| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 6009095 | Clinical Neurophysiology | 2011 | 6 Pages |
ObjectiveTo design a fast algorithm that evaluates the degree of correlation of recordings among single trials (CoRaST) for mismatch negativity (MMN) activity.MethodsThe participants were 114 children, aged 8-16Â years. MMNs were elicited by two deviants in duration that occurred in an uninterrupted sound within a passive oddball paradigm, and each trial lasted 650Â ms with 130 samples. CoRaST was derived from the frequency-domain MMN model through Fourier transformation. To validate the effectiveness of the proposed method, the wavelet transformation-based inter-trial coherence (ITC) was taken as a reference.ResultsPerformances of the proposed CoRaST and ITC were similar in evaluating the correlation of MMN activity among single trials. However, the analysis of electroencephalograph (EEG) recordings comprising approximately 330 trials at one channel took approximately 0.12Â s with CoRaST, whereas ITC required approximately 45Â s in our workstation.ConclusionsCoRaST has the potential to evaluate the correlation of MMN activity among single trials in a real-time system. Furthermore, the new method can be facilitated to study other event-related potentials (ERPs) of evoked or induced brain activity.SignificanceThe correlation of ERP activity among single trials can be immediately inspected during the ERP data collection in a real-time system.
⺠CoRaST and ITC measure the correlation of 330 single trials' EEG recordings in 0.12 second and 45 seconds with the normal workstation, respectively. ⺠The correlation of ERP activity among single trials can be immediately inspected during the ERP data collection in a real-time system with CoRaST. ⺠CoRaST can be facilitated to study event-related potentials of evoked and induced brain activities simultaneously.
