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Showing results 1 to 53 of 53

Issue DateTitle / Author(s) / CitationFileAltmetrics
2008
Comparison of Decision Learning Models Using the Generalization Criterion Method

Ahn, Woo-Young; Busemeyer, Jerome R.; Wagenmakers, Eric-Jan; Stout, Julie C.

Cognitive Science, Vol.32 No.8, pp.1376-1402

DOI
2009-11
Steady State Responses: Electrophysiological Assessment of Sensory Function in Schizophrenia
DOI
2010-02
Cognitive mechanisms underlying risky decision-making in chronic cannabis users
DOI
2011
A Model-Based fMRI Analysis With Hierarchical Bayesian Parameter Estimation

Ahn, Woo-Young; Krawitz, Adam; Kim, Woojae; Busemeyer, Jerome R.; Brown, Joshua W.

Journal of Neuroscience, Psychology, and Economics, Vol.4 No.2, pp.95-110

DOI
2011-04
Propensity for risk taking and trait impulsivity in the Iowa Gambling Task

Upton, Daniel J.; Bishara, Anthony J.; Ahn, Woo-Young; Stout, Julie C.

Personality and Individual Differences, Vol.50 No.4, pp.492-495

DOI
2011-11
Temporal Discounting of Rewards in Patients With Bipolar Disorder and Schizophrenia
DOI
2012
Emotion-Based Reinforcement Learning

Ahn, Woo-Young; Rass, Olga; Shin, Yong-Wook; Busemeyer, Jerome R.; Brown, Joshua W.; O’Donnell, Brian F.

Building Bridges Across Cognitive Sciences Around the World - Proceedings of the 34th Annual Meeting of the Cognitive Science Society, CogSci 2012, pp.78-83

2013-08
Computational Modeling Reveals Distinct Effects of HIV and History of Drug Use on Decision-Making Processes in Women
DOI
2014
To simulate or not? Comment on steingroever, Wetzels, and Wagenmakers (2014)
DOI
2014-03
Differential Impairments Underlying Decision Making in Anorexia Nervosa and Bulimia Nervosa: A Cognitive Modeling Analysis
DOI
2014-08
Decision-making in stimulant and opiate addicts in protracted abstinence: evidence from computational modeling with pure users
DOI
2014-11
Nonpolitical Images Evoke Neural Predictors of Political Ideology
DOI
2016-01
Resting-state EEG, impulsiveness, and personality in daily and nondaily smokers

Rass, Olga; Ahn, Woo-Young; O'Donnell, Brian F.

Clinical Neurophysiology, Vol.127 No.1, pp.409-418

DOI
2016-01
Computational modeling for addiction medicine: From cognitive models to clinical applications

Ahn, Woo Young; Dai, Junyi; Vassileva, Jasmin; Busemeyer, Jerome R.; Stout, Julie C.

Progress in Brain Research, Vol.224, pp.53-65

DOI
2016-03
Utility of Machine-learning approaches to identify Behavioral Markers for substance Use Disorders: impulsivity Dimensions as Predictors of current cocaine Dependence

Ahn, Woo-Young; Ramesh, Divya; Moeller, Frederick Gerard; Vassileva, Jasmin

Frontiers in Psychiatry, Vol.7 No.MAR, p. 34

DOI
2016-04
Machine-learning identifies substance-specific behavioral markers for opiate and stimulant dependence

Ahn, Woo-Young; Vassileva, Jasmin

Drug and Alcohol Dependence, Vol.161, pp.247-257

DOI
2016-10
Challenges and promises for translating computational tools into clinical practice

Ahn, Woo-Young; Busemeyer, Jerome R.

