title: Phase space analysis of Event Related Potential during episodic memory retrieval.
abstract: In this study we have used recurrence analysis (RA) to classify ERPs that appear from episodic memory retrieval in old/new recognition task. Since RA is based on embedding phase space, we have used correlation dimension and autocorrelation function in order to estimate embedding dimension and the lag time between successive components of each of embedding space vectors alternatively. According to RA the rates of classification have been improved in comparison to previous study. We have obtained 98.9% accuracy for train data and 97.7% for test data. Furthermore we could classify ERPs with line interference noise using RA.
authors.affiliation: Department of Biomedical Engineering, Islamic Azad University, Mashhad Branch, Mashhad, Iran. ghoshuni@gmail.com
authors.forename: M
authors.initials: M
authors.lastname: Ghoshuni
authors.forename: A M
authors.initials: AM
authors.lastname: Nasrabadi
authors.forename: M A
authors.initials: MA
authors.lastname: Khalilzadeh
authors.forename: M R
authors.initials: MR
authors.lastname: Hashemi
mesh_terms: D000465:Algorithms; D003627:Data Interpretation, Statistical; D004569:Electroencephalography / Q000295:instrumentation*; D004867:Equipment Design; D005071:Evoked Potentials; D006801:Humans; D008297:Male; D008568:Memory; D008606:Mental Processes; D015233:Models, Statistical; D008962:Models, Theoretical; D011930:Reaction Time; D015203:Reproducibility of Results; D012815:Signal Processing, Computer-Assisted