Hierarchical structure and computation of data-driven neuronal networks

Mathematical Biology Seminar
Friday, March 19, 2021 - 3:00pm for 1 hour (actually 50 minutes)
Hannah Choi – Georgia Tech – https://hannahchoi.math.gatech.edu/
Daniel Cruz

The complex connectivity structure unique to the brain network is believed to underlie its robust and efficient coding capability. Specifically, neuronal networks at multiple scales utilize their structural complexities to achieve different computational goals. I will first introduce functional implications that can be inferred from a weighted and directed “single” network representation of the brain. Then, I will consider a more detailed and realistic network representation of the brain featuring multiple types of connection between a pair of brain regions, which enables us to uncover the hierarchical structure of the brain network using an unsupervised method.  Finally, if time permits, I will discuss computational implications of the hierarchical organization of the brain network, focusing on a specific type of visual computation- predictive coding.

Meeting Link: https://gatech.bluejeans.com/348270750