Research

Unlocking neural mechanisms underlying learning & memory

To understand underlying neural mechanisms of learning and memory, we take a combined approach of computational modeling, behavioral experiments, neuroimaging, and neuromodulation. We are interested in two distinct memory systems, which are procedural and declarative memory, and how these two systems interact. Building on these scientific findings, we investigate the development of efficient learning protocols applicable to the rehabilitation of patients with stroke and Parkinsonism. 

Computational modeling of motor control, learning, and memory

Motor learning tasks are often categorized into motor adaptation, which learns recalibration of existing motor policies  to perturbed environment, and motor skill learning, which learns novel motor policies to achieve task goals. Learning to walk on the moon would be a...

Computational approaches to fMRI analysis

Thanks to fast-increasing computing power, it is becoming more available to perform computationally intensive analysis on high-dimensional fMRI data. Also, during last two decades, traditional analysis of localizing brain regions associated cognitive functions has been...

Neuromodulation of learning and memory
using noninvasive stimulation

Stimulation of brain has a long history dating back to the 18th century, using transcranial electrical stimulation. In the era, people did not have enough knowledge about neurophysiology such that they shocked their own brain regardless of irreversible permanent brain...

Neural substrates of de novo motor skill learning

Human motor skill learning is a complicated process of generating a novel movement pattern to achieve a task goal. To date, most neuroimaging studies investigating neural mechanism of motor skill learning have employed target-reaching, sequential force control, or sequ...

Computational, behavioral and neural correlates of human reinforcement learning are well understood in decision making with discrete choices, however, little has been known about more generalized decision making in a continuous choice space....

Neural computations underlying human reinforcement learning in a continuous choice space