Find research datasets worth reusing

opencc-by-4.0Sep 2024View details →

Eletronic Companion - A Novel MILP Formulation for Optimal Allocation and Coordination of Protective and Switching Devices in Active Distribution Networks

This release is associated with a paper entitled "A Novel MILP Formulation for Optimal Allocation and Coordination of Protective and Switching Devices in Active Distribution Networks". The attached document provides the data adopted to obtain the results presented in the paper.

opencc-zeroMay 2020View details →

Data from: Recurrent circuit dynamics underlie persistent activity in the macaque frontoparietal network

During delayed oculomotor response tasks, neurons in the lateral intraparietal area (LIP) and the frontal eye fields (FEF) exhibit persistent activity that reflects the active maintenance of behaviorally relevant information. Despite many computational models of the mechanisms of persistent activity, there is a lack of circuit-level data from the primate to inform the theories. To fill this gap, we simultaneously recorded ensembles of neurons in both LIP and FEF while macaques performed a memory-guided saccade task. A population encoding model revealed strong and symmetric long-timescale recurrent excitation between LIP and FEF. Unexpectedly, LIP exhibited stronger local functional connectivity than FEF, and many neurons in LIP had longer network and intrinsic timescales. The differences in connectivity could be explained by the strength of recurrent dynamics in attractor networks. These findings reveal reciprocal multi-area circuit dynamics in the frontoparietal network during persistent activity and lay the groundwork for quantitative comparisons to theoretical models.

opencc-zeroAug 2021View details →

Data from: Ongoing habenular activity is driven by forebrain networks and modulated by olfactory stimuli

The data was collected using volumetric two-photon calcium imaging of the forebrain and habenula of juvenile zebrafish expressing a transgenic calcium indicator. The data provided is organized according to the figures of our manuscript and contains the necessary codes and data to replicate the figures presented. In short, included repository contains 6 datasets of experiments. Data structure includes neuronal data as normalised to the baseline fluorescence for each neuron over time (DF/F), 2 or 3 dimensional coordinates of each cell and information about duration and samplings rate of experiments, and appropriate information about stimulation either microstimulation or odor stimulation (if any was performed within the experiment).

opencc-by-4.0Oct 2018View details →

Characterization of deep neural network features by decodability from human brain activity

We present a dataset derived through the DNN feature decoding analyses (<a href="https://www.nature.com/articles/ncomms15037">Horikawa and Kamitani, 2017</a>), including true and decoded feature values of DNNs (AlexNet and VGG19) and decoding accuracies of individual DNN features with their rankings. The decoding accuracies of individual DNN features were highly correlated across subjects, suggesting the systematic differences between the brain and DNNs. The unpreprocessed fMRI data is available from the OpenNeuro (<a href="https://openneuro.org/datasets/ds001246">https://openneuro.org/datasets/ds001246</a>). We hope the present dataset will contribute to reveal the gap between the brain and DNNs and provide an opportunity to make use of the decoded features for further applications.

opencc-by-4.0Aug 2023View details →

Data for "Using Convolutional Neural Network to Emulate Seasonal Tropical Cyclone Activity"

The trained 600-member ensemble convolutional neural networks (CNNs) for seasonal tropical cyclone (TC) activity to allow future studies. Please refer Fu et al. (2023; Using Convolutional Neural Network to Emulate Seasonal Tropical Cyclone Activity) for more details.

opencc-zeroSep 2023View details →

Posterior default mode network activity underlies distracted interoceptive attention and provides an objective basis for low mindfulness and depression

