Statistical Inference for Assessing Functional Connectivity of Neuronal Ensembles With Sparse Spiking Data

Statistical Inference for Assessing Functional Connectivity of Neuronal Ensembles With Sparse Spiking Data

The ability to accurately infer functional connectivity between ensemble neurons using experimentally acquired spike train data is currently an important research objective in computational neuroscience. Point process generalized linear models and maximum likelihood estimation have been proposed as...

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Bibliographic Details
Main Authors: Ghosh, S., Chen, Zhe, Putrino, David F., Barbieri, Riccardo, Brown, Emery N., Tseng, Mitchell, Sharif, Naubaha
Other Authors: Harvard University--MIT Division of Health Sciences and Technology
Format: Article
Language:en_US
Published: Institute of Electrical and Electronics Engineers (IEEE) 2012
Online Access:http://hdl.handle.net/1721.1/70044
https://orcid.org/0000-0003-2668-7819
https://orcid.org/0000-0002-6166-448X

Internet

http://hdl.handle.net/1721.1/70044
https://orcid.org/0000-0003-2668-7819
https://orcid.org/0000-0002-6166-448X

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