Weighted kernel density estimation of the prepulse inhibition test

Hongbo Zhou, Qiang Cheng, Hong Ju Yang, Haiyun Xu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Prepulse inhibition (PPI) refers to the reduction in startle reaction towards a startle-eliciting "pulse" stimulus when it is shortly preceded by a sub-threshold "prepulse" stimulus. PPI deficits have been seen in patients with schizophrenia and animal models of this mental disorder. The goal of this study was to provide an alternative method for the analysis of PPI data. The new method is expected to be more reliable and sensitive than the existing conventional method. We applied the Kernel density estimation (KDE) in the analysis of PPI data. KDE is a non-parametric method of estimating the probability density function of a random variable and is widely used in inferring population statistics based on limited, noisy samples of continuous random variables. Our results showed that the KDE method performed better than the conventional method and offered some advantages which are of significant in the post-session analysis of PPI data and in performing animal experiments.

Original languageEnglish
Title of host publicationProceedings - 2010 6th World Congress on Services, Services-1 2010
Pages291-297
Number of pages7
DOIs
StatePublished - 2010
Event2010 6th World Congress on Services, Services-1 2010 - Miami, FL, United States
Duration: 5 Jul 201010 Jul 2010

Publication series

NameProceedings - 2010 6th World Congress on Services, Services-1 2010

Conference

Conference2010 6th World Congress on Services, Services-1 2010
Country/TerritoryUnited States
CityMiami, FL
Period5/07/1010/07/10

Keywords

  • Kernel density estimation
  • Prepulse inhibitation test
  • Startle response

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