Follow
Nathaniel Haines
Nathaniel Haines
Computational Psychologist
Verified email at osu.edu - Homepage
Title
Cited by
Cited by
Year
Revealing neurocomputational mechanisms of reinforcement learning and decision-making with the hBayesDM package
WY Ahn, N Haines, L Zhang
Computational Psychiatry (Cambridge, Mass.) 1, 24, 2017
3072017
Theoretically Informed Generative Models Can Advance the Psychological and Brain Sciences: Lessons from the Reliability Paradox
N Haines, PD Kvam, LH Irving, C Smith, TP Beauchaine, MA Pitt, WY Ahn, ...
PsyArXiv. https://doi. org/10.31234/osf. io/xr7y3, 2020
119*2020
The outcome‐representation learning model: A novel reinforcement learning model of the iowa gambling task
N Haines, J Vassileva, WY Ahn
Cognitive science 42 (8), 2534-2561, 2018
632018
The indirect effect of emotion regulation on minority stress and problematic substance use in lesbian, gay, and bisexual individuals
AH Rogers, I Seager, N Haines, H Hahn, A Aldao, WY Ahn
Frontiers in Psychology 8, 302224, 2017
462017
Rapid, precise, and reliable measurement of delay discounting using a Bayesian learning algorithm
WY Ahn, H Gu, Y Shen, N Haines, HA Hahn, JE Teater, JI Myung, MA Pitt
Scientific reports 10 (1), 12091, 2020
382020
Using computer-vision and machine learning to automate facial coding of positive and negative affect intensity
N Haines, MW Southward, JS Cheavens, T Beauchaine, WY Ahn
PLoS One 14 (2), e0211735, 2019
382019
A computational model of the Cambridge gambling task with applications to substance use disorders
RJ Romeu, N Haines, WY Ahn, JR Busemeyer, J Vassileva
Drug and alcohol dependence 206, 107711, 2020
372020
Delay discounting of protected sex: Relationship type and sexual orientation influence sexual risk behavior
H Hahn, S Kalnitsky, N Haines, S Thamotharan, TP Beauchaine, WY Ahn
Archives of sexual behavior 48, 2089-2102, 2019
25*2019
Anxiety modulates preference for immediate rewards among trait-impulsive individuals: A hierarchical Bayesian analysis
N Haines, TP Beauchaine, M Galdo, AH Rogers, H Hahn, MA Pitt, ...
Clinical Psychological Science 8 (6), 1017-1036, 2020
202020
Learning from the reliability paradox: how theoretically informed generative models can advance the social
N Haines, PD Kvam, LH Irving, C Smith, TP Beauchaine, MA Pitt, WY Ahn, ...
Behavioral, and Brain Sciences, 2020
202020
Functionalist CHAPTER 1 and Constructionist Perspectives on Emotion Dysregulation
TP Beauchaine, N Haines
The Oxford handbook of emotion dysregulation, 1, 2020
182020
Using automated computer vision and machine learning to code facial expressions of affect and arousal: Implications for emotion dysregulation research
N Haines, Z Bell, S Crowell, H Hahn, D Kamara, H McDonough-Caplan, ...
Development and psychopathology 31 (3), 871-886, 2019
182019
Future directions for cognitive neuroscience in psychiatry: Recommendations for biomarker design based on recent test re-test reliability work
RJR Blair, A Mathur, N Haines, S Bajaj
Current Opinion in Behavioral Sciences 44, 101102, 2022
152022
From classical methods to generative models: Tackling the unreliability of neuroscientific measures in mental health research
N Haines, H Sullivan-Toole, T Olino
Biological Psychiatry: Cognitive Neuroscience and Neuroimaging 8 (8), 822-831, 2023
102023
Enhancing the psychometric properties of the iowa gambling task using full generative modeling
H Sullivan-Toole, N Haines, K Dale, TM Olino
Computational Psychiatry (Cambridge, Mass.) 6 (1), 189, 2022
102022
What is next for the neurobiology of temperament, personality and psychopathology?
I Trofimova, S Bajaj, SA Bashkatov, J Blair, A Brandt, RCK Chan, ...
Current Opinion in Behavioral Sciences 45, 101143, 2022
92022
Easyml: Easily build and evaluate machine learning models
P Hendricks, WY Ahn
BioRxiv, 137240, 2017
92017
Easyml: Easily build and evaluate machine learning models. bioRxiv, 137240
WY Ahn, P Hendricks, N Haines
52017
Explaining the description-experience gap in risky decision-making: Learning and memory retention during experience as causal mechanisms
N Haines, PD Kvam, BM Turner
Cognitive, Affective, & Behavioral Neuroscience 23 (3), 557-577, 2023
42023
Negative affect induces rapid learning of counterfactual representations: A model-based facial expression analysis approach
N Haines, O Rass, YW Shin, JW Brown, WY Ahn, WY Ahn, N Haines
bioRxiv, 2020
4*2020
The system can't perform the operation now. Try again later.
Articles 1–20