Nathaniel Haines
Psychology · The Ohio State University
Publications
48
Citations
1,225
Est. group size
~1
Recurring co-author estimate
Active years
52
Publishing since 1974
Nathaniel Haines studies how people learn from rewards and punishments, and how these learning processes relate to mental health conditions like depression, anxiety, and substance use. A major focus of his work is developing better statistical and computational tools (generative models) to make psychological and neuroscience measurements more reliable and reproducible. His research combines behavioral tasks, such as gambling and decision-making tests, with advanced modeling methods drawn from computational psychiatry and Bayesian statistics.
Publication output has fluctuated over the past decade, dipping in 2021 before recovering to a steady rate of about 3-5 papers per year in recent years.
Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026
- A tutorial on using generative models to advance psychological science: Lessons from the reliability paradox.
Psychological Methods · 2025
- Reward-specific learning parameters change across normative adolescent development and are blunted in youth with high risk for depression.
2025
- Reward and punishment learning among people with a lifetime history of anxiety, depression, and substance use disorder
Cognitive Affective & Behavioral Neuroscience · 2025
- Reward and Punishment Learning Among People with a Lifetime History of Anxiety, Depression, and Substance Use Disorder
2025
- Reward‐specific learning parameters change across normative adolescent development and are blunted in youth with high risk for depression
Journal of Child Psychology and Psychiatry · 2025
- Test-retest reliability of the play-or-pass version of the Iowa Gambling Task
Cognitive Affective & Behavioral Neuroscience · 2024
- BayesBlend: Easy Model Blending using Pseudo-Bayesian Model Averaging, Stacking and Hierarchical Stacking in Python
arXiv (Cornell University) · 2024
- A Bayesian workflow for securitizing casualty insurance risk
arXiv (Cornell University) · 2024
- From Classical Methods to Generative Models: Tackling the Unreliability of Neuroscientific Measures in Mental Health Research
Biological Psychiatry Cognitive Neuroscience and Neuroimaging · 2023
- Explaining the description-experience gap in risky decision-making: learning and memory retention during experience as causal mechanisms
Cognitive Affective & Behavioral Neuroscience · 2023
- From Classical Methods to Generative Models: Tackling the Unreliability of Neuroscientific Measures in Mental Health Research
2023
- Test-Retest Reliability of the Play-or-Pass Version of the Iowa Gambling Task (Haynes et al.)
2023
- Enhancing the Psychometric Properties of the Iowa Gambling Task Using Full Generative Modeling
Computational Psychiatry · 2022
- Future directions for cognitive neuroscience in psychiatry: recommendations for biomarker design based on recent test re-test reliability work
Current Opinion in Behavioral Sciences · 2022
- What is next for the neurobiology of temperament, personality and psychopathology?
Current Opinion in Behavioral Sciences · 2022
- bioRxiv (Cold Spring Harbor Laboratory)×4
- Cognitive Affective & Behavioral Neuroscience×3
- Computational Psychiatry×2
- Current Opinion in Behavioral Sciences×2
- Archives of Sexual Behavior×2
- Dylan D. Wagner
Psychology · The Ohio State University
- Kristen A. Lindquist
Psychology · The Ohio State University
- Nikki A. Puccetti
Psychology · The Ohio State University
- Scott A. Langenecker
Psychology · The Ohio State University
- Scott D. Blain
Psychology · The Ohio State University
This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.
Last updated Jul 19, 2026.
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