Current Opinion in Behavioral Sciences, Vol.11, pp.1-7

DOI
2017-03
Predicting the knowledge-recklessness distinction in the human brain

Vilaresa, Iris; Wesley, Michael J.; Ahn, Woo-Young; Bonnie, Richard J.; Hoffman, Morris; Jones, Owen D.; Morse, Stephen J.; Yaffe, Gideon; Lohrenz, Terry; Montague, P. Read

Proceedings of the National Academy of Sciences of the United States of America, Vol.114 No.12, pp.3222-3227

DOI
2017-10
The indirect effect of emotion regulation on minority stress and problematic substance use in lesbian, gay, and bisexual individuals
DOI
2018-07
Selective effects of the loss of NMDA or mGluR5 receptors in the reward system on adaptive decision-making
DOI
2018-11
Combined genetic influence of the nicotinic receptor gene cluster CHRNA5/A3/B4 on nicotine dependence

Lee, Sung-Ha; Ahn, Woo-Young; Seweryn, Micha; Sadee, Wolfgang

BMC Genomics, Vol.19 No.1, p. 826

DOI
2018-11
The outcome‐representation learning model: a novel reinforcement learning model of the iowa gambling task

Haines, Nathaniel; Vassileva, Jasmin; Ahn, Woo-Young

Cognitive Science, Vol.42 No.8, pp.2534-2561

DOI
2019
Optimizing the Design of an Experiment using the ADOpy Package: An Introduction and Tutorial

Myung, Jay I.; Pitt, Mark A.; Yang, Jaeyeong; Ahn, Woo-Young

Proceedings of the 41st Annual Meeting of the Cognitive Science Society: Creativity + Cognition + Computation, CogSci 2019, pp.19-20

2019-02
Using computer-vision and machine learning to automate facial coding of positive and negative affect intensity
DOI
2019-09
Identifying Children With Clinical Language Disorder: An Application of Machine-Learning Classification

Justice, Laura M.; Ahn, Woo-Young; Logan, Jessica A. R.

Journal of Learning Disabilities, Vol.52 No.5, pp.351-365

DOI
2019-10
Altered learning under uncertainty in unmedicated mood and anxiety disorders
DOI
2019-10
Delay Discounting of Protected Sex: Relationship Type and Sexual Orientation Influence Sexual Risk Behavior
DOI
2020-01
Attitudes Toward Gay Men and Lesbian Women Moderate Heterosexual Adults' Subjective Stress Response to Witnessing Homonegativity

Hahn, Hunter; van Dyk, Ilana Seager; Ahn, Woo-Young

Frontiers in Psychology, Vol.10, p. 2948

DOI
2020-01
A computational model of the Cambridge gambling task with applications to substance use disorders
DOI
2020-03
Estimating quality of life with biomarkers among older Korean adults: A machine-learning approach

Lee, Sung-Ha; Choi, Incheol; Ahn, Woo-Young; Shin, Enyoung; Cho, Sung-Il; Kim, Sunyoung; Oh, Bumjo

Archives of Gerontology and Geriatrics, Vol.87, p. 103966

DOI
2020-07
Rapid, precise, and reliable measurement of delay discounting using a Bayesian learning algorithm
DOI
2020-11
Anxiety Modulates Preference for Immediate Rewards Among Trait-Impulsive Individuals: A Hierarchical Bayesian Analysis
DOI
2020-11
Post–COVID-19 한국임상심리학회 발전 로드맵

서수연; 이영준; 이주영; 한영경; 허지원; 어유경; 김석웅; 안우영; 이원혜; 진주희; 천정현; 최승원; 송현주

Korean Journal of Clinical Psychology, Vol.39 No.4, pp.396-429

DOI
2021-04
ADOpy: a python package for adaptive design optimization

Yang, Jaeyeong; Pitt, Mark A.; Ahn, Woo-Young; Myung, Jay I.

