RADLab Projects 

Long-Term Projects in our Lab

Decision Making: We are building a neural network (in the form of a software program) to model core features of decision-making and self-control. Our particular interest is to examine mechanisms by which contextual (non-value-related factors) influence value-based decision-making. 
Complementary Learning Systems: We are uncovering the interactions between the PFC and the Hippocampus related to semantic knowledge. We seek to identify a common set of learning principles that operate in both learning systems. 
Learning Mechanisms in the Brain: Back-propagation is a widely used learning system in Artificial Intelligence. However, it is unlikely to operate in biological brains. We are characterizing a learning algorithm that can afford the flexibility of back-propagation and respects constraints imposed by biology.
Mind Wandering: Our minds often do not stay on task. We are developing new ways of measuring when our minds wander. We also seek to develop computational approaches to better understand the neural underpinnings of mind-wandering.
Emotions: What is an instance of an emotion? How do emotion categories emerge? How do we regulate our emotions? These age-old questions have primarily been examined via behavioral and neural experiments. We seek to make progress on these questions via computational modeling.

Graduate Researcher-Led Projects in our Lab

We are committed to the principle that every graduate student admitted to the lab will take leadership of a project. They play a key role from the initial design of their project to paper writing, and re-submitting.

Several graduate-researcher-led projects have led to publications in the field's top journals.
Graduate-researcher-led-led projects reflect both the individual interests of the graduate student and the long term interests of the lab.

Development and validation of a mind-wandering measure that does not rely on self-report measures.

Examining the interactions between a context-driven tendency to use a particular method of emotion regulation and a contrary instruction.

Examining the role of attention in diverse decision-making scenarios including The Decoy Effect, Status Quo Bias, and Anchoring.

An empirical project examining the performance of people high on the Alxithymia scale on internal and external repeating variables.

Examining how the co-occurrence of items leads to the subjective feeling of how close those items are.

Determining whether some emotional states more naturally lead to other emotional states. For example, is a state of calmness more likely to be followed by a state of anger or a state of sadness?

Examining the role of attention in diverse decision-making scenarios including The Decoy Effect, Status Quo Bias, and Anchoring 

Several graduate students in our lab have ongoing projects related to Artificial Neural Networks, Data Science, and User Experience.