KSC Seminar Series: Using Network Structure to Predict Activity in Neural Networks

Presented by Dr. Caitlyn Parmelee, Mathematics: With the advancement of the technology used to map neural networks and record brain activity, there is increasingly more data for the construction of connectomes, or complete maps of neural networks. C. elegans, a tiny roundworm with 302 neurons and around 7,000 synapses, was the first organism for which scientists mapped a complete connectome in 1982. Since then, further progress has been made on the connectomes for other organisms such as flies, zebrafish, and mice. Despite the wealth of connectivity information available, an important question remains unanswered: How does the structure of neural connectivity affect the behavior of the network? Using a particular neural network model called the Combinatorial Threshold-Linear Network model, we will explore how particular patterns of connections can lead to different patterns of firing rate activity with the goal of predicting neural activity from network structure.

Presented live in Mason Library 240 and via Zoom: https://keene.zoom.us/j/87527648670 (no registration needed).

Learn more at http://keene.presence.io/event/ksc-seminar-series-using-network-structure-to-predict-activity-in-neural-networks

This event is part of the Owlnet calendar.