Computational models are important tools for developing explicit process models of cognitive and neurobiological processes. Building such models forces one to be explicit about the mechanisms underlying a particular phenomenon and how those mechanisms interact with each other. Running such models provides a plausibility test/existence proof for the theories you develop and implement in such models. Our lab focuses on building neurobiologically plausible neural network models in a variety of different domains:
- Motivation
- The Structure and Dynamics of Human Personality
- Motivated Decision-making and Behavior
- Pathologies of Motivation: Depression, Anxiety
- Social Evaluation and Threat Perception
- Coherence-based Reasoning in Legal and Everyday Decision-making
- Coherence in Belief Systems, Belief Change attitude accessibility and the consistency of belief systems
- Impression Formation and Person Perception
We are currently developing connectionist (neural network) models to better understand motivation, personality, depression & anxiety, person perception, attitudes & beliefs, social reasoning, and social behavior. We are currently working on the following models:
- A neural network model of human motivation and motivated decision-making.
- A neural network model of personality.
- A neural network model of depression and anxiety
- A neural network model of threat perception, with David Marsh
- A neural network model of Spontaneous Trait Inference and how such inferences could be updated by new information.
Previous modeling work
- Computational models of attitudes and beliefs
- Computational models of person perception
- A connectionist model of Cognitive Dissonance.
- Computational models of online social behavior (GITHUB, Twitter, Reddit, etc.)
- A connectionist model of social evaluation, based on Cunningham’s Iterative Reprocessing model.
Current Projects
A number of different projects with code and compiled versions can be found at:
https://github.com/SocialComputation
Associated Faculty
Stephen J. Read (Psychology)
Lynn C. Miller (Annenberg School and Psychology)
In addition, a number of individuals in a variety of other departments are also actively investigating computational models (Linguistics, Psychology (Cognitive and Clinical), Computer Science, and the Neural, Informational, and Behavioral Sciences Program (NIBS)).
Collaborators
David March -Florida
Students
- Santie Mackenzie
- Andre Rodrigues
- Akili Tulloch
- Tommaso Bianzino
- Athena Sy Kuzuhara
Hardware
- one 20 core HP computing cluster
- one 12 core HP workstation
Software
Emergent Neural Network simulation software.
Thagard’s ECHO program for parallel constraint satisfaction models
Articles
Read, S. J., & Marcus-Newhall, A. R. (1993). Explanatory coherence in social explanations: A parallel distributed processing account. Journal of Personality and Social Psychology, 65, 429-447.
Read, S. J., & Miller, L. C. (1993). Rapist or “regular guy”: Explanatory coherence in the construction of mental models of others. Personality and Social Psychology Bulletin, 19, 526-540.
Read, S. J., Vanman, E. J., & Miller, L. C. (1997). Connectionism, Parallel Constraint Satisfaction Processes and Gestalt Principles: (Re) Introducing Cognitive Dynamics to Social Psychology. Personality and Social Psychology Review, 1, 26-53.
Read, S. J., & Montoya, J. A. (1999). An autoassociative model of causal learning and causal reasoning. Journal of Personality and Social Psychology, 76, 728-742.
Read, S. J., & Miller, L. C. (2002). Virtual Personalities: A Neural Network Model of Personality. Personality and Social Psychology Review. 6, 357-369.
Read, S. J., & Urada, D. (2003). A neural network model of the outgroup homogeneity effect. Personality and Social Psychology Review. 7, 146-169.
Read, S. J., Monroe, B. M., Brownstein, A. L., Yang, Y., Chopra, G., & Miller, L. C. (2010). A Neural Network Model of the Structure and Dynamics of Human Personality. Psychological Review. 117, 61–92.
Ehret, P. J., Monroe, B. M., & Read, S. J. (2015). Modeling the Dynamics of Evaluation: A Multilevel Neural Network Implementation of the Iterative Reprocessing Model. Personality and Social Psychology Review, 19(2), 148-176.
Read, S. J., Smith, B., Droutman, V., & Miller, L. C. (2017). Virtual Personalities: Using Computational Modeling to Understand Within-Person Variability. Journal of Research in Personality. 69, 237–249.
Read, S. J., Droutman, V., Smith, B. J., and Miller, L. C. (2017). Using Neural Networks as Models of Personality Process: A Tutorial. Personality and Individual Differences. https://doi.org/10.1016/j.paid.2017.11.015
Brown, A. D., & Read, S. J. (2018). Interested in Understanding the Dynamics of Personality Disorders? Computational Modelling Can Help. European Journal of Personality, 32(5), 533-534.
Read, S. J., Brown, A. D., Wang, P., & Miller, L. C. (2018). The Virtual Personalities Neural Network Model: Neurobiological Underpinnings. Personality Neuroscience. Vol 1: e10, 1–11. doi:10.1017/ pen.2018.6
Smith, B. J., & Read, S. J. (2021). Modeling incentive salience in Pavlovian learning more parsimoniously using a multiple attribute model. Cognitive, Affective, and Behavioral Neuroscience. doi.org/10.3758/s13415-021-00953-2
Chapters
Read, S. J., & Miller, L. C. (1994). Dissonance and Balance in belief systems: The promise of parallel constraint satisfaction processes and connectionist modeling approaches. In R. C. Schank & E. J. Langer (Eds.), Beliefs, reasoning, and decision making: Psycho-logic in honor of Bob Abelson (pp. 209-235). Hillsdale, NJ: Erlbaum.
Read, S. J., & Miller, L. C. (1998). On the dynamic construction of meaning: An interactive activation and competition model of social perception. In S. J. Read & L. C. Miller (Eds.) Connectionist models of social reasoning and behavior. Mahwah, NJ: Erlbaum.
Read, S. J., & Monroe, B. M. (2009). Using Connectionist Networks to Understand Neurobiological Processes in Social and Personality Psychology. In E. Harmon-Jones & J. Beers (Eds.) Methods in Social Neuroscience. New York: Guilford Press.
Read, S. J., Droutman, V., & Miller L. C. (2017). Virtual Personalities: A Neural Network Model of the Structure and Dynamics of Personality. In R. R. Vallacher, S. J. Read, & A. Nowak (Eds.). Computational Social Psychology. New York: Psychology Press (Frontiers of Psychology series).
Read, S. J., & Miller, L. C. (2019). A Neural Network Model of Motivated Decision-making and Everyday Behavior. In Angela O’Mahony and Paul Davis (Ed.). Social-Behavioral Modeling for Complex Systems. Wiley.
Read, S. J., Wang, P., Brown, A. D., Smith, B. J., & Miller (2021). Neural Networks and Virtual Personalities. In J. Rauthmann (Ed.). The Handbook of Personality Dynamics and Processes. Elsevier.
Read, S. J., & Miller, L. C. (2021). Neural Network Models of Personality Structure and Dynamics. In Wood, D., Harms, P., Read, S. J., & Slaughter, A. (Eds.). Measuring and Modeling Persons and Situations. Cambridge, MA: Elsevier.
Books
Read, S. J., & Miller, L. C. (1998). (Eds.). Connectionist models of social reasoning and social behavior. Mahwah, NJ: Erlbaum.
Vallacher, R. R., Read, S. J., & Nowak, A. (2017). (Eds.). Computational Social Psychology. New York: Psychology Press (Frontiers of Psychology series).