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McKelvey School of Engineering

Learning about the Brain Using Mathematical and Statistical Models

Tuesday, January 19 | 3:00 PM - 4:00 PM

Virtual Event

Geoffrey Goodhill, Professor, Queensland Brain Institute

Learning about learning in the brain using mathematical and statistical models

Register for the virtual event here.

Abstract: As the brain develops it adapts to the statistical structure of the environment. While supervised learning algorithms such as deep learning have proven very powerful for practical applications, we still have much to discover about the unsupervised methods that drive early adaptation and learning in real brains. First, I will discuss work that suggests how maps of visual features in the mammalian cortex may develop according to an optimisation principle that can be mapped onto the traveling salesman problem. This successfully predicts how maps of ocular dominance and orientation selectivity change in response to altered environmental input. Second I will discuss our more recent work looking at the early development of neural activity in the zebrafish brain, and how this is related to the development of the fish's behavior. This includes developing a community detection algorithm for identifying groups of neurons that fire together, a Hebbian model for understanding how such groups might form, and a latent variable model for separating evoked from spontaneous activity. In the long term we hope that understanding more about the computational principles driving neural development will help inspire new advances in artificial intelligence.

Event Type

Seminar/Colloquia

Schools

McKelvey School of Engineering

Website

https://cse.wustl.edu/news-events/col...

Department
Computer Science & Engineering
Event Contact

s.andrew@wustl.edu

Speaker Information

Prof Goodhill originally trained in Mathematics, Physics, Artificial Intelligence and Cognitive Science in the UK. He then spent 10 years in the USA, including 8 as Professor at Georgetown University in Washington DC, where he was awarded tenure 2 years early. He moved to the University of Queensland in 2005. He has published over 100 peer-reviewed papers including in Nature Neuroscience, 4 in Neuron, 4 in PNAS and 8 in Trends in Neurosciences. In 2014 he received the Paxinos-Watson prize from the Australasian Neuroscience Society for a paper in Neuron. Since moving to Australia he has been awarded an NHMRC Investigator grant, 12 ARC Discovery and NHMRC Project grants and a Simons Foundation grant as lead PI, as well as numerous other national and international grants as a co-PI. He has trained over 30 PhD students and postdocs, many of whom are now faculty members in universities worldwide, or work as scientists in tech companies such as Google Deepmind. From 2005-2010 he was Editor-in-Chief of the journal Network: Computation in Neural Systems, and he is currently on the Editorial Boards of Neural Computation and Brain Informatics. He has reviewed manuscripts for over 60 different journals and grants for 15 different research agencies worldwide. In 2006 he founded the Australian Workshop on Computational Neuroscience which now runs annually, and in 2015 he founded the Systems and Computational Neuroscience DownUnder (SCiNDU) conference which now runs bi-annually. During his career he has taught courses in Medical Neuroscience, Developmental Neuroscience, Mathematical Neuroscience, Numerical Methods and Scientific Computing. Besides giving many radio interviews and public lectures about his work he has also written several articles for The Conversation and given a TEDx talk.

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