Research

In the broadest sense, I use computational models to understand and make sense of the different facets of human cognition, especially memory, and its pathologies. As with every researcher, my research and collaborations form a network of themes, which I like to visualize like this:

Computational Psychiatry

Together with Briana Smith and Lori Zoellner, we have developed ACT-REM, a model of intrusive memories in PTSD:

  • Smith, B. M., Thomasson, M., Yang, Y. C., Sibert, C., & Stocco, A. (2021). When fear shrinks the brain: A computational model of the effects of posttraumatic stress on hippocampal volume. Topics in Cognitive Science, 13(3), 499-514.
  • Stocco, A., Smith, B. M., PeConga, E., & Zoellner, L. (2021). Memory, Interrupted: A Retrieval Model of Intrusive Memories, Recovery Trajectories, and Neurobiological Effects in Post-Traumatic Stress Disorder.

Together with Holly Hake, Tom Grabowski, and Hedderik van Rijn, we have been using ACT-R’s declarative memory model to track down cognitive decline in Mild Cognitive Impairment and Alzheimer’s Disease.

  • Hake, H., Grabowski, T., van Rijn, H., and Stocco, A. (in press) Breaking New Ground in Computational Psychiatry: Characterizing Forgetting in Healthy Aging and Mild Cognitive Impairment. Proceedings of the 45th Annual Meeting of the Cognitive Science Society. [Winner of the Modeling Prize in Applied Cognition]
FORGETTING IN Human Declarative Memory

Together with Hedderik van Rijn, we have tried to decode individual differences in long-term memory from resting state EEG and fMRI data

  • Xu, Y., Prat, C., Sense, F., van Rijn, H., & Stocco, A. (2021). Distributed Patterns of Functional Connectivity Underlie Individual Differences in Long-Term Memory Forgetting. bioRxiv, 2021-08.
  • Zhou, P., Sense, F., van Rijn, H., & Stocco, A. (2021). Reflections of idiographic long-term memory characteristics in resting-state neuroimaging data. Cognition, 212, 104660.
Human Procedural Memory and the basal ganglia

AKA the basal ganglia, my first love, and how to model it at different levels of abstraction.

  • Stocco, A., Prat, C. S. Graham, L. K., & (2021). Individual differences in reward learning processes predict fluid reasoning abilities. Cognitive Science, 45(2), e12941.
  • Xu, Y., & Stocco, A. (2021). Recovering reliable idiographic biological parameters from noisy behavioral data: The case of basal ganglia indices in the Probabilistic Selection Task. Computational Brain & Behavior, 4, 318–334.
  • Stocco, A. (2018). A biologically plausible action selection system for cognitive architectures: Implications of basal ganglia anatomy for learning and decision‐making models. Cognitive science, 42(2), 457-490.
  • Stocco, A., Murray, N., L. Yamasaki, B. L., Renno, T., J., Nguyen, J., & Prat, C. S. (2017). Individual differences in the Simon effect are underpinned by differences in competitive dynamics in the basal ganglia: An experimental verification and a computational model. Cognition, 164, 31-45.
  • Stocco, A. (2012). Acetylcholine-based entropy in response selection: A model of how striatal interneurons modulate exploration, exploitation, and response variability in decision making. Frontiers in Neuroscience, 6, 18.
  • Stocco, A., Lebiere, C., O’Reilly, R. C., & Anderson, J. R. (2010). The role of the anterior prefrontal-basal ganglia circuit as a biological instruction interpreter. Frontiers in Artificial Intelligence and Applications, 221, 153-162.
  • Stocco, A., Lebiere, C., & Anderson, J. R. (2010). Conditional routing of information to the cortex: A model of the basal ganglia’s role in cognitive coordination. Psychological review, 117(2), 541.
Brain Architecture and the Common Model of Cognition

A lot of the problems in using models in neuroscience come down to the problem of architecture, that is, a way to formally capture assumptions about cognition so that a model or a specific process (let’s say, perception) lives within a reasonable approximation of other memory processes (i.e., memory). There are plenty of computational architectures to choose from.

Together with Holly Hake and Catherine Sibert, we have used effective and functional connectivity to test whether the Common Model of Cognition provides a realistic approximation to the brain’s true architecture.

  • Hake, H. S., Sibert, C., & Stocco, A. (2022). Inferring a Cognitive Architecture from Multitask Neuroimaging Data: A Data‐Driven Test of the Common Model of Cognition Using Granger Causality. Topics in Cognitive Science, 14(4), 845-859.
  • Sibert, C., Hake, H. S., & Stocco, A. (2022). The structured mind at rest: low-frequency oscillations reflect interactive dynamics between spontaneous brain activity and a common architecture for task control. Frontiers in Neuroscience, 16.
  • Wapstra, N. J., Ketola, M., Thompson, S., Lee, A., Madhyastha, T., Grabowski, T. J., & Stocco, A. (2022). Increased Basal Ganglia Modulatory Effective Connectivity Observed in Resting-State fMRI in Individuals With Parkinson’s Disease. Frontiers in Aging Neuroscience, 14.
  • Stocco, A., Sibert, C., Steine-Hanson, Z., Koh, N., Laird, J. E., Lebiere, C. J., & Rosenbloom, P. (2021). Analysis of the human connectome data supports the notion of a “Common Model of Cognition” for human and human-like intelligence across domains. NeuroImage, 235, 118035.
CHARACTERIZING INDIVIDUAL DIFFERENCES THROUGH PREDICTIVE MODELING

One theme that runs through my research is the need to characterize predictive models that can be personalized for a specific individual — a “digital twin” of a person that can be used to make predictions about future outcomes or treatments.

  • Hake, H., Grabowski, T., van Rijn, H., and Stocco, A. (in press) Breaking New Ground in Computational Psychiatry: Characterizing Forgetting in Healthy Aging and Mild Cognitive Impairment. Proceedings of the 45th Annual Meeting of the Cognitive Science Society. [Winner of the Modeling Prize in Applied Cognition]
  • Stocco, A., Prat, C. S. Graham, L. K., & (2021). Individual differences in reward learning processes predict fluid reasoning abilities. Cognitive Science, 45(2), e12941.
  • Xu, Y., Prat, C., Sense, F., van Rijn, H., & Stocco, A. (2021). Distributed Patterns of Functional Connectivity Underlie Individual Differences in Long-Term Memory Forgetting. bioRxiv, 2021-08.
  • Zhou, P., Sense, F., van Rijn, H., & Stocco, A. (2021). Reflections of idiographic long-term memory characteristics in resting-state neuroimaging data. Cognition, 212, 104660.
  • Xu, Y., & Stocco, A. (2021). Recovering reliable idiographic biological parameters from noisy behavioral data: The case of basal ganglia indices in the Probabilistic Selection Task. Computational Brain & Behavior, 4, 318–334.
  • Stocco, A. (2018). A biologically plausible action selection system for cognitive architectures: Implications of basal ganglia anatomy for learning and decision‐making models. Cognitive science, 42(2), 457-490.
  • Stocco, A., Murray, N., L. Yamasaki, B. L., Renno, T., J., Nguyen, J., & Prat, C. S. (2017). Individual differences in the Simon effect are underpinned by differences in competitive dynamics in the basal ganglia: An experimental verification and a computational model. Cognition, 164, 31-45.