A New Method to Detect Event-Related Potentials Based on Pearson's Correlation

EURASIP Journal on Bioinformatics and Systems Biology (2016)

17 Pages Posted: 23 May 2015 Last revised: 6 Jun 2017

Date Written: October 8, 2015

Abstract

Event-Related Potentials (ERPs) are widely used in Brain-Computer Interface applications and in neuroscience.

Normal EEG activity is rich in background noise and therefore, in order to detect ERPs, it is usually necessary to take the average from multiple trials to reduce the effects of this noise.

The noise produced by EEG activity itself is not correlated with the ERP waveform and so, by calculating the average, the noise is decreased by a factor inversely proportional to the square root of N, where N is the number of averaged epochs.

This is the easiest strategy currently used to detect ERPs, which is based on calculating the average of each ERP’s waveform, these waveforms being time-and phase-locked.

In this paper a new method called GW6 is proposed, which calculates the ERP using a mathematical method based only on Pearson's Correlation.

This results in a graph with the same time resolution as the classical ERP and which contains only positive peaks representing the increase – in consonance to the stimuli – in EEG signal correlation over all channels.

This new method is also useful for selectively identifying and highlighting any hidden components of the ERP response that are not phase-locked, and that are usually hidden in the standard and simple method based on the averaging of all the epochs.

These hidden components seem to be caused by variations (between each successive stimulus) of the ERP's inherent phase latency period (jitter), although the same stimulus across all EEG channels produces a reasonably constant phase.

For this reason, this new method could be very helpful to investigate these hidden components of the ERP response and to develop applications for scientific and medical purposes.

Moreover, this new method is more resistant to EEG artifacts than the standard calculations of the average.

The method we are proposing can be directly used in the form of a process written in the well known Matlab programming language and can be easily and quickly written in any other software language.

Keywords: Event-Related Potentials; Brain-Computer-Interfaces; Pearson’s correlation

Suggested Citation

Giroldini, William and Pederzoli, Luciano and Bilucaglia, Marco and Melloni, Simone and Tressoldi, Patrizio E., A New Method to Detect Event-Related Potentials Based on Pearson's Correlation (October 8, 2015). EURASIP Journal on Bioinformatics and Systems Biology (2016). Available at SSRN: https://ssrn.com/abstract=2609008 or http://dx.doi.org/10.2139/ssrn.2609008

William Giroldini

EvanLab ( email )

Firenze
Italy

Luciano Pederzoli

University of Padova ( email )

Via 8 Febbraio
Padova, 2-35122
Italy

Marco Bilucaglia

EvanLab ( email )

Firenze
Italy

IULM University ( email )

Milan
Italy

Simone Melloni

EvanLab ( email )

Firenze
Italy

Patrizio E. Tressoldi (Contact Author)

Università di Padova ( email )

via Venezia 8
Padova, 35131
Italy

HOME PAGE: http://www.patriziotressoldi.it

Register to save articles to
your library

Register

Paper statistics

Downloads
58
Abstract Views
464
rank
362,921
PlumX Metrics