Talk Abstract: In a 2009 TED talk, a well-known neuroscientist announced that within 10 years, we would be able to reconstruct the brain in a computer. Almost 15 years later, this moving target still seems out of reach, but a systematic framework has been clearly established. In this seminar presentation, I will discuss how scientists attempt to tackle this grand challenge. After discussing the importance of modeling in science, engineering, and medicine, I will highlight the impressive complexity of the brain, and, for perspective, I will compare it with the complexity of modern CPUs and deep learning models. I will then summarize the approach exemplified by the Blue Brain Project to reconstruct the brain using biophysically-detailed models of neurons. I will conclude with examples of simplification used to simulate a whole -- albeit very simplified -- brain in silico, and give some examples of how such approaches can help in clinical applications and in fundamental neuroscience.  

Bio: Christian O’Reilly received his B.Ing (electrical eng.; 2007), his M.Sc.A. (biomedical eng.; 2011), and his Ph.D. (biomedical eng.; 2012) from the École Polytechnique de Montréal where he worked under the mentoring of Pr. R. Plamondon to apply pattern recognition and machine learning to predict brain stroke risks. Between 2012 and 2018, he pursued postdoctoral studies in various institutions (Université de Montréal, Mcgill, EPFL) studying sleep and autism, using different approaches from neuroimaging and computational neuroscience. In 2020, he accepted a position as a research associate at McGill where he studied brain connectivity in autism and related neurodevelopmental disorders. Since 2021, Christian joined the Department of Computer Science and Engineering, the Artificial Intelligence Institute (AIISC), and the Carolina Autism and Neurodevelopment (CAN) research center at the University of South Carolina as an assistant professor in neuroscience and artificial intelligence.