Article
Psychology, Mathematical
Brian C. Howatt, Michael E. Young
Summary: This study examined the effects of pairing sounds with outcomes in the BART and found that regardless of the outcome or valence, sounds did not affect risk-taking behavior in an adult, non-clinical sample.
BEHAVIOR RESEARCH METHODS
(2023)
Article
Psychology
Ran Zhou, Jay Myung, Mark A. Pitt
Summary: The STL model describes learning as adjustments to an individual's strategy in reaction to outcomes in the task, with the size of adjustments reflecting an individual's sensitivity to wins and losses. The model is sensitive to the learning elicited by experimental manipulations and matches or bests the performance of three competing models in traditional model comparison tests.
COGNITIVE PSYCHOLOGY
(2021)
Article
Psychology, Mathematical
Jeff Coon, Michael D. Lee
Summary: The Balloon Analogue Risk Task is widely used to measure risk propensity, but traditional measurement methods have limitations. A new method based on censoring is proposed in the study, which more accurately measures risk propensity and behavioral consistency.
BEHAVIOR RESEARCH METHODS
(2022)
Article
Biochemistry & Molecular Biology
E. L. Nurmi, C. P. Laughlin, H. de Wit, A. A. Palmer, J. MacKillop, T. D. Cannon, R. M. Bilder, E. Congdon, F. W. Sabb, L. C. Seaman, J. J. McElroy, M. R. Libowitz, J. Weafer, J. Gray, A. C. Dean, G. S. Hellemann, E. D. London
Summary: The study explores the genetic architecture of risky decision-making in psychiatric disorders and its correlation with cannabis use. The results indicate a polygenic nature of risky decision-making and its overlap with cannabis use.
MOLECULAR PSYCHIATRY
(2023)
Article
Psychology, Biological
Francisco Molins, Monica Paz, Liza Rozman, Nour Ben Hassen, Miguel Angel Serrano
Summary: Stress can alter decision-making, often promoting risk-taking and reward-seeking. However, our study found that participants exposed to stress during the Balloon Analogue Risk Task (BART) exhibited a pessimistic prior belief about balloon bursting likelihood and lower risk preference. This cautious attitude may be attributed to the alertness state induced by stress. However, it may also indicate maladaptive decision-making resulting from learning difficulties and altered feedback processing under stress.
PHYSIOLOGY & BEHAVIOR
(2022)
Article
Psychology, Biological
Sihua Xu
Summary: This study investigated the impact of self-other differences on outcome evaluation using ERP and BART paradigm. The results showed that negative outcome feedback elicited larger P300 when decisions were made for oneself, while no significant effect of self-other differences was observed for positive feedback. The FRN amplitude was found to be insensitive to self-other manipulation, but both components were modulated by the valence of the feedback.
INTERNATIONAL JOURNAL OF PSYCHOPHYSIOLOGY
(2021)
Article
Geriatrics & Gerontology
Adam T. Schulman, Amy W. Chong, Corinna E. Lockenhoff
Summary: This study expands previous research on age differences in risky decision making by examining the effects of framing. The findings indicate that older adults pump the virtual balloon more frequently and experience more popped balloons than younger adults in a loss frame, while no significant age differences were found in a gain frame. The overall performance on the Balloon Analogue Risk Task (BART) was not affected by age or frame.
JOURNALS OF GERONTOLOGY SERIES B-PSYCHOLOGICAL SCIENCES AND SOCIAL SCIENCES
(2022)
Article
Engineering, Industrial
Haoyuan Shen, Yizhong Ma, Chenglong Lin, Jian Zhou, Lijun Liu
Summary: This paper proposes a hierarchical Bayesian support vector regression (HBSVR) model for dynamic high-dimensional reliability modeling, which combines the step-size adaptive accelerated Markov Chain Monte Carlo (SAA-MCMC) method with Sequential Minimal Optimization (SMO) for parameter calibration and dynamic update. The HBSVR model is further improved by applying an active learning algorithm to continuously improve model accuracy.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2023)
Article
Multidisciplinary Sciences
Uijong Ju, Christian Wallraven
Summary: Researchers developed a virtual reality BART task to assess risk behavior and evaluated its usability by examining the relationships with psychological metrics. They found that BART scores were significantly correlated with sensation-seeking and risky driving behavior. Additionally, the high-score BART group exhibited higher sensation-seeking and more risky decision-making. Overall, the study demonstrates the potential of the virtual reality BART paradigm in predicting risky decision-making in the real world.