Interoceptive attention to internal sensory signals is fundamental to mindfulness. However, it is difficult to measure objectively, and the vast majority of investigations of the neural correlates of mindfulness-based attention rely on subjective and retrospective measures of distraction. In this study, we measured consistency of response times on a breath-monitoring task (instruction to respond every 2 breath cycles) to objectively measure interoceptive attention in individuals across the lifespan (15–91 years of age, n=324). Consistently timed responses were indicative of on-task attention, whereas variable delayed responses indicated distraction or mind-wandering. Signifying the importance of interoceptive attention consistency, we observed that this measure was positively correlated across subjects with performance across several exteroceptive cognitive tasks. Electroencephalographic (EEG) source reconstruction demonstrated that distraction on the eyes-closed task was associated with elevated alpha band (8–12 Hz) brain activity, particularly in posterior default mode network (pDMN) brain regions. The neural data revealed four important findings: 1) pDMN brain activity was inversely linked with functional connectivity to the fronto-parietal network (FPN), suggesting that pDMN-FPN interactions play a key role in the regulation of pDMN activity during interoceptive attention. 2) pDMN activity on distracted trials was inversely correlated with trait-level mindfulness. 3) A key hub of the pDMN, the isthmus region of the posterior cingulate cortex (ICC), showed elevated activity on distracted trials in individuals with self-reported depressive symptoms. 4) In an independent second experiment, pDMN activity was adaptively modulated by task difficulty that invoked different levels of distraction. These results identify an EEG-based neurophysiological marker (elevated pDMN alpha activity) underlying interoceptive distraction, which is correlated with subjective markers of mindfulness and depression and that can be adaptively modulated. Our findings, thus, provide a direct link between a neurophysiological substrate of interoceptive attention, and subjective ratings of mindfulness and depressed mood.

opencc-by-4.0Dec 2023View details →

Detecting Transient Deformation at the Active Volcano Ol Doinyo Lengai in Tanzania with the TZVOLCANO Network: Supplementary software, data, model files

These are supplementary data, code, and model files associated with the manuscript "Detecting Transient Deformation at the Active Volcano Ol Doinyo Lengai in Tanzania with the TZVOLCANO Network" in consideration for publication in the Geophysical Research Letters. tzvolcano_code_and_models.zip contains all necessary Targeted Projection Operator (TPO) software, input, and output files for the GNSS inversions presented in our manuscript necessary to reproduce the results. The TPO program is a Unix/Linux code developed by Kang-Hyeun Ji working at the Korea Institute for Geoscience and Mineral Resources, Daejeon, South Korea. The source code is available in the supplementary Zenodo repository. We also include input and output model files for the USGS code dMODELS for reproducibility. Please see the README.txt file for more details. This study was funded by the US National Science Foundation grant number EAR-1943681 to Virginia Tech, internal university funds via Ardhi University, and Ministry of Science and ICT of Korea Basic Research Project GP2021-006 to the Korea Institute of Geosciences and Mineral Resources. We acknowledge and thank the EarthScope Consortium for archiving and making TZVOLCANO GNSS datasets freely available, supported by the National Science Foundation’s Seismological Facility for the Advancement of Geoscience (SAGE) Award under Cooperative Support Agreement EAR-1851048 and Geodetic Facility for the Advancement of Geoscience (GAGE) Award under NSF Cooperative Agreement EAR-1724794.

controlledIPD-YESFeb 2026View details →

Brain Network Activation and Gait and Posture in FXTAS

ClinicalTrials.gov study NCT02936531. IPD Sharing: YES. Countries: 1. Publications: 14.

Brain Network Activation in Patients With Movement Disorders

ClinicalTrials.gov study NCT03269201. IPD Sharing: Not stated. Countries: 1. Publications: 5.

Testing the Efficacy of an Online Social Network Intervention to Increase Social Support for Physical Activity

ClinicalTrials.gov study NCT01421758. IPD Sharing: Not stated. Countries: 1. Publications: 1.

Healthy Eating & Active Living for Diabetes in Primary Care Networks

ClinicalTrials.gov study NCT00991380. IPD Sharing: Not stated. Countries: 1. Publications: 3.

A Person-Centered Geotagged Social Networking System to Promote Physical Activity in the Community

ClinicalTrials.gov study NCT05216393. IPD Sharing: UNDECIDED. Countries: 1. Publications: 6.

National Active Surveillance Network and Pharmacogenomics of Adverse Drug Reactions in Children

ClinicalTrials.gov study NCT00414115. IPD Sharing: Not stated. Countries: 1. Publications: 2.

closedIPD-NOFeb 2026View details →

Altering Default Mode Network Activity With Transcranial Focused Ultrasound to Reduce Depressive Symptoms

ClinicalTrials.gov study NCT06320028. IPD Sharing: NO. Countries: 1. Publications: 6.