Detecting EEG evoked responses for target image search with mixed effect models.

Yonghong Huang, Deniz Erdogmus, Santosh Mathan, Misha Pavel

Research output: Contribution to journalArticle

Abstract

There is evidence that brain signals associated with perceptual processes can be used for target image search. We describe the application of mixed effect models (MEMs) to brain signature detection. We develop an MEM detector for detecting brain evoked responses generated by perceptual processes in the human brain associated with detecting novel target stimuli. We construct the model using principal component analysis and linear discriminant analysis (LDA) bases. We adopt the LDA for dimension reduction. For parameter regularization we use 10-fold cross validation and report experimental results from six subjects. Four out of six subjects achieve very good detection performance with more than 0.9 areas under receiver operating characteristic curves. The results demonstrate that the MEM can provide reliable inference on single-trial ERP detection on the task of target image search.

Original languageEnglish (US)
Pages (from-to)4988-4991
Number of pages4
JournalConference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference
StatePublished - 2008
Externally publishedYes

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Electroencephalography
Brain
Discriminant Analysis
Discriminant analysis
Enterprise resource planning
Principal Component Analysis
ROC Curve
Principal component analysis
Detectors

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Biomedical Engineering
  • Health Informatics

Cite this

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