Dr Tin Chung: prosthetic system for the cerebellum

25 August 2017

Dr Chung Tin (Croucher Scholarship 2002) explains how our respiratory system works.

Dr Chung Tin (Croucher Scholarship 2002) is an Assistant Professor at the Department of Mechanical and Biomedical Engineering of the City University of Hong Kong (CityU).

Inspired by his maternal grandfather, who was an engineer, he was always fascinated by how products worked.

“Even as a child, I always liked to break things up and understand how they are assembled and how they function,” he says.

This general interest developed into a specific fascination with machines and robotics and it was a natural direction for him to study mechanical engineering at the University of Hong Kong. During his undergraduate study, he started to consider a career in science and was encouraged by Professor Chow Kwok Wing to study overseas. By co-incidence, Chow had been a student at the same high school as Tin and had later undertaken post-graduate studies at Massachusetts Institute of Technology, thus able to support his student in obtaining a place at the same graduate school.

“I was lucky that I had a great deal of support from the universities and from the Croucher Foundation,” says Tin.

Tin’s master’s degree at MIT focused on unmanned aerial vehicles (UAVs or drones) and looked at developing advanced optimisation techniques for the flight paths of a group of UAVs, visiting multiple targets. When the opportunity arose to pursue a PhD at MIT, the direction of Tin’s research took a slight departure.

“I was fascinated by some projects running in biomedical engineering,” he says and with an award of an American Heart Association Pre-Doctoral Fellowship, he joined a project focused on the adaptive neural control of the respiratory system.

By using Tin and his colleagues’ background in mechanical engineering and control theory, the team regarded the brain as a sophisticated adaptive controller and sought to obtain a better understanding of how it controls the respiratory system, using classic engineering control theory. He still needed to learn about the biology of the brain though, so that he could establish correlation between the biological and engineering perspectives.

While some might regard breathing as an involuntary reflex, it is a complex control process that must adapt to multiple variables such as the environment, exercise levels and disease and respond to input from sensory inputs differently as needed.

His PhD supervisor, Dr Chi-Sang Poon, proposed that the adaptive control function of the respiratory system was a form of optimization and some respiratory related conditions such as exercise hyperpnea (increased respiration at constant blood CO2 level during exercise) and sleep apnea (pauses in breathing or shallow breaths during sleep) can be better understood by using this framework. Tin investigated if conditions of this nature were a result of change in gain realized by the adaptive control mechanism.

Undertaking animal experiments, Tin took neural recordings of the brainstem, the centre of respiratory control, and looked at the neural response to different combination of input levels of O2 and CO2. While it had been assumed that this was a relatively simple additive function, Tin discovered that it was more of a complex multiplicative interaction. The information from input sensors enhance each other and are integrated by the respiratory related neurons in brainstem in a nonlinear way and not just treated as independent inputs. For example, Tin discovered that when CO2 levels are very low, these neurons are more sensitive to the O2 stimulus, and hence a hypoadditive hypercapnic–hypoxic interaction. It was an important new insight.

Tin says his years at MIT was an “eye-opening experience” and he met a lot of very smart people but at first it was a “culture shock” after studying in Hong Kong. He remembers that while he felt well equipped with the technical skills and knowledge to undertake his work, he had to “adapt his mindset a little” for the process of formulating problems and exploring solutions, using open questions.

After an interesting period as a postdoctoral associate in MIT with Dr Chi-Sang Poon, Tin was ready to return to Hong Kong and his family roots. He accepted the offer of a position at CityU and started in his current role in 2012. He continued his work in system control, computational neuroscience and neural prosthetics, the hardware devices that substitute a motor, sensory or cognitive modality.

Tin has recently completed a highly demanding project and submitted a paper for publication on a prosthetic system he has built for the cerebellum. This part of the brain receives information from the sensory systems, the spinal cord, and other parts of the brain and regulates motor movements such as posture, balance, coordination, and speech, resulting in smooth and balanced muscular activity.

The prosthetic is able to simulate important functions of the cerebellum in real time and given the vast complexity and processing power required, it utilises a field-programmable gate array (FPGA) platform to implement.

The simulator was tested using the classic delayed eyeblink conditioning (DEC) procedure. This form of classical conditioning has been used extensively to study neural structures and mechanisms that underlie learning and memory. The procedure consists of pairing an auditory stimulus (the conditioned stimulus (CS)) with a delayed eyeblink-eliciting unconditioned stimulus (US) (e.g. a mild puff of air to the cornea ). After many CS-US pairings, an association is formed such that a learned blink, or conditioned response (CR), occurs and precedes US onset.

The real neural spike from the animal was streamed to the FPGA board and processed in real time by the prosthetic before generating a feedback spike and trigger for the eye blink, so replacing the animal’s cerebellum function.

In what is an exciting breakthrough, this demonstrated the new neural prosthetic successfully substituted a cerebellum function that could contribute to muscle coordination and timing element, by making use of the neural network of the real cerebellum. This was done by integrating a sophisticated mathematical model which takes into account a good portion of the actual network structure of the cerebellum and efficient hardware implementation for real-time simulation. The paper will be published shortly.


Dr Tin Chung is currently an Assistant Professor in Department of Mechanical and Biomedical Engineering at City University of Hong Kong. He received his BEng. degree (1st Class) from University of Hong Kong in Mechanical Engineering in 2002. He then moved to the United States and obtained his S.M. and PhD. degrees, both in Mechanical Engineering, from Massachusetts Institute of Technology, in 2004 and 2011, respectively. He continues as a postdoctoral associate in MIT until he returned to Hong Kong in 2012. He has been awarded Croucher Foundation Scholarship (HK), American Heart Association Predoctoral Fellowship, and Early Career Award (Research Grant Council, Hong Kong). His research interests include neural prosthetic systems, brain-machine interface, neural computation and sensorimotor learning and control.


To view Dr Tin's Croucher profile, please click here