David Chen

Student Spotlight on David Qixiang Chen

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By: Melissa Galati

For some graduate students, identifying and following their passion is straightforward. For most of us, however, carving out a niche in scientific research is not as easy as it appears. We sometimes wonder where our experiences will take us or if our efforts will ever amount to anything. I sat down with David Chen to discuss how his background in computer science prepared him for neuroscience research and served as a conduit for his future success in the field of neuroimaging.

David, born and raised in Chengdu, China, moved to Toronto at the age of 11. Throughout high school, he envisioned a career in graphic design, never intending on going to university. However, his parents, who valued education, encouraged him to pursue a postsecondary education. Consequently, he completed his bachelor’s degree in computer science at the University of Toronto (U of T), reasoning that he could appease his parents while simultaneously learning more about graphic design. During his third year, he interned for a 3D graphics technology company called Alias. It was only after this experience that David began to question his career goals. “You always think your life is going to go in one direction and you think you know what you want to do… the experience itself made me question what kind of value I wanted to create in my life.”

After completing his computer science degree, David took on some freelance web development projects. “I sort of wandered around for a while… a friend of mine, who was doing a summer studentship, mentioned that her boss needed a computer guy.” This is how David came to meet his future supervisor, Dr. Mojgan Hodaie, a neurosurgeon at Toronto Western Hospital (TWH). “She asked me if I would do research in neuroscience, so I thought—yeah I could do that. At this point I hadn’t touched biology since grade ten,” David smiled, “I had a lot of catching up to do.” While working for Dr. Hodaie as research associate (RA), David, who found that he enjoyed neuroscience immensely, decided that he wanted to pursue graduate studies. “By the time I started grad school, I had a good idea of what my project would be.” David laughed as he reflected on his decision. “In retrospect, I think it was a good choice… I guess I should probably thank my parents for that.”

David is now a fourth year PhD student in the Institute of Medical Science (IMS). He studies Trigeminal Neuralgia (TN), a facial neuropathic pain syndrome typically caused by neurovascular compression of the fifth cranial (trigeminal) nerve. “People say it’s the worst pain that humans can experience because it’s a very sudden, shock-like, stabbing pain… it’s pretty horrendous,” remarks David. The trigeminal nerve, he points out, is a gateway to study pain. “It’s the primary sensory input of the face, but you get a very wide range of pain [sensations].” This includes TN-like pain that sometimes occurs in patients suffering from multiple sclerosis (MS). This spectrum of pain, arising from the perturbations of the same nerve, is what makes this structure interesting to study. David’s project involves comparing classical TN to TN secondary to MS (MS-TN) using diffusion magnetic resonance imaging (MRI)—a novel neuroimaging method that allows for better imaging of the trigeminal nerve (specifically the regions encompassed within the brain stem). David’s findings suggest that classical TN is caused by microstructure changes in the cisternal portion of the trigeminal nerve, while MS-TN may be caused by lesions near the trigeminal nucleus—a structure contained within the brain stem. These results were recently published in Multiple Sclerosis.

Data analysis using diffusion MRI images is incredibly time consuming if done manually, on a patient by patient basis. By employing his computer graphics intuition, David created a workflow to automate this process. 3D tractography data from many individuals can be combined to create an average, normalized brain in a way that retains the 3D model but prevents the loss of information. For the future, David hopes that this technology can be used to make tractography much more clinically relevant. Physicians, who normally have to wait a week for diffusion MRI images to be analyzed, can perform the analysis instantly. “If a machine can be precomputed [to tell you] how out of range your brain is from “normal”…this makes clinical diagnosis much faster.”

When asked about his experience in the IMS, he reflects that the program has allowed him to interact with both basic science and clinical researchers, both of whom have methods of problem solving that are different from computer scientists. By combining these strategies, David has been able to successfully apply his computer science background to accelerate neuroscience research. It is clear that David’s experience in the IMS has given him some valuable insight into what it takes to make it in scientific research. Students, he reasons, should be more involved in the design of experiments and interpretation of data. They should spend time discussing their projects and ideas with others. Although experiments are important for generating data, machines are replacing much of what we do in the lab. “The value of humans in knowledge creation is their creativity. They can interpret complexity in a different way.” He also advises new students to choose their mentors wisely. His supervisor, Dr. Hodaie, has been incredibly patient and supportive of him since he started as an RA in her lab. David’s story shows us that in order to find our passion, we sometimes have to be open to new opportunities. The experiences and skills we acquire can help us in ways we never anticipated.