Behavior Research Methods & Instrumentation, Vol.53 No.2, pp.874-897

DOI
2021-06
Machine Learning Analysis to Identify Digital Behavioral Phenotypes for Engagement and Health Outcome Efficacy of an mHealth Intervention for Obesity: Randomized Controlled Trial

Kim, Meelim; Yang, Jaeyeong; Ahn, Woo-Young; Choi, Hyung Jin

Journal of Medical Internet Research, Vol.23 No.6

DOI
2021-06
Development of a novel computational model for the Balloon Analogue Risk Task: The exponential-weight mean-variance model

Park, Harhim; Yang, Jaeyeong; Vassileva, Jasmin; Ahn, Woo-Young

Journal of Mathematical Psychology, Vol.102, p. 102532

DOI
2022-01
Identifying Prepubertal Children with Risk for Suicide Using Deep Neural Network Trained on Multimodal Brain Imaging

Ahn, Gun; Kim, Bogyeom; Kim, Ka-kyeong; Kim, Hyeonjin; Lee, Eunji; Ahn, Woo-Young; Kim, Jae-Won; Cha, Jiook

Studies in Computational Intelligence, Vol.1013, pp.75-86

DOI
2022-02
Association of Genome-Wide Polygenic Scores for Multiple Psychiatric and Common Traits in Preadolescent Youths at Risk of Suicide
DOI
2022-04
A Randomized, Double-Blind, Sham-Controlled Trial of Transcranial Direct Current Stimulation for the Treatment of Persistent Postural-Perceptual Dizziness (PPPD)
DOI
2022-08
The sexual brain, genes, and cognition: A machine-predicted brain sex score explains individual differences in cognitive intelligence and genetic influence in young children
DOI
2022-11
Psychological treatments for excessive gaming: a systematic review and meta-analysis
DOI
2023-03
Coordinated anatomical and functional variability in the human brain during adolescence
DOI
2023-05
Psychological well-being and salivary markers of inflammation: The moderating effect of age
DOI
2023-05
Utility of Computational Approaches for Precision Psychiatry: Applications to Substance Use Disorders
DOI
2023-06
Causal role of the dorsolateral prefrontal cortex in modulating the balance between Pavlovian and instrumental systems in the punishment domain
DOI
2023-07
Biopsychosocial factors of gaming disorder: a systematic review employing screening tools with well-defined psychometric properties
DOI
2023-08
Adaptive Design Optimization as a Promising Tool for Reliable and Efficient Computational Fingerprinting

Kwon, Mina; Lee, Sang Ho; Ahn, Woo-Young

Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, Vol.8 No.8, pp.1-804

DOI
2023-12
The neurocognitive role of working memory load when Pavlovian motivational control affects instrumental learning

Park, Heesun; Doh, Hoyoung; Lee, Eunhwi; Park, Harhim; Ahn, Woo-Young

PLoS Computational Biology, Vol.19 No.12, p. 1011692

DOI
2024
Neural correlates of model-based behavior in internet gaming disorder and alcohol use disorder

Kwon, Mina; Choi, Hangnyoung; Park, Harhim; Ahn, Woo-Young; Jung, Young-Chul

Journal of behavioral addictions, Vol.13 No.1, pp.236-249

DOI
2024-01
Caffeinated Soda Intake in Children Is Associated with Neurobehavioral Risk Factors for Substance Misuse
DOI
2024-02
Acute Stress Enhances Memory and Preference for Smoking-Related Associations in Smokers

Lee, Jeung-Hyun; Kang, Sanghoon; Maier, Silvia U.; Lee, Sang Ah; Goldfarb, Elizabeth V.; Ahn, Woo-Young

Nicotine and Tobacco Research, Vol.26 No.3, pp.333-341

DOI
2024-04
Bridging the Gap Between Self-Report and Behavioral Laboratory Measures: A Real-Time Driving Task With Inverse Reinforcement Learning

Lee, Sang Ho; Song, Myeong Seop; Oh, Min-hwan; Ahn, Woo-Young

Psychological Science, Vol.35 No.4, pp.35-4

DOI
2024-04
Multimodal-based machine learning approach to classify features of internet gaming disorder and alcohol use disorder: A sensor-level and source-level resting-state electroencephalography activity and neuropsychological study
DOI
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