The Montreal Artificial Intelligence and Neuroscience (MAIN) conference will kick off on Sunday, December 9, with two days of lectures followed by a two-day programming workshop. Now in its second year, the gathering attracts researchers working at the intersection of AI and Neuroscience in dynamic and interconnected Montreal-based hubs. HBHL caught up with co-organizer Dr. Bratislav Misic, who leads an interdisciplinary research team at the Montreal Neurological Institute (MNI).
What can neuroscience learn from AI?
Today, AI algorithms provide powerful approaches to addressing a wide range of important neuroscience questions. The future impact and progress in both Neuroscience and AI will strongly depend on a more efficient synergy between the research communities in the two fields. But, it goes both ways. There is knowledge about how the brain works that people in AI can learn from and apply to more realistic and more optimal artificial neural networks. For neuroscientists, AI can provide basic tools for analyzing brain data or performing quality control on an MRI. On a deeper level, AI can teach us a lot about the best way a network can learn to represent a function in the outside world. For example, if something works in AI, is there evidence of something similar in the brain?
What does it mean to be at the intersection of AI and Neuroscience?
It’s an area that is very much on the rise. We’re now seeing a new generation of students who are really comfortable with the quantitative and computational aspects but are also trained in biology and physiology. They speak both languages. There is an emerging lingua franca that straddles both disciplines. The goal of this meeting is to foster links. These are people who want to work with each other. It's genuinely a two-way street.
A two-day workshop will follow the conference. What will students get out of it?
There has been a great tradition of having hackathons -- opportunities to learn that are not so exclusive, whether it’s something simple like using Github or more complex, such as how to use machine learning. The workshop is organized to be very hands-on with lots of peer learning, and the leaders will make sure everyone is on track. It is a different way of teaching and getting students on board with this new discipline.
How can these exchanges inform your work at the MNI?
The way the two disciplines come together is by allowing ideas and data to travel back and forth. The NeuroHub, the Open Science initiative, the Canadian Neuroscience Open Platform (CONP), all based at the MNI, are initiatives to make data sharing and analysis easier. If you have expertise in computer science, you will be able to take advantage of the data now being made available. It’s a means to democratize data access.
Main 2018 takes place from 9-12 December at l’Université de Montréal. HBHL is a partner in this event, which is benefits from two CFREF-funded initiatives: HBHL under the Knowledge Mobilization program and IVADO.