Northwestern University Feinberg School of Medicine

Physical Therapy & Human Movement Sciences

Yuan Yang, PhD

Lab Description

My lab focuses on the development of novel neural signal (EEG, EMG) processing and multi-modal brain imaging (EEG, MRI) tools to quantify neural connectivity in the nervous system. Assessing the connectivity between neuronal populations reveals how the nervous system adapts and reorganizes after neural disorders (e.g. stroke) and during the recovery, so as to evaluate neural impairments and facilitate neurorehabilitation interventions.

Important Links

NIH Bibliography
Google Scholar Page


Current Projects

Project 1: Quantifying nonlinear neural connectivity during movement control: Neural interactions in the human nervous system can occur as a nonlinear process. Due to lack of an effective nonlinear method, methods based on linear coherence are extensively used to investigate neural interactions between the central nervous system and the periphery during movement control. I proposed and developed a novel method to assess nonlinear neural connectivity and time delays in neural systems. My method unveils the neural coupling within sensorimotor system in a more complete way than the commonly used (linear) corticomuscular coherence method. Our results indicate that the nonlinear neural coupling likely comes from multi-synaptic interactions. Due to this remarkable contribution, we received 2017 Hojjat Adeli Award for Outstanding Contributions in Neural Systems for the paper entitle “A General Approach for Quantifying Nonlinear Connectivity in the Nervous System Based on Phase Coupling” (Int J Neural Syst. 2016;26(1):1550031. PubMed PMID: 26404514)
Project 2: Integration of multi-modal brain imaging approaches to understand brain function: Brain connectivity studies reveal how different brain areas work together during a task. Using advanced methods, I investigated brain connectivity during the movement control as well as cognitive tasks. These studies provide us with a better understanding of how the brain processes incoming information and controls body movements. In collaboration with Dr. Dewald and our international collaborators, I very recently proposed a novel multi-model brain imaging method which combines high-density EEG, T1 MRI and diffusion MRI. This approach allows tracking of neural information flow between cortical sources through existing neural tracts. This approach has the potential to be developed into a new neuroimaging tool to monitor brain neural network changes post hemiparetic stroke. This is expected to increase our understanding of stroke induced neural changes and allow us to determine the effect of more targeted neurorehabilitation interventions that reduce such changes.


Lab Members and Student Projects

Runfeng Tian, MSc (Clinical research associate)

Runfeng received his Master's degree in Biomechanical Engineering from Delft University of Technology, the Netherlands. He was Dr. Yang's former graduate student (co-supervised with Professor Frans van der Helm). He is a clinical research associate in Dr. Yang's lab, working on developing a multi-brain imaging approach (project 2) to assess the dynamic information flow in the brain network.

Nirvik Sinha (US-India Khorana Scholar 2018)

Nirvik has a M.D. background and is currently doing his research project in Dr. Yang's lab. He is working on computational modelling of multi-synaptic neural systems, which will eventually lead to a better understanding of the usage of backup indirect motor pathways (e.g. corticobulbospinal tracts) following a unilateral brain injury. 

Thomas Arend Michiel Plaisier, MEng (PhD student with Professor Julius Dewald)

Thomas is currently doing his PhD in Biomedical Engineering. Dr. Yang serves as a committee member to support his thesis.

Synthesis Project for the Class of 2021 DPT Students (co-supervised with Dr. Netta Gurari)

More information coming soon.

Completed Student Projects/Theses (including previous students at TU Delft)

Runfeng Tian (Master's thesis: Brain Dynamic Information Flow Estimation Based on EEG and Diffusion MRI)

Pablo Maceira Elvira (Master's thesis: Neural Dynamics based on EEG and diffusion MRI)

Bekir Guliyev (Master's thesis: Quantifying Effective Connectivity During the Cortical Intervention to Stretch Reflex)

Ioannis Petridis (Master's thesis: Nonlinear dynamics in the steady-state visual evoked response: methodology and clinical relevance in migraine)

Leonidas Eleftheriou (Intern Probing nonlinear mechanism of neuronal communication in the human stretch reflex)

Principal Investigator

Collaborating Faculty