Scalable Spike Localization in Extracellular Recordings using Amortized Variational Inference
Date:
Extracellular recordings using modern, dense probes provide detailed footprints of action potentials (spikes) from thousands of neurons simultaneously. Inferring the activity of single neurons from these recordings, however, is a complex blind source separation problem, complicated both by the high intrinsic data dimensionality and large data volume. Despite these complications, dense probes can allow for the estimation of a spike’s source location, a powerful feature for determining the firing neuron’s position and identity in the recording. At this talk, I present a novel, generative model for inferring the source of individual spikes given observed electrical traces.