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Psychopathology
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July 15, 2020
Moving beyond Ordinary Factor Analysis in Studies of Personality and Personality Disorder: A Computational Modeling Perspective
Nathaniel Haines, Theodore P Beauchaine
Biological Psychiatry. Cognitive Neuroscience and Neuroimaging
|
March 30, 2023
From Classical Methods to Generative Models: Tackling the Unreliability of Neuroscientific Measures in Mental Health Research
Nathaniel Haines, Holly Sullivan-Toole, Thomas Olino
Computational Psychiatry (Cambridge, Mass.)
|
March 31, 2018
Revealing Neurocomputational Mechanisms of Reinforcement Learning and Decision-Making With the hBayesDM Package
Woo-Young Ahn, Nathaniel Haines, Lei Zhang
Cognitive Science
|
October 6, 2018
The Outcome-Representation Learning Model: A Novel Reinforcement Learning Model of the Iowa Gambling Task
Nathaniel Haines, Jasmin Vassileva, Woo-Young Ahn
Cognitive, Affective & Behavioral Neuroscience
|
June 8, 2023
Explaining the description-experience gap in risky decision-making: learning and memory retention during experience as causal mechanisms
Nathaniel Haines, Peter D Kvam, Brandon M Turner
Computational Psychiatry (Cambridge, Mass.)
|
June 19, 2023
Enhancing the Psychometric Properties of the Iowa Gambling Task Using Full Generative Modeling
Holly Sullivan-Toole, Nathaniel Haines, Kristina Dale, et al.
Cognitive, Affective & Behavioral Neuroscience
|
July 30, 2025
Reward and punishment learning among people with a lifetime history of anxiety, depression, and substance use disorder
Jeremy M Haynes, Holly Sullivan-Toole, Nathaniel Haines, et al.
Cognitive, Affective & Behavioral Neuroscience
|
June 7, 2024
Test-retest reliability of the play-or-pass version of the Iowa Gambling Task
Jeremy M Haynes, Nathaniel Haines, Holly Sullivan-Toole, et al.
Drug and Alcohol Dependence
|
November 19, 2019
A computational model of the Cambridge gambling task with applications to substance use disorders
Ricardo J Romeu, Nathaniel Haines, Woo-Young Ahn, et al.
Plos One
|
February 6, 2019
Using computer-vision and machine learning to automate facial coding of positive and negative affect intensity
Nathaniel Haines, Matthew W Southward, Jennifer S Cheavens, et al.
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of 2
Search research articles
Search
Showing results (1-10 of 17) with videos related to
Sort By:
Page
of 2
Psychopathology
|
July 15, 2020
Moving beyond Ordinary Factor Analysis in Studies of Personality and Personality Disorder: A Computational Modeling Perspective
Nathaniel Haines, Theodore P Beauchaine
Biological Psychiatry. Cognitive Neuroscience and Neuroimaging
|
March 30, 2023
From Classical Methods to Generative Models: Tackling the Unreliability of Neuroscientific Measures in Mental Health Research
Nathaniel Haines, Holly Sullivan-Toole, Thomas Olino
Computational Psychiatry (Cambridge, Mass.)
|
March 31, 2018
Revealing Neurocomputational Mechanisms of Reinforcement Learning and Decision-Making With the hBayesDM Package
Woo-Young Ahn, Nathaniel Haines, Lei Zhang
Cognitive Science
|
October 6, 2018
The Outcome-Representation Learning Model: A Novel Reinforcement Learning Model of the Iowa Gambling Task
Nathaniel Haines, Jasmin Vassileva, Woo-Young Ahn
Cognitive, Affective & Behavioral Neuroscience
|
June 8, 2023
Explaining the description-experience gap in risky decision-making: learning and memory retention during experience as causal mechanisms
Nathaniel Haines, Peter D Kvam, Brandon M Turner
Computational Psychiatry (Cambridge, Mass.)
|
June 19, 2023
Enhancing the Psychometric Properties of the Iowa Gambling Task Using Full Generative Modeling
Holly Sullivan-Toole, Nathaniel Haines, Kristina Dale, et al.
Cognitive, Affective & Behavioral Neuroscience
|
July 30, 2025
Reward and punishment learning among people with a lifetime history of anxiety, depression, and substance use disorder
Jeremy M Haynes, Holly Sullivan-Toole, Nathaniel Haines, et al.
Cognitive, Affective & Behavioral Neuroscience
|
June 7, 2024
Test-retest reliability of the play-or-pass version of the Iowa Gambling Task
Jeremy M Haynes, Nathaniel Haines, Holly Sullivan-Toole, et al.
Drug and Alcohol Dependence
|
November 19, 2019
A computational model of the Cambridge gambling task with applications to substance use disorders
Ricardo J Romeu, Nathaniel Haines, Woo-Young Ahn, et al.
Plos One
|
February 6, 2019
Using computer-vision and machine learning to automate facial coding of positive and negative affect intensity
Nathaniel Haines, Matthew W Southward, Jennifer S Cheavens, et al.
Page
of 2