The extraction of LRP via functional data analysis techniques

Yan Bin Zhao, Jian Tao, Ning Zhong Shi, Ming Zhang, Jie Sui

Research output: Contribution to journalArticle

Abstract

A new strategy based on functional data analysis (FDA) techniques is proposed to extract the lateralized readiness potential (LRP), which treats electroencephalographic data as functional data. This FDA-based method combines longitudinal information from each trial (time series data) with cross-sectional information from all trials at a fixed time point (cross-sectional data). The comparison results show that the FDA-based LRP is closer to the assumed true LRP and is more robust against a reduction in the number of trials than the traditional average-based LRP. Furthermore, the results indicate that the onset of an FDA-based LRP is more accurate than that of an average-based LRP under several measuring criteria.

Original languageEnglish
Pages (from-to)94-101
Number of pages8
JournalJournal of Neuroscience Methods
Volume206
Issue number1
Early online date22 Feb 2012
DOIs
Publication statusPublished - 30 Apr 2012

Keywords

  • Functional data analysis
  • Lateralized readiness potential
  • Onset latency measurement

ASJC Scopus subject areas

  • Neuroscience(all)

Fingerprint Dive into the research topics of 'The extraction of LRP via functional data analysis techniques'. Together they form a unique fingerprint.

Cite this