@article {46575,
	title = {Inferring neural population dynamics from multiple partial recordings of the same neural circuit.},
	journal = {Advances in Neural Information Processing Systems (NIPS) },
	volume = {26},
	year = {2013},
	month = {2013},
	abstract = {<p>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.</p>
},
	url = {http://papers.nips.cc/paper/4874-inferring-neural-population-dynamics-from-multiple-partial-recordings-of-the-same-neural-circuit},
	author = {Turaga, Srinivas C and Buesing, Lars and Packer, Adam M. and Dalgleish, Henry and Pettit, Noah and H{\"a}usser, Michael and Macke, Jakob H.}
}
