Combination of PCA and LORETA for sources analysis of ERP data: An emotional processing study

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

Abstract

The purpose of this paper is to study spatiotemporal patterns of neuronal activity in emotional processing by analysis of ERP data. 108 pictures (categorized as positive, negative and neutral) were presented to 24 healthy, right-handed subjects while 128-channel EEG data were recorded. An analysis of two steps was applied to the ERP data. First, principal component analysis was performed to obtain significant ERP components. Then LORETA was applied to each component to localize their brain sources. The first six principal components were extracted, each of which showed different spatiotemporal patterns of neuronal activity. The results agree with other emotional study by fMRI or PET. The combination of PCA and LORETA can be used to analyze spatiotemporal patterns of ERP data in emotional processing.

Original languageEnglish
Title of host publicationMedical Imaging 2006
Subtitle of host publicationPhysiology, Function, and Structure from Medical Images
DOIs
StatePublished - 2006
Externally publishedYes
EventMedical Imaging 2006: Physiology, Function, and Structure from Medical Images - San Diego, CA, United States
Duration: 12 Feb 200614 Feb 2006

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume6143 II
ISSN (Print)1605-7422

Conference

ConferenceMedical Imaging 2006: Physiology, Function, and Structure from Medical Images
Country/TerritoryUnited States
CitySan Diego, CA
Period12/02/0614/02/06

Keywords

  • Emotional processing
  • LORETA
  • Principal component analysis (PCA)

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