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Research projects

Knowledge representation and generalization

Category representations can be broadly classified as containing within–category information or between–category information. Although such representational differences can have a profound impact on decision–making, relatively little is known about the factors contributing to the development and generalizability of different types of category representations. These issues are addressed by investigating the impact of training methodology and category structures using a traditional empirical approach as well as the novel adaptation of computational modeling techniques from the machine learning literature. You can learn more about this topic here or here.

Collaborator: Shawn Ell.

System-switching in perceptual categorization

Mounting evidence suggests that category learning is achieved using different psychological and biological systems. While existing multiple-system theories and models of categorization may disagree about the number or nature of the different systems, all assume that people can switch between systems seamlessly. However, little empirical data has been collected to test this assumption, and recent available data suggest that system-switching is difficult. The main goal of this project is to identify factors influencing the proportion of participants who successfully learn to switch between procedural and declarative systems on a trial-by-trial basis. You can learn more about this topic here.

Collaborator: Greg Ashby.

Neuroeconomics, valuation, and cognitive function

In neuroeconomics, valuation refers to the process of assigning values to states and actions based on the animal's current representation of the environment while reward processing corresponds to processing the feedback received from the environment to update the values of states and actions. This project explores how these fundamental processes affect various cognitive functions. Specifically, we focus on the role of valuation and reward processing in attention, memory, decision-making, and learning. Another goal of this project is to explore how deficits in cognitive functions observed in a number of psychiatric disorders (e.g., addiction, pathological gambling, schizophrenia, and mood disorders) can be explained in terms of abnormal valuation and reward processing. You can here learn more about this project here or here.

Collaborator: Dan Foti.