Decision making is ubiquitous, and the ability to develop the knowledge about our environment from experience and use this knowledge to produce a series of actions that will maximize the overall reward is essential for survival. The main goal of our research in the Lee Lab is to understand the cortical (e.g., prefrontal cortex) and subcortical (e.g., basal ganglia) mechanisms that enable animals to choose appropriate behaviors and to improve their decision-making strategies by evaluating the outcomes of previous actions.
Research in the Lee Lab is highly inter-disciplinary and capitalizes on the insights from formal theories of economics and reinforcement learning as well as computational neuroscience of neural coding and behavioral studies of decision making. Lee Lab develops novel behavioral paradigms that can probe the core processes of decision making. Combined with the use of multi-electrode recording systems, this research seeks to unravel the biological basis of willful actions.
Anatomical distribution of neurons in the primate dorsolateral prefrontal cortex that encode multiple types of value signals during intertemporal choice (from Kim et al., 2012).
Economic Decision Making (Neuroeconomics)During decision-making, many different types of information about reward and penalty, such as their magnitude and probability, must be estimated and combined appropriately. By combining (i) economic and psychological theories, (ii) single-neuron recording method, and (iii) computational modeling, we aim to characterize the mechanisms of neural circuits responsible for selecting actions and predicting their outcomes. We also study the emotional processes involved in decision-making and their neural basis, such as regret.
Neural Mechanisms of Temporal and Numerical Cognition
Lee Lab also investigates how the brain represents time and uses timing information to control behavior. In particular, we study the cortical mechanisms necessary for multitasking by recording the activity of cortical neurons while the animals time multiple temporal intervals simultaneously. In addition, we study the computational algorithms and neurophysiological mechanisms for representing numerical quantities and how such information is manipulated during simple arithmetic operations.