Mashbayar Tugsbayar is a PhD IPN student at the Learning in Neural Circuits (LiNC) lab at MILA and McGill. Her project, titled Brain-based top-down recurrent model of the visual system, falls under Healthy Brains, Healthy Lives' Research Theme 1—Neuroinformatics and Computational Modelling.
What inspired you to pursue your current degree?
I've always been fascinated by the idea of creating a digital brain and being able to test hypotheses, drug interactions and novel therapies on it. My current research allows me to combine both my fascination with the brain and my love of building things.
What is your area of research and what are the future implications of your project?
I work with NeuroAI, implementing computations related to the human brain to better understand it. I hope to gain an understanding of these computations and neural circuitry in vision to ultimately help repair damage, such as the reversal of vision loss after a stroke, for example.
What are some challenges that you face as a trainee or in your research? How do you try to overcome them?
I'd never met a scientist until I went to college, so I often feel as if I'm missing something others understand, not working as much as I should, etc. The best way to combat these feelings, I find, is to be open about my experiences and background. That way, I often get help or find that I'm not alone in my experiences.
What do you like best about (your) research?
NeuroAI has the "cool factor" in AI research, and it can be applied to causes I care very deeply about, which are aiding stroke recovery and combating neurodegenerative diseases.
What non-science activity or hobby do you most enjoy?
I love writing heist and mystery short stories. It's so satisfying to make everything come together and click neatly in the end, unlike what often happens in biology research.
What accomplishment are you most proud of this year?
Aside from being an HBHL Fellow, I'm very proud to have started my PhD this year. It's a very banal thing in a community of scientists, but 15-year-old me wouldn't have understood what a PhD does, much less my research or any of the math I deal with now, so I'm all for celebrating progress!
