Multivariate evoked response detection based on the spectral F-test

• Published in: Journal of neuroscience methods Vol. 264; pp. 113 - 118
• Main Authors: Rocha, Paulo Fábio F., Felix, Leonardo B., Miranda de Sá, Antonio Mauricio F.L., Mendes, Eduardo M.A.M.
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier B.V 01.05.2016
• Subjects: Detection; EEG; Electroencephalography - methods; Evoked Potentials - physiology; Evoked response; Humans; Multivariate detector; Signal Processing, Computer-Assisted; Spectral F-test; Spectral F-test; Evoked response; Multivariate detector; Detection; EEG
• ISSN: 0165-0270; 1872-678X
• DOI: 10.1016/j.jneumeth.2016.03.005

•We propose a new multivariate objective response detector based in the spectral F-test.•Detector's performance increases with number of signals.•The false positive rate does not change with increasing number of signals.•Results in EEG data showed significant improvement when two or more signals were used. Objective response detection techniques, such as magnitude square coherence, component synchrony measure, and the spectral F-test, have been used to automate the detection of evoked responses. The performance of these detectors depends on both the signal-to-noise ratio (SNR) and the length of the electroencephalogram (EEG) signal. Recently, multivariate detectors were developed to increase the detection rate even in the case of a low signal-to-noise ratio or of short data records originated from EEG signals. In this context, an extension to the multivariate case of the spectral F-test detector is proposed. The performance of this technique is assessed using Monte Carlo. As an example, EEG data from 12 subjects during photic stimulation is used to demonstrate the usefulness of the proposed detector. The multivariate method showed detection rates consistently higher than those ones when only one signal was used. It is shown that the response detection in EEG signals with the multivariate technique was statistically significant if two or more EEG derivations were used.