On the Separation of Signals from Neighboring Cells in Tetrode Recordings
Abstract
We discuss a solution to the problem of separating waveforms pro(cid:173) duced by multiple cells in an extracellular neural recording. We take an explicitly probabilistic approach, using latent-variable mod(cid:173) els of varying sophistication to describe the distribution of wave(cid:173) forms produced by a single cell. The models range from a single Gaussian distribution of waveforms for each cell to a mixture of hidden Markov models. We stress the overall statistical structure of the approach, allowing the details of the generative model chosen to depend on the specific neural preparation.
Cite
Text
Sahani et al. "On the Separation of Signals from Neighboring Cells in Tetrode Recordings." Neural Information Processing Systems, 1997.Markdown
[Sahani et al. "On the Separation of Signals from Neighboring Cells in Tetrode Recordings." Neural Information Processing Systems, 1997.](https://mlanthology.org/neurips/1997/sahani1997neurips-separation/)BibTeX
@inproceedings{sahani1997neurips-separation,
title = {{On the Separation of Signals from Neighboring Cells in Tetrode Recordings}},
author = {Sahani, Maneesh and Pezaris, John S. and Andersen, Richard A.},
booktitle = {Neural Information Processing Systems},
year = {1997},
pages = {222-228},
url = {https://mlanthology.org/neurips/1997/sahani1997neurips-separation/}
}