In this webinar, Dr. Fan Wu and Lidor Spivak discuss the use of artificial intelligence to automate electrophysiological data analysis, including a new cloud-based software platform.
Diagnostic Biochips has recently released DBCloud, which is a cloud-based service that allows electrophysiology researchers to store, visualize, analyze, and share data, all from the simple interface of an internet browser. This not only saves researchers from setting up expensive storage and compute resources locally, but also helps to standardize and maintain data management and analysis pipelines, which are critical for effective collaborations between different organizations.
In this webinar, we present a new feature using artificial intelligence to guide post-spikesorting curation steps that would otherwise require researchers to painstakingly and subjectively curate the spikesorting results manually. The AI algorithm learns to mimic the decisions made by human curators, and generates models that can automatically generate recommended curation steps. By leveraging the expansive database on DBCloud, we expect the AI models to improve from iterative training processes, and they can be tailored for specific types of recordings. It is conceivable that the models can reach human performance and completely eliminate the need for manual spikesorting curation.
Key Topics Include:
- General application and usage of DBCloud
- How AI-models on DBCloud can significantly improve spikesorting quality and throughput
- Learn how to participate in beta testing and become a DBCloud user
Sagol School of Neuroscience