The Vancouver Coastal Health Research Institute (VCHRI) is committed to fostering a culture of mentorship for the next cohort of health researchers with the VCHRI Summer Program Advancing Research Knowledge and Skills (SPARKS). In this program, a select group of qualified undergraduate and medical students receive hands-on experience in health research by undertaking a summer project with a VCHRI principal investigator. This summer, students partnered with DMCBH faculty members to explore the mysteries of the brain.
Benjamin Nazif
Ben, a current fourth-year undergraduate at UBC, studies neuroscience, public health, and pharmacological and educational interventions. Under the supervision of Dr. Fidel Vila Rodriguez in the Ninet Lab, he worked on the CARS project, a prospective study on electroconvulsive therapy (ECT). This study aims to optimize ECT treatment by analyzing demographic and clinical profiles, EEG, and EKG data to improve patient care.
Ben applied to the SPARKS program to learn firsthand what scientific research looked like and contribute to meaningful advancements in psychiatric treatment. In the lab, he manages clinical data collection, grades EEG recordings, and codes R scripts for data analysis. During the summer he presented a research poster at the UBC Psychiatry Research Day, focusing on Youth ECT patients, and is working on publishing a case report in the Journal of ECT. Inspired by his parents, Ben aims to pursue a career in medicine, attempting both continue innovation while addressing the implementation gap of research to patient care.
Jasmyn Traboulay
The SPARKS program provided Jasmyn with a way to gain experience into clinical research. She has an avid interest in medical research and neurology, gaining valuable insight and knowledge into these respective fields through this program. Under the supervision of Dr. Stefan Lang, her research project centers on the use of deep brain stimulation (DBS) for the symptomatic treatment of Parkinson’s disease. Their goal is to become the second centre in Canada to establish a DBS and functional magnetic resonance imaging (fMRI) research program. This research aims to utilize fMRI to determine the effects of DBS on brain activity and network connectivity.
In the lab, Jasmyn participated in data acquisition and analysis. Their data primarily uses fMRI to visualize the brain underdifferent stimulation conditions. She learned how to employ different fMRI software packages to preprocess and analyze data acquired from these brain images. In doing so, Jasmyn gained skills related to image processing, quality control techniques, statistical modelling strategies, and brain connectivity modelling.
Jasmyn’s ultimate aspiration is to pursue a career in surgery, specifically in either neurosurgery or cardiothoracic surgery, to align her clinical practice with her research interests.
Kyle Vavasour
Kyle applied to the SPARKS program to gain practical experience applying the skills from his undergraduate degree in data science to real-world problems. His undergraduate degree’s focus on machine learning and data analysis aligns with medical research, making it an ideal opportunity for him to see how his classroom knowledge can contribute to the field. Kyle is particularly drawn to health research because he values the tangible impact it can have on people’s lives.
Under the supervision of Dr. Cornelia Laule, Kyle’s research project was to develop a machine learning model that can identify different regions of tissue in MRI images of ex-vivo spinal cords. The different types of tissue are called white matter and gray matter, and identifying these regions is often an important but time consuming step in the processing of MRI data. Creating an automated method of identifying these regions helped speed up this process and could enable research on larger datasets of MRI images.
When he first started the SPARKS program, Kyle knew very little about MRI imaging. He has learned a lot about the topic through the instruction of Dr. Laule, other members of the lab, and seminars held by the lab. He has also learned about how to effectively communicate his research through the lab meetings and presentations that he participated in over the course of the program. His most memory moment was when his machine learning model started to achieve good accuracy on identifying regions of the spinal cord MRI images. Seeing his model successfully identify the regions was a breakthrough moment, especially after the first few variations of the model were unsuccessful.
His biggest accomplishment during the research was delivering his machine learning model to his supervisor and the lab team. He’s very excited to see how the model can support their research!
