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Inferring neural population dynamics from multiple partial recordings of the same neural circuit
Srinivas C Turaga · Lars Buesing · Adam M Packer · Henry Dalgleish · Noah Pettit · Michael Hausser · Jakob H Macke

Fri Dec 06 07:00 PM -- 11:59 PM (PST) @ Harrah's Special Events Center, 2nd Floor

Simultaneous recordings of the activity of large neural populations are extremely valuable as they can be used to infer the dynamics and interactions of neurons in a local circuit, shedding light on the computations performed. It is now possible to measure the activity of hundreds of neurons using 2-photon calcium imaging. However, many computations are thought to involve circuits consisting of thousands of neurons, such as cortical barrels in rodent somatosensory cortex. Here we contribute a statistical method for "stitching" together sequentially imaged sets of neurons into one model by phrasing the problem as fitting a latent dynamical system with missing observations. This method allows us to substantially expand the population-sizes for which population dynamics can be characterized---beyond the number of simultaneously imaged neurons. In particular, we demonstrate using recordings in mouse somatosensory cortex that this method makes it possible to predict noise correlations between non-simultaneously recorded neuron pairs.

Author Information

Srinivas C Turaga (Janelia Research Campus, Howard Hughes Medical Institute)
Lars Buesing (Columbia University)
Adam M Packer (UCL)
Henry Dalgleish (UCL)
Noah Pettit (UCL)
Michael Hausser (UCL)
Jakob H Macke (University of Tübingen & MPI IS Tübingen)

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