Linked Life Data

10661394

Source:http://linkedlifedata.com/resource/pubmed/id/10661394

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
2
pubmed:dateCreated
2000-3-15
pubmed:abstractText
A method for extracting single-unit spike trains from extracellular recordings containing the activity of several simultaneously active cells is presented. The technique is particularly effective when spikes overlap temporally. It is capable of identifying the exact number of neurons contributing to a recording and of creating reliable spike templates. The procedure is based on fuzzy clustering and its performance is controlled by minimizing a cluster-validity index which optimizes the compactness and separation of the identified clusters. Application examples with synthetic spike trains generated from real spikes and segments of background noise show the advantage of the fuzzy method over conventional template-creation approaches in a wide range of signal-to-noise ratios.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Feb
pubmed:issn
0169-2607
pubmed:author
pubmed:issnType
Print
pubmed:volume
61
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
91-8
pubmed:dateRevised
2006-11-15
pubmed:meshHeading
pubmed:year
2000
pubmed:articleTitle
Identification of reliable spike templates in multi-unit extracellular recordings using fuzzy clustering.
pubmed:affiliation
Department of Neurosurgery, University of Texas-Houston Medical School, 77030, USA. zouridakis@uth.tmc.edu
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, Non-P.H.S.