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506 results for “decision-making”
Human Decision-Making Through the Lifecycle of Autonomous and Intelligent Systems in Defense Applications: Example Scenario with Comments
<p>This example scenario with comments has been created in conjunction with the report “A Framework for Human Decision-Making Through the Lifecycle of Autonomous and Intelligent Systems in Defense Applications” to be published by the IEEE Standards Association (IEEE SA) Research Group on Issues of AI and Autonomy in Defense Systems (the Research Group). It provides insights into the Research Group's working methods and process.</p>
Dataset for "Dissociable Roles of the mPFC-to-VTA pathway in the control od Impulsive action and Risk-Related Decision-Making in Roman High- and Low-Avoidance Rats"
<p>This dataset corresponds to the study "Dissociable Roles of the mPFC-to-VTA Pathway in the Control of Impulsive Action and Risk-Related Decision-Making in Roman High- and Low-Avoidance Rats". In this study, we used Positron Emission Tomography with [18F]-Fluorodeoxyglucose to evaluate brain metabolic activity in Roman High- (RHA) and Low-avoidance (RLA) rats, which exhibit innate differences in impulsivity. Notably, we used a viral-based intersectional chemogenetic strategy to isolate the role of the mPFC-to-VTA pathway in controlling impulsive behaviors. We selectively activated the mPFC-to-VTA pathway in RHA rats and inhibited it in RLA rats, assessing the effects on impulsive action and RDM in the rat gambling task. Our results showed that RHA rats displayed higher impulsive action, less optimal decision-making, and lower cortical activity than RLA rats at baseline. Chemogenetic activation of the mPFC-to-VTA pathway reduced impulsive action in RHA rats, whereas chemogenetic inhibition had the opposite effect in RLA rats. However, these manipulations did not affect RDM. Our findings suggest a dissociable role of the mPFC-to-VTA pathway in impulsive action and RDM, highlighting its potential as a target for investigating impulsivity-related disorders.</p> <p><strong>Contributions for usage of this data in publications:</strong></p> <p>If you publish any work using these data, please cite this repository and the associated publication.</p>
WaveMAP analysis of extracellular waveforms from monkey premotor cortex during decision-making
<p>Cortical circuits are thought to contain a large number of cell types that coordinate to produce behavior. Current <em>in vivo</em> methods rely on clustering of specified features of extracellular waveforms to identify putative cell types, but these capture only a small amount of variation. Here, we develop a new method (<em>WaveMAP</em>) that combines non-linear dimensionality reduction with graph clustering to identify putative cell types. We apply <em>WaveMAP</em> to extracellular waveforms recorded from dorsal premotor cortex of macaque monkeys performing a decision-making task. Using <em>WaveMAP</em>, we robustly establish eight waveform clusters and show that these clusters recapitulate previously identified narrow- and broad-spiking types while revealing previously unknown diversity within these subtypes. The eight clusters exhibited distinct laminar distributions, characteristic firing rate patterns, and decision-related dynamics. Such insights were weaker when using feature-based approaches. <em>WaveMAP</em> therefore provides a more nuanced understanding of the dynamics of cell types in cortical circuits.</p>
Visual processing and collective motion-related decision-making in desert locusts
<p>Collectively moving groups of animals rely on decision-making of locally interacting individuals in order to maintain swarm cohesion. However, the complex and noisy visual environment poses a major challenge to the extraction and processing of relevant information. We addressed this challenge by studying swarming-related decision-making in desert locust nymphs. Controlled visual stimuli, in the form of random dot kinematograms, were presented to tethered locust nymphs in a trackball setup, while monitoring movement trajectory and walking parameters. In a complementary set of experiments, the neurophysiological basis of the observed behavioral responses was explored. Our results suggest that locusts utilize filtering and discrimination upon encountering multiple stimuli simultaneously. Specifically, we show that locusts are sensitive to differences in speed at the individual conspecific level, and to movement coherence at the group level, and may use these to filter out non-relevant stimuli. The locusts also discriminate and assign different weights to different stimuli, with an observed interactive effect of stimulus size, relative abundance, and motion direction. Our findings provide insights into the cognitive abilities of locusts in the domain of decision-making and visual-based collective motion and support locusts as a model for investigating sensory-motor integration and motion-related decision-making in the intricate swarm environment.</p>
dhaw/fluCodeImperial: Using real-time data to guide decision-making during an influenza pandemic: a modelling analysis
<p><strong>All codes and data used for "Using real-time data to guide decision-making during an influenza pandemic: a modelling analysis" are included in this folder. The file "runExamples.m" contains a step-by-step method for reproducing figures and running model fits. Ensure that all data and code files are in the same directory, then a single execution of “runExamples” on the command line will generate all main and supplementary figures in the manuscript. There is one line of code per figure, clearly marked, that can be commented out as desired. In order to run the MCMC adaptive algorithm, a single line of code, also clearly marked, must be commented back in. Instructions to change the single-state example are given at the top of the file “runExamples.m”. The saved state selection of California (“state=1”) is consistent with all results presented in the manuscript. </strong></p> <p><strong> </strong></p> <p><strong>Plots make use of files from the following sources, with some modifications:</strong></p> <p><strong>Holger Hoffmann (2022). Violin Plot (https://www.mathworks.com/matlabcentral/fileexchange/45134-violin-plot);</strong></p> <p><strong>Evan (2022). Plot Groups of Stacked Bars (https://www.mathworks.com/matlabcentral/fileexchange/32884-plot-groups-of-stacked-bars);</strong></p> <p><strong>John Onofrey (2022). Shaded Plots and Statistical Distribution Visualizations (https://www.mathworks.com/matlabcentral/fileexchange/69203-shaded-plots-and-statistical-distribution-visualizations)</strong></p>
Real-time Alignments for Predicting Decision-Making Time for Diagnostics over NGS Cycles
<p>Input datasets for an interpretable learning approach to predict decision-making time for diagnostics over NGS cycles. The dataset contains alignment files of two clinical sputum samples sequenced with an Illumina MiSeq sequencing device, and following a real-time sequencing protocol.</p> <p>The datasets consist of real-time alignment files for specific sequencing cycle intervals. The alignment has been performed to a database of respiratory microbes. Data preprocessing, including the removal of human host DNA, is integrated into the real-time alignment approach that has been applied to generate the alignments.</p>
Information integration for decision-making in desert locusts
<p>Locust swarms can extend over hundred kilometers, and starvation compels this ancient pest to devour everything in its path. Theory suggests that gregarious behavior benefits foraging efficiency, yet the role of social cohesion remains elusive. To this end, we collected high-resolution trajectories of individual and grouped gregarious desert locusts in a 2-choice assay with patches of either similar or different quality. Carefully maintaining animals' identities allowed us to monitor each individual's experience and estimate the leaky accumulation process of personally-acquired and socially-derived evidence. We fitted data to a Bayesian model to gain insight into the decision-making system for patch selection. By disentangling the relative contribution of each information class, our study suggests that locusts balance incongruent evidence but reinforce congruent ones. We provide insight into the collective foraging decisions of social (but non-eusocial) insects and present locusts as a powerful empirical system to study individual choices and consequent collective dynamics.</p>
Dataset for Preferred and actual involvement of caregivers in oncologic treatment decision-making: A systematic review
<p>This dataset shows the search that was done for the publication Preferred and actual involvement of caregivers in oncologic treatment decision-making: A systematic review, which can be found at <a href="https://doi.org/10.1016/j.jgo.2023.101525">https://doi.org/10.1016/j.jgo.2023.101525</a>. </p>
Code and Datasets for "A simple mechanism for collective decision-making in the absence of payoff information"
<p>This repository contains R code and datasets used for analyses in the paper:</p> <p>"A simple mechanism for collective decision-making in the absence of payoff information"</p> <p>Published in <em>Proceedings of the National Academy of Sciences of the United States of America</em> (PNAS) in 2023</p> <p>by Daniele Carlesso, Justin M. McNab, Christopher J. Lustri, Simon Garnier, and Chris. R. Reid.</p> <pre><code>✓ Ensure that all files are in the same folder for the code to run properly. ✓ the repository also includes a summary HTML file for easier visualisation. </code></pre> <p>Datasets:</p> <pre><code>• chain_growth.csv • cumsum_df.csv • growth_data.csv • GrowthMP.csv • JL_chaingrowth.csv • joining_distance.csv • leave_10.csv • leaving_positions.csv • timespent.csv • traffic_mean.csv </code></pre> <p>Code:</p> <pre><code>• Code.Rmd </code></pre> <p>Markdown summary:</p> <pre><code>• Code.html </code></pre>
The essential-use concept: a valuable tool to guide decision-making on applications for authorisation under REACH?
<p>Supporting Information from The essential-use concept: a valuable tool to guide decision-making on applications for authorisation under REACH?</p>
A Culturally Sensitive Values-Guided Aid for End of Life Decision-Making
ClinicalTrials.gov study NCT00122135. IPD Sharing: Not stated. Countries: 1. Publications: 9.
Shared Decision-Making for Elderly Depressed Primary Care Patients
ClinicalTrials.gov study NCT01031134. IPD Sharing: NO. Countries: 1. Publications: 1.
Decision-Making in Labor Admission Using Transperineal Ultrasound vs. Vaginal Examination
ClinicalTrials.gov study NCT07278271. IPD Sharing: YES. Countries: 1. Publications: 1.
Promoting Resilience to Food Commercials Decreases Susceptibility to Unhealthy Food Decision-Making
ClinicalTrials.gov study NCT04905498. IPD Sharing: NO. Countries: 1. Publications: 1.
Patient-Centered Support for Contraceptive Decision-Making
ClinicalTrials.gov study NCT02078713. IPD Sharing: UNDECIDED. Countries: 1. Publications: 2.
Sharing Decision-making Program for HCC Patients Treatment Decisions
ClinicalTrials.gov study NCT03926039. IPD Sharing: NO. Countries: 1. Publications: 5.
Comparing Artificial Intelligence and Physicians: A Vignette-Based Study in Pediatric Clinical Decision-Making
ClinicalTrials.gov study NCT07179861. IPD Sharing: NO. Countries: 1. Publications: 5.
Increasing Patients' Engagement in Breast Cancer Surgery Decision-Making
ClinicalTrials.gov study NCT03766009. IPD Sharing: YES. Countries: 3. Publications: 4.
Shared Decision-Making for Colorectal Cancer Screening
ClinicalTrials.gov study NCT00251862. IPD Sharing: Not stated. Countries: 1. Publications: 5.
Conversational AI in Tactical Casualty Care: Baseline GPT-4o Improves Combat Medic Decision-Making
ClinicalTrials.gov study NCT06796036. IPD Sharing: NO. Countries: 1. Publications: 2.
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.