Master AI and Machine Learning: From Neural Networks to Applications
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Explore how topological data analysis reveals the hidden structure of spontaneous neural activity in zebrafish visual systems through this research presentation by Nikki Sanderson from Brown University. Discover the application of persistent homology and Betti curves to analyze calcium imaging data from approximately 2000 neurons recorded over one hour, examining how neuronal assemblies in the optic tectum activate even without visual stimuli. Learn about the identification of glutamatergic, GABAergic, and cholinergic neurons through immunostaining techniques and understand how topological methods uncover low-rank correlation structures that traditional spectral analyses might miss. Examine the sliding window analysis approach that clusters spontaneous activations into distinct dynamic profiles, leading to new hypotheses about cholinergic neurons' role in recruiting and maintaining assembly activity. Gain insights into how these findings contribute to our understanding of visual attention mechanisms and the functional organization of neural networks in developing visual systems.
Syllabus
Topological analysis of neuronal assemblies = low-rank structure modulated by cholinergic activity
Taught by
Fields Institute