Can connectomics help us understand the brain and sustain the revolution in AI?
3 short talks and a panel discussion on the topic of "Can connectomics help us understand the brain and sustain the revolution in AI?" Expect beautiful connectomics data, provocative dreaming, realistic critiques and everything in between. Students & post-docs, stay on to meet our 3 amazing speakers. Moderator: Dr Greg Jefferis https://www2.mrc-lmb.cam.ac.uk/group-leaders/h-to-m/gregory-jefferis/
SpikeInterface
Much development has been directed toward improving the performance and automation of spike sorting. This continuous development, while essential, has contributed to an over-saturation of new, incompatible tools that hinders rigorous benchmarking and complicates reproducible analysis. To address these limitations, we developed SpikeInterface, a Python framework designed to unify preexisting spike sorting technologies into a single codebase and to facilitate straightforward comparison and adoption of different approaches. With a few lines of code, researchers can reproducibly run, compare, and benchmark most modern spike sorting algorithms; pre-process, post-process, and visualize extracellular datasets; validate, curate, and export sorting outputs; and more. In this presentation, I will provide an overview of SpikeInterface and, with applications to real and simulated datasets, demonstrate how it can be utilized to reduce the burden of manual curation and to more comprehensively benchmark automated spike sorters.