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We study neural representations in large-scale population recordings from cortex and beyond.
The coordinated activity of large populations of neurons gives rise to perception, decision and action. The rules by which this activity is coordinated are not well understood, mainly because up to now we have not extracted enough information from the brain. Our lab records from populations of up to 50,000 neurons simultaneously, using two-photon calcium imaging with a large field of view mesoscope. We use machine learning techniques to investigate the structure of the recorded activity patterns, either in response to external stimuli, or in response to the animal's own actions.
Here are 50,000 neurons recorded at 3Hz from mouse visual cortex. The left plane is in the superficial layers, while the right plane is in the input layer 4.
To support this work, we are continuously developing data analysis software, like Suite2p, Cellpose, Kilosort and Facemap, and share these with the rest of the community. We also share our data and analysis code publicly and are committed to open, collaborative science. Learn more about our work from this twitter thread (or this one, or this one).