Journal
JOURNAL OF NEUROSCIENCE METHODS
Volume 122, Issue 1, Pages 43-57Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/S0165-0270(02)00276-5
Keywords
data clustering; expectation-maximization; antennal lobe; locust; sampling jitter; multi-electrode; tetrode
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Funding
- NCRR NIH HHS [P41RR09754] Funding Source: Medline
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We have developed a simple and expandable procedure for classification and validation of extracellular data based on a probabilistic model of data generation. This approach relies on an empirical characterization of the recording noise. We first use this noise characterization to optimize the clustering of recorded events into putative neurons. As a second step, we use the noise model again to assess the quality of each cluster by comparing the within-cluster variability to that of the noise. This second step can be performed independently of the clustering algorithm used, and it provides the user with quantitative as well as visual tests of the quality of the classification. (C) 2002 Elsevier Science B.V. All rights reserved.
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