Article
Mathematics, Interdisciplinary Applications
Harhim Park, Jaeyeong Yang, Jasmin Vassileva, Woo-Young Ahn
Summary: A novel computational model, the EWMV model, was proposed to analyze choice behavior in the Balloon Analogue Risk Task (BART). The EWMV model showed superior performance in model comparison and parameter recovery. Additionally, the results suggest that heroin-dependent individuals exhibit reduced risk preference compared to other groups.
JOURNAL OF MATHEMATICAL PSYCHOLOGY
(2021)
Article
Computer Science, Software Engineering
Hannah Kim, Barry Drake, Alex Endert, Haesun Park
Summary: Human-in-the-loop topic modeling allows users to explore and steer the process to produce better quality topics. Integration of automated topic modeling algorithms into visual analytic systems with interactive parameters has limitations, but tight integration co-develops interactive algorithms and visual analytic systems for flexibility and scalability. Interactive hierarchical topic modeling offers fast, flexible, and algorithmically valid analysis for users to generate, explore, and steer hierarchical topics.
IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS
(2021)
Article
Psychology, Multidisciplinary
Simone Di Plinio, Mauro Pettorruso, Sjoerd J. H. Ebisch
Summary: This article discusses the issues in using the Balloon Analog Risk Task (BART) to assess risk-taking behavior and provides suggestions for optimizing the experimental design. It proposes a non-stochastic version of the BART that better approximates individuals' risk-taking profiles. The article emphasizes the importance of selecting optimal parameters for neuroscience experiments to acquire neuroimaging data.
FRONTIERS IN PSYCHOLOGY
(2022)
Article
Psychology, Clinical
Qinyu Liu, Runqing Zhong, Xinlei Ji, Samuel Law, Fan Xiao, Yiming Wei, Shulin Fang, Xinyuan Kong, Xiaocui Zhang, Shuqiao Yao, Xiang Wang
Summary: This study compared suicide attempters and non-suicide attempters with current MDD using psychometric assessments and computational modeling. The results revealed that suicide attempters were more likely to avoid psychological pain and loss, while there were no significant differences in decision-making biases between non-suicide attempters and healthy controls.
DEPRESSION AND ANXIETY
(2022)
Article
Engineering, Multidisciplinary
Xinyu Jia, Omid Sedehi, Costas Papadimitriou, Lambros S. Katafygiotis, Babak Moaveni
Summary: A new time-domain probabilistic technique based on hierarchical Bayesian modeling framework is proposed for calibration and uncertainty quantification of hysteretic type nonlinearities of dynamical systems. The technique introduces probabilistic hyper models for material hysteretic model parameters and prediction error variance parameters, considering both the uncertainty of the model parameters and the prediction error uncertainty. The technique employs a new asymptotic approximation to simplify the process of nonlinear model updating and reduce the computational burden. Numerical examples demonstrate the accuracy and performance of the proposed method.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(2022)
Article
Computer Science, Artificial Intelligence
Wentao Fan, Lin Yang, Nizar Bouguila
Summary: This paper proposes an unsupervised hierarchical nonparametric Bayesian framework for modeling axial data, introduces a closed-form optimization algorithm based on collapsed variational Bayes inference, and demonstrates the merits of the proposed models through experiments on gene expression data clustering and depth image analysis.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
(2022)
Article
Infectious Diseases
Arthur E. Attema, Lisheng He, Alasdair J. C. Cook, Victor J. Del Rio Vilas
PLOS NEGLECTED TROPICAL DISEASES
(2019)
Article
Psychology
Lisheng He, Wenjia Joyce Zhao, Sudeep Bhatia
Summary: Decision models are essential tools in studying choice behavior, but there is little consensus about the best model for describing choice. This study presents a computational analysis using landscaping techniques to generate a representational structure for decision models, measuring the properties of individual models and quantifying relationships between different models. The results show how decades of research on human choice behavior can be synthesized within a single framework.
PSYCHOLOGICAL REVIEW
(2022)
Article
Management
Lisheng He, Pantelis P. Analytis, Sudeep Bhatia
Summary: This study conducted a large-scale comparison of 58 prominent models of risky choice, revealing that crowds of risky choice models perform better than individual models and provide a performance bound for assessing the historical accumulation of knowledge in the field. The results suggest that each model captures unique aspects of the decision process, and existing models offer complementary rather than competing accounts of behavior.
MANAGEMENT SCIENCE
(2022)
Editorial Material
Multidisciplinary Sciences
Sudeep Bhatia, Lisheng He
Article
Neurosciences
Xiaocui Zhang, Xiang Wang, Daifeng Dong, Xiaoqiang Sun, Xue Zhong, Ge Xiong, Chang Cheng, Hui Lei, Ya Chai, Meichen Yu, Peng Quan, Philip R. Gehrman, John A. Detre, Shuqiao Yao, Hengyi Rao
Summary: This study investigated the neural responses to negative outcomes in patients with current and remitted major depressive disorder (MDD). The results showed that patients with current MDD exhibited hyper-responses in several limbic regions to loss outcomes, while patients with remitted MDD showed persistent hyperactivity in the ventral anterior cingulate cortex (vACC).
BIOLOGICAL PSYCHIATRY
(2023)
Article
Psychology, Multidisciplinary
Hongyi Wang, Jiaxin Ma, Lisheng He
Summary: It is widely believed that people rely on incomplete information and use non-compensatory choice rules when selecting a partner. However, recent experiments have shown that people actually use compensatory choice strategies. To bridge the gap between theory and experimental evidence, we characterized the mate choice problem by distinguishing the information search process from the evaluation process. In eye-tracking and MouseLab experiments, we found that people display strong value-directed search heuristics for all types of cues, and the magnitude of these searches increases with cue primacy.
JUDGMENT AND DECISION MAKING
(2022)
Article
Psychology
Lisheng He, Daniel Wall, Crystal Reeck, Sudeep Bhatia
Summary: This study examines the link between intertemporal decision models and information processing in decision making. The results indicate that the parameters of an attention model can predict which intertemporal choice model corresponds to a participant's choices.
COGNITIVE PSYCHOLOGY
(2023)
Article
Multidisciplinary Sciences
Ya Chai, Philip Gehrman, Meichen Yu, Tianxin Mao, Yao Deng, Joy Rao, Hui Shi, Peng Quan, Jing Xu, Xiaocui Zhang, Hui Lei, Zhuo Fang, Sihua Xu, Elaine Boland, Jennifer R. Goldschmied, Holly Barilla, Namni Goel, Mathias Basner, Michael E. Thase, Yvette I. Sheline, David F. Dinges, John A. Detre, Xiaochu Zhang, Hengyi Rao
Summary: Sleep loss can disrupt mood regulation in healthy individuals but may have an antidepressant effect for some depressed patients. This study found that the amygdala and the dorsal nexus play important roles in mood regulation, and the connectivity between the amygdala and the anterior cingulate cortex is associated with mood changes after sleep deprivation.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2023)
Article
Biology
Lisheng He, Sudeep Bhatia
Summary: Neurocognitive theories of value-based choice fail to explain complex multiplicative preferences. This research proposes an interactive attention mechanism where attention to attributes depends on previously attended attributes. Eye-tracking and mouse-tracking data tests show that interactive attention is necessary for making good choices, and incorporating it into accumulation-based decision models improves their predictions. By introducing sophisticated attentional dynamics, this study extends existing decision models to describe complex economic choices and unifies two prominent theoretical approaches.
PROCEEDINGS OF THE ROYAL SOCIETY B-BIOLOGICAL SCIENCES
(2023)
Article
Psychology, Multidisciplinary
Qingji Zhang, Jinglin Lu, Peng Quan
Summary: The study validates the applicability of the dual-factor model of mental health among new generation migrant workers in China. Results show that the model has better construct validity and can separate workers into four subgroups, highlighting the importance of positive mental health and psychopathology in their mental well-being.
Article
Psychology, Multidisciplinary
Hongyi Wang, Zhilin He, Lisheng He
Summary: This study conducted an experimental test on the transitivity in human mate preferences, finding that transitive models provided better accounts in Bayesian model selection and strong stochastic transitivity. SST model outperformed other transitive models in explaining mate preferences.
DECISION-WASHINGTON
(2021)
Article
Psychology, Experimental
Sudeep Bhatia, Lisheng He, Wenjia Joyce Zhao, Pantelis P. Analytis
Summary: The study highlights that decision makers often use threshold decision rules during sequential search tasks, but the observed stopping thresholds are typically lower than optimal thresholds. The research finds that decision maker behavior can be explained as maximizing stochastic risk averse utility while considering risk aversion, psychological effort cost, and decision errors.
Meeting Abstract
Clinical Neurology
P. Quan, H. Lei, J. Wang, W. Liu, X. Zhang, D. Dinges, H. Rao
Article
Neurosciences
Jose Sanchez-Bornot, Roberto C. Sotero, J. A. Scott Kelso, Ozguer Simsek, Damien Coyle
Summary: This study proposes a multi-penalized state-space model for analyzing unobserved dynamics, using a data-driven regularization method. Novel algorithms are developed to solve the model, and a cross-validation method is introduced to evaluate regularization parameters. The effectiveness of this method is validated through simulations and real data analysis, enabling a more accurate exploration of cognitive brain functions.
