NDLI: Neural cell type recognition between globus pallidus externus and globus pallidus internus by Gaussian mixture modeling

Content Provider	IEEE Xplore Digital Library
Author	Qiang Fu Clements, M. Mewes, K.
Copyright Year	2005
Description	Author affiliation: Sch. of Electr. & Comput. Eng., Georgia Inst. of Technol., Atlanta, GA, USA (Qiang Fu; Clements, M.)
Abstract	This paper proposes a new application of Gaussian mixture modeling (GMM) for neural cell type classification between globus pallidus externus (GPe) and globus pallidus internus (GPi). Our work is motivated by the results of previous research in which different neural cell types could be identified by their discharge patterns. It is critical for surgeons to distinguish between these two cell types to identify brain nuclei during the procedure known as a pallidotomy, a treatment for Parkinson's disease. Currently, skilled surgeons rely on discharge patterns converted to sound. In this study, performance evaluations are conducted based on a labeled database recorded during previous neural surgeries. The GMM achieves better than 92% correct recognition using 10-second segments, which demonstrates the best performing classifier to date.
Sponsorship	IEEE Signal Processing Soc
File Size	267271
File Format	PDF
ISBN	0780388747
ISSN	15206149
DOI	10.1109/ICASSP.2005.1415048
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-03-23
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Parkinson's disease Neurons Surgery Surges Degenerative diseases Timing Shape Fires Feature extraction Detection algorithms
Content Type	Text
Resource Type	Article

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