in the high Guinean savanna of Ngaoundéré (Adamawa, Cameroon)

Figure 5. Temporal variation of Collembola, Oribatida and Gamasina abundance (tsd. ind./m2) in savanna and experimental field in (A) 2017 and (B) 2018. Abundance being significantly different from each other in time per treatment are marked by different letters for each microarthropod group (Wilcoxon signed-rank test [p ˂ 0.05]). Months not sampled are marked by asterisks. Error bars = standard error. sav ctrl: savanna, mb: maize bare, mbnpk: maize with chemical NPK fertilizer, mmdom: maize with dry organic matter (DOM).

Figure 2 in Effect of three different land use types on the temporal dynamics of microarthropod abundance in the high Guinean savanna of Ngaoundéré (Adamawa, Cameroon)

Figure 2. Completely randomized block design of the experimental field; experimental field before sowing (A: 08/05/17) and with maize crop (B: 28/06/17); sav ctrl: savanna untreated (outside). mb(1): maize bare = maize plot without mulch or NPK fertilizer; mbnpk(2): maize bare with NPK = Maize plot treated with NPK fertilizer only and mmdom(3): maize mulch = maize plot treated with mulch only.

Figure 1 in Effect of three different land use types on the temporal dynamics of microarthropod abundance in the high Guinean savanna of Ngaoundéré (Adamawa, Cameroon)

Figure 1. Weather data for the Ngaoundéré area, Jan. to Dec. 2017 and 2018, provided by Ngaoundéré airport meteorological station; t: temperature, p: precipitation, h: relative humidity; h: averages per month; p: sum per month.

Figure 3 in Effect of three different land use types on the temporal dynamics of microarthropod abundance in the high Guinean savanna of Ngaoundéré (Adamawa, Cameroon)

Figure 3. Abundances (mean ± S.E.) of Acari and Collembola for the rainy seasons of 2017 (n = 4) and 2018 (n = 4) as well as for the dry season of 2017/18 (n = 2). n sampling campaigns with 9 samples per plot [sav ctrl: savanna; mb: maize bare; mbnpk: maize with chemical NPK fertilizer; mmdom: maize with dead organic matter (DOM)].

Figure 4 in Effect of three different land use types on the temporal dynamics of microarthropod abundance in the high Guinean savanna of Ngaoundéré (Adamawa, Cameroon)

Figure 4. Abundances (mean ± S.E.) of Oribatida and Gamasina for the rainy seasons of 2017 (n = 4) and 2018 (n = 4) as well as for the dry season of 2017/18 (n = 2). n sampling campaigns with 9 samples per plot [sav ctrl: savanna; mb: maize bare; mbnpk: maize with chemical NPK fertilizer; mmdom: maize with dead organic matter (DOM)].

Datapanel for Understanding Global Water Cooperation and Conflict Dynamics

The panel forms the baseline for analysis of water-related cooperation and conflict events worldwide between 1951-2019. When the scientific paper is published, a link and reference will be added here. The panel includes events per country-year, socioeconomic variables per country-year, and climatic variables per basin-year or country-year depending on availability. The data for demographic, economic, and climatic variables used in this study were sourced from various international databases (see table) and were here merged into a country-year panel (see figure). Water cooperation and conflict event records include the year, geographic location, and countries involved in conflict and cooperation (Kåresdotter et al., 2022b). The socio-economic variables include World Development Indicators (WDI), available from 1960 as yearly values per country. Precipitation data were obtained from outputs of the Water Balance Model (WBM) as modeled by Kåresdotter et al., (2022a), and extracted as yearly mean values per hydrological basin from HydroBASINS level 6 used for Aqueduct water risk indicators (Hofste et al., 2019; World Resources Institute, 2023, 2019). A baseline water stress was used for water stress, i.e., a long-term chronic water stress measure defined as the ratio of total water withdrawal to available renewable surface and groundwater supply (Hofste et al., 2019). Regional classifications are based on the United Nations Statistics Division geographic regions (UN Statistics Division, n.d.). The input datasets were consolidated to reflect basin-level values for conflicts and cooperation events, instead of using country-level mean values. Table 1. Summary of variables in the water cooperation and conflict panel <table> <tbody> <tr> <td> Variable </td> <td> Definition </td> <td> Unit </td> <td> Datasource </td> </tr> </tbody> <tbody> <tr> <td> Event type </td> <td> Type of water-related event (conflict, cooperation, both, no event) </td> <td> Categorical (0 or 1) </td> <td> Kåresdotter et al., (2022b) </td> </tr> <tr> <td> Population density </td> <td> Number of people per unit area </td> <td> People per square km </td> <td> WDI </td> </tr> <tr> <td> Export </td> <td> Export metrics of the country </td> <td> USD </td> <td> WDI </td> </tr> <tr> <td> GDP per capita </td> <td> Economic output per person </td> <td> USD per person </td> <td> WDI </td> </tr> <tr> <td> Rural population </td> <td> Proportion of population in rural areas </td> <td> Percentage </td> <td> WDI </td> </tr> <tr> <td> Precipitation </td> <td> Amount of rainfall or precipitation </td> <td> Millimeters </td> <td> Created for Kåresdotter et al., (2022a) </td> </tr> <tr> <td> Water stress </td> <td> Baseline water stress </td> <td> Categorical (0 to 5) </td> <td>  Aqueduct 3.0 (events up until 1984) and 4.0 </td> </tr> <tr> <td> Coordinates </td> <td> Latitude and longitude of event </td> <td> Degree </td> <td> Kåresdotter et al., (2022b) </td> </tr> <tr> <td> Region </td> <td> Geographic region of event(s) </td> <td> Region </td> <td> UN Statistics Division </td> </tr> <tr> <td> Event text </td> <td> Text describing the conflict or cooperation event </td> <td> Event text </td> <td> Kåresdotter et al., (2022b) </td> </tr> <tr> <td> Year </td> <td> Year of observation </td> <td> Year </td> <td>   </td> </tr> </tbody> </table>

Ecosystem Services Potential Dynamics of European Capital Metropolitan Areas

These are the Supplementary Dataset of the article "Ecosystem Services Potential is Declining across European Capital Metropolitan Areas". These results rely on the Urban Atlas (UA) data. In our study, we first used the UA data 2018 to compare all ECMA by their current ESP. While the UA change products enabled us to reveal the ESP dynamics across three different periods. Consequently, we could differentiate between metropolitan areas that have faced high rates of ESP reduction and ECMA that have slightly improved.  The data presented here include the following files: <ol> <li>UAch_12_18_ALL.gpkg: Includes all altered LULC patches within the European capital metropolitan areas.</li> <li>FINAL_corr_Table.xlsx: Is the cumulative table which feeds the correlation analysis between ESP and ESPD results to socio-economic and other variables.</li> <li>WB_Urban_Population_Growth_Europe.xlsx: Delivers the population change metrics based on World Bank data.</li> <li>ESPD__Experts_Matrix_Revision: Including the revision procedure of the expert matrox evaluation criteria.</li> <li>ESPD_1806_ALL_City_level:  Results of Ecosystem Services Potential Dynamics between 12 year period for 27 European metropolitan regions.</li> <li>ESPD_1812_ALL_City_level: Results of Ecosystem Services Potential Dynamics between 6 year period for 38 European metropolitan regions.</li> <li>ESPD_1812_ALL_Patch_level: Detailed table including all changed patches within 38 European metropolitan regions.</li> <li>ESPD_1812_UD_Pop_correlation: cumulative table incuding the urban expansion ratio and population growth, which feed our correlation analysis in our article.</li> </ol>

Local optima network metrics from the IEEE CEC 2024 paper "Information flow and Laplacian dynamics on local optima networks"

Local optima network metrics from the IEEE CEC 2024 paper "Information flow and Laplacian dynamics on local optima networks".  There are two CSV files: one for each of the two iterated local search confgurations used to construct the networks (low or high). In each file, a row contains information about one QAPLIB instance. Easch row contains all the metrics computed for the associated LON and also algorithm performance data on the instance.