Tzyy-Ping Jung


Center for Advanced Neurological Engineering

Institute for Neural Computation (INC) and

Institute of Engineering in Medicine (IEM)

University of California, San Diego (UCSD)

Associate Director

Swartz Center for Computational Neuroscience

Institute for Neural Computation (INC), UCSD

Adjunct Professor

Department of Bioengineering, UCSD

Adjunct Professor

Department of Computer Science

Department of Electrical Engineering

National Chiao Tung University, Hsinchu, Taiwan

Adjunct Professor

School of Precision Instrument and Opto-electronic Engineering

Tianjin University, Tianjin, China

The long-range goal of my research is to integrate methods in neural engineering and computation with basic scientific and clinical knowledge of nervous system to improve the diagnosis, treatment, and prevention of neurological diseases. I mainly focus on:

•novel approaches to recording and modeling brain activities and body functions, including and combining electroencephalographic, electromyographic, behavioral, and physiological measures,

•dry EEG sensor arrays and wearable/wireless data acquisition and signal processing hardware and software that can monitor and record non-invasive, high spatial and temporal resolution, brain activity of unconstrained, actively engaged human subjects,

•applying computational approaches such as independent component analysis (ICA), time-frequency analysis, and statistical analysis to analyze and model neural activity associated with human cognition, perception and awareness,

•fusing multiple streams of psychophysiological information to construct prototypes of neurocognitive brain-machine interface to improve overall human performance,

  1. methods and concepts to characterize and clarify neuropathogenic processes, and improve prevention, diagnosis, and treatment of neurological diseases and injuries. 


NEW demo

High-speed spelling with a noninvasive brain-computer interface

High-speed spelling with a noninvasive brain-computer interface, Proceedings of the National Academy of Sciences, Nov. 8, 2015.

This study reports a noninvasive brain speller that achieved a multi-fold increase in information transfer rate compared to other existing systems. Based on extremely precise coding of frequency and phase in single-trial steady-state visual evoked potentials (SSVEPs), this study developed a new joint frequency-phase modulation method and a user-specific decoding algorithm to implement synchronous modulation and demodulation of electroencephalogram (EEG). The resulting speller obtained high spelling rates up to 60 characters (12 words) per minute. The proposed methodological framework of high-speed BCI can lead to numerous applications in both patients with motor disabilities and healthy people.