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Dealing with correlations in the multichannel EEG using bipolar derivations and Monte Carlo simulations: application to the detection of auditory steady-state responses

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Abstract

The multichannel objective response detection (MORD) techniques are statistical methods, which use information from more than one electroencephalography (EEG) channel, to infer the presence of evoked potential. However, the correlation level between the channels can lead to a decrease in MORD performance, such as an increase in the false positive (FP) rate and/or a decrease in the detection rate (DR). The present study aims to propose a method to deal with the correlations in the multichannel EEG. The method consists of making an adjustment in the Monte Carlo simulation, considering the information between channels. The MORD techniques with and without the new method were applied to an auditory steady-state response (ASSR) database, composed of the EEG multichannel of eleven volunteers during multifrequency stimulation. The proposed method kept the FP rate at values equal to or less than the significance level of the test and led to an increase of 8.51% in the DR in relation to non-application of the method. Results of this study indicate that the proposed method is an alternative to deal with the effect of the correlation between channels in situations where MORD techniques are applied.

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Abbreviations

AM2:

Second-order exponentially modulated

aMSC:

Average of MSCs

D-aMSC:

Average of the MSCs from the bipolar derivations

DFT:

Discrete Fourier transform

D-pMSC:

Product of the MSCs from the bipolar derivations

DR:

Detection rate

EEG:

Electroencephalogram

EP:

Evoked potential

FP:

False positive

\({H}_{0}\) :

Null hypothesis

MMSC:

Multiple magnitude-squared coherence

MORD:

Multichannel objective response detector

MSC:

Magnitude-squared coherence

ORD:

Objective response detection

pMSC:

Product of MSCs

SNR:

Signal-to-noise ratio

SPL:

Sound pressure level

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Funding

This study was financed in part by CAPES, CNPq, FAPEMIG, and FAPES (EDITAL FAPES No. 03/2021 — UNIVERSAL, grant No. 457/2021).

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Authors and Affiliations

  1. Federal Institute of Education Science and Technology of Espírito Santo - São Mateus Campus, São Mateus, ES, CEP, 29932-540, Brazil

    Tiago Zanotelli

  2. Federal Institute of Education Science and Technology of Minas Gerais - Ipatinga Campus, Ipatinga, MG, Brazil

    Felipe Antunes

  3. Graduate Program in Electrical Engineering, Federal University of Minas Gerais, Belo Horizonte, MG, Brazil

    Eduardo Mazoni Andrade Marçal Mendes

  4. Department of Electrical Engineering, Federal University of Viçosa, Viçosa, MG, Brazil

    Leonardo Bonato Felix

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  1. Tiago Zanotelli
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  2. Felipe Antunes
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  4. Leonardo Bonato Felix
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Correspondence to Tiago Zanotelli.

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Work approved by the Local Ethics Committee CEP/UFV No. 2.105.334.

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Zanotelli, T., Antunes, F., Mendes, E.M.A.M. et al. Dealing with correlations in the multichannel EEG using bipolar derivations and Monte Carlo simulations: application to the detection of auditory steady-state responses. Med Biol Eng Comput 61, 811–819 (2023). https://doi.org