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Our Research

The Computational Cognitive and Neural Sciences Lab at the University of California, Riverside uses a multimodal approach to investigate the mechanisms that enable people to make adaptive decisions and pursue their goals. You can read below about some of our projects.

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Mechanisms of goal selection

Humans are constantly faced with decisions between different goals. For example, should you work late tonight to meet a deadline, or should you go to the store to cook yourself a healthy meal? Our research investigates how rewards influence these decisions: you may be more likely to choose to cook a healthy meal if a month of this behavior has led to rewarding improvements in health. The influence of reward on goal selection can be adaptive when it reinforces beneficial behaviors (as in the case of healthy eating) or maladaptive when it impairs the flexibility to adopt better goals (as in substance use disorder). We use a multimodal approach to study the neural mechanisms linking rewards to goal selection. The figure on the left depicts a new approach, real-time fMRI neurotriggering, for targeting reward delivery to specific neural representations of goals. You can read about our other approaches here:

Neural circuits for behavioral flexibility

How do we adapt our behavior when it is no longer effective for achieving our goals? We are investigating how subcortical brain nuclei (including the striatum, depicted in red) and the dopamine system respond to reward feedback by engaging cognitive flexibility. A key idea from this line of work is that negative feedback is a vital signal for behavioral change and new learning. Our research suggests that psychological interventions emphasizing the informativeness of errors and losses for goal-pursuit could help improve cognitive flexibility. 

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Neurocomputational mechanisms of anxiety and anxiety disorders

Anxiety is a pervasive mental state that impacts many people's lives in both healthy and clinical populations. There is substantial research showing alterations in the mesolimbic dopamine system in patients with anxiety disorders. Our research seeks to understand why and how anxiety and anxious behaviors activate the dopamine reward system and engage habit learning. In addition, we are applying our computational approach (schematically depicted on the left) to understand how goals, rules, and rewards interact in anxiety disorders. Ultimately, the goal of this research is to uncover strategies for unlearning associations that trigger and reinforce anxious mental states. 

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