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Dataset results
19 results for “Human Decision Making”
Intraparietal stimulation disrupts negative distractor effects in human multi-alternative decision-making
<p>There has been debate about whether addition of an irrelevant distractor option to an otherwise binary decision influences which of the two choices is taken. We show that disparate views on this question are reconciled if distractors exert two opposing but not mutually exclusive effects. Each effect predominates in a different part of decision space: 1) a positive distractor effect predicts high-value distractors improve decision-making; 2) a negative distractor effect, of the type associated with divisive normalisation models, entails decreased accuracy with increased distractor values. Here, we demonstrate both distractor effects coexist in human decision making but in different parts of a decision space defined by the choice values. We show disruption of the medial intraparietal area (MIP) by transcranial magnetic stimulation (TMS) increases positive distractor effects at the expense of negative distractor effects. Furthermore, individuals with larger MIP volumes are also less susceptible to the disruption induced by TMS. These findings also demonstrate a causal link between MIP and the impact of distractors on decision-making via divisive normalisation.</p>
Decision-making in dynamic, continuously evolving environments: Quantifying the flexibility of human choice
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Intraparietal stimulation disrupts negative distractor effects in human multi-alternative decision-making
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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: Recruitment responses of shade-tolerant and heliophilous trees in human-degraded areas: the necessity of knowing the recruitment autecology of species for making reforestation decisions
<p>This repository contains the files associated with the following article:</p> <p>Johanna Croce, Ernesto I. Badano, Andrés Tálamo. Recruitment responses of shade-tolerant and heliophilous trees in human-degraded areas: the necessity of knowing the recruitment autecology of species for making reforestation decisions Submitted to <em>Land Degradation & Development</em>.</p> <p>The first Microsoft Excel file (Dataset 01 - Microclimate.xlsx) contains two sheets with the microclimatic data (average, maximum and minimum soil temperatures, and volumetric soil water content) measured in Cerro Chachapoyas and Cerro Fachacano. These measurements were performed on three plots of each trearment, including shrub-protected treatment with high shade, shrub-protected treatment with medium shade, sunny treatment with high herbaceous cover, sunny treatment with medium herbaceous cover and controls. The second Microsoft Excel file (Dataset 02 -Plant responses.xlsx Dataset 02 - Plant responses.xlsx) contains three sheets with the data used to estimate the seedling emergence rates, plant survival rates and net aboveground growth rates of the tree species, including <em>Anadenanthera colubrina</em> and <em>Ceiba chodatii</em> in Cerro Chachapoyas, and <em>Jacaranda mimosifolia</em> in Cerro Fachacano.</p>
Learn from Human-driving Accidents to Attack Autonomous Driving_Practical Traffic Flow Attacks on Decision-making
<p>We provide some demo videos of attack patterns</p>
Choice-dependent delta-band neural trajectory during semantic category decision making in the human brain
<p>The dataset and code provided correspond to Manuscript Number: ISCIENCE-D-23-09408R1, titled "Choice-dependent delta-band neural trajectory during semantic category decision making in the human brain."</p> <p>This dataset comprises delta and alpha filtered data from a total of 19 participants. Each .mat file contains 800 cells, representing the number of trials. Each cell contains a matrix of size 128 x 1750. Here, 128 denotes the number of EEG channels, and 1750 represents the number of time points. Time points are sampled from -1 s to 2.5 s relative to the onset of the first stimulus, with a 2ms interval.<br><br></p> <p>The participants' behavioral data are stored in separate .mat files for each run (or block). Upon loading these files, a struct named "data" is loaded, containing six variables, each representing a 1 x 200 vector:</p> <ol> <li> <p>Cat1: Represents the category of the first stimulus. It takes a value of 1 for animate words and 2 for inanimate words.</p> </li> <li> <p>Cat2: Denotes the category of the second stimulus. It is assigned 1 for animate words and 2 for inanimate words.</p> </li> <li> <p>Same: Indicates the correct response for each trial. A value of 1 signifies a match between the categories of Stimulus 1 and Stimulus 2, while 2 indicates a non-match.</p> </li> <li> <p>Resp: Records the participant's decision for each trial. A value of 1 denotes a match between the categories of Stimulus 1 and Stimulus 2, whereas 2 represents a non-match.</p> </li> <li> <p>RT: Represents the participant's response time in seconds for each trial.</p> </li> <li> <p>Corr: Indicates the correctness of the participant's response. A value of 1 signifies a correct response, while 0 indicates an incorrect response.</p> </li> </ol> <p> </p>
Data from: Wild ungulate decision-making and the role of tiny refuges in human-dominated landscapes
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Data from: Does fertility status influence impulsivity and risk taking in human females? Adaptive influences on intertemporal choice and risky decision making
Informed by the research on adaptive decision making in other animal species, this study investigated human females' intertemporal and risky choices across the ovulatory cycle. We tested the hypothesis that at peak fertility, women who are exposed to environments that signal availability of higher quality mates (by viewing images of attractive males), become more impulsive and risk-seeking in economic decision tasks. To test this, we collected intertemporal and risky choice measures before and after exposure to images of either attractive males or neutral landscapes both at peak and low fertility conditions. The results showed an interaction between women's fertility status and image type, such that women at peak fertility viewing images of attractive men chose the smaller, sooner monetary reward option less than women at peak fertility viewing neutral images. Neither fertility status nor image type influenced risky choice. Thus, though exposure to images of men altered intertemporal choices at peak fertility, this occurred in the opposite direction than predicted—i.e., women at peak fertility became less impulsive. Nevertheless, the results of the current study provide evidence for shifts in preferences over the ovulatory cycle and opens future research on economic decision making.
Data from: Does fertility status influence impulsivity and risk taking in human females? Adaptive influences on intertemporal choice and risky decision making
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Data from: Rate maximization and hyperbolic discounting in human experiential intertemporal decision making
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Data from: Evidence accumulation and choice maintenance are dissociated in human perceptual decision making
Perceptual decision making in monkeys relies on decision neurons, which accumulate evidence and maintain choices until a response is given. In humans, several brain regions have been proposed to accumulate evidence, but it is unknown if these regions also maintain choices. To test if accumulator regions in humans also maintain decisions we compared delayed and self-paced responses during a face/house discrimination decision making task. Computational modeling and fMRI results revealed dissociated processes of evidence accumulation and decision maintenance, with potential accumulator activations found in the dorsomedial prefrontal cortex, right inferior frontal gyrus and bilateral insula. Potential maintenance activation spanned the frontal pole, temporal gyri, precuneus and the lateral occipital and frontal orbital cortices. Results of a quantitative reverse inference meta-analysis performed to differentiate the functions associated with the identified regions did not narrow down potential accumulation regions, but suggested that response-maintenance might rely on a verbalization of the response.
The Computational and Neural Mechanisms Linking Decision-making and Memory in Humans
ClinicalTrials.gov study NCT06072378. IPD Sharing: YES. Countries: 1. Publications: 0.
Contribution of L-Tyrosine to Human Decision Making in Stressful Situations
ClinicalTrials.gov study NCT04518254. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
Data from: Human subthalamic nucleus activity during non-motor decision making
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Data from: Evidence accumulation and choice maintenance are dissociated in human perceptual decision making
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Dopaminergic modulation of the exploration/exploitation trade-off in human decision-making
<p>raw choice data of the four-armed bandit task</p> <p>1. fMRI study (31 participants, 3 drug conditions (placebo, L-dopa, haloperidol) )</p> <p>2. pilot study (16 participants)</p>
EEG-based approach for predicting varied human cognitive decision-making in driving
<p>These data are part of the data sample of the paper "EEG-based approach for predicting varied human cognitive decision-making in driving". For use by editors and reviewers. This includes one compressed files: 'RAW Data.zip'. 'RAW Data.zip' includes EEG Data and driving behavior data as well as code for extracting features and training individual models. A detailed description can be found in 'Read_Me.txt'. </p>
EEG-based approach for predicting varied human cognitive decision-making in driving
<p>These data are part of the data sample of the paper "EEG-based approach for predicting varied human cognitive decision-making in driving". For use by Nature Communications editors. This includes one compressed files: 'RAW Data.zip'. 'RAW Data.zip' includes EEG Data and driving behavior data as well as code for extracting features and training individual models. A detailed description can be found in 'Read_Me.txt'. </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.