PROJECTS
I'm a biomedical engineer and neuroscientist. I develop methods to investigate brain activity at network level.
During my PhD, I developed a complete toolbox (on MATLAB platform) for high-density EEG analysis. It allows us to clean the EEG signals, to build realistic head model according to the individual structural image, to estimate the neuronal activity with precision, and to map the brain connectivity.
Currently, I am mainly interested in using control theory and computational models to help us understand the architecture of human brain, the function of brain, and the dysfunction of diseased brain.
Ongoing Projects
PROJECT 1: Layered architecture in human sensorimotor control
Nervous systems sense, communicate, compute, and actuate movement, using distributed components with tradeoffs in speed, accuracy, cost, sparsity, noise, and saturation throughout. Nevertheless, the resulting control can achieve remarkably fast, accurate, robust performance. This is due to a highly effective layered architecture that combines higher layers of planning/tracking with lower layer reflex/reaction. We proposed a theoretical framework using feedback control theory and information theory which connects the component level speed-accuracy tradeoffs (SATs) in neurophysiology and system level SATs in sensorimotor control performance.
PROJECT 2: Bayesian Brain in aging: from predictive coding perspective
When getting older, certain brain functions, such as working memory and executive function, decline, and the corresponding patterns of neural oscillations might be disrupted. The functional deficits in clinical population have been intensively studied. However, the underlying neurocomputational basis of these functional deficits is less known. In this project, I proposed a dynamic Bayesian framework to show the predictive process and the updated belief in aging brain. We show that the model parameter significantly correlated with CSF tau level at Alzheimer's disease. The computational framework allows to reveal the hidden computational processes in human brain, and provides a potential tool to disentangle the deficits at neurocomputational level.
PROJECT 3: Brain network analysis using Multi-modal neuroimaging
Brain is organized as a complex network architecture. How the brain network is structured, and how the network structure supports brain functions are still elusive. In this project, we aim to develop new neuroimage methods using multimodal neuroimage techniques including high-density EEG, fMRI and DTI to investigate the structural organization of brain network and the functional correspondence.