Statistical Modeling of Cell Assemblies Activities in Associative Cortex of Behaving Monkeys
Abstract
So far there has been no general method for relating extracellular electrophysiological measured activity of neurons in the associative cortex to underlying network or "cognitive" states. We propose to model such data using a multivariate Poisson Hidden Markov Model. We demonstrate the application of this approach for tem(cid:173) poral segmentation of the firing patterns, and for characterization of the cortical responses to external stimuli. Using such a statisti(cid:173) cal model we can significantly discriminate two behavioral modes of the monkey, and characterize them by the different firing pat(cid:173) terns, as well as by the level of coherency of their multi-unit firing activity. Our study utilized measurements carried out on behaving Rhesus monkeys by M. Abeles, E. Vaadia, and H. Bergman, of the Hadassa Medical School of the Hebrew University.
Cite
Text
Gat and Tishby. "Statistical Modeling of Cell Assemblies Activities in Associative Cortex of Behaving Monkeys." Neural Information Processing Systems, 1992.Markdown
[Gat and Tishby. "Statistical Modeling of Cell Assemblies Activities in Associative Cortex of Behaving Monkeys." Neural Information Processing Systems, 1992.](https://mlanthology.org/neurips/1992/gat1992neurips-statistical/)BibTeX
@inproceedings{gat1992neurips-statistical,
title = {{Statistical Modeling of Cell Assemblies Activities in Associative Cortex of Behaving Monkeys}},
author = {Gat, Itay and Tishby, Naftali},
booktitle = {Neural Information Processing Systems},
year = {1992},
pages = {945-952},
url = {https://mlanthology.org/neurips/1992/gat1992neurips-statistical/}
}