Finding needles in the neural haystack: unsupervised analyses of noisy data

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• Marine Schimel, Kris Jensen, Department of Engineering
• Wednesday 01 December 2021, 17:00-18:00
• Zoom.

If you have a question about this talk, please contact Katharina Zuhlsdorff.

https://us02web.zoom.us/j/85395342039

In modern neuroscience, we often want to extract information from recordings of many neurons in the brain. Unfortunately, the activity of individual neurons is very noisy, making it difficult to relate to cognition and behavior. Thankfully, we can use the correlations across time and neurons to denoise the data we record. In particular, using recent advances in machine learning, we can build models which harness this structure in the data to extract more interpretable signals. In this talk, we present two such methods as well as examples of how they can help us gain further insights into the neural underpinnings of behavior.

This talk is part of the CamBRAIN Virtual Journal Club series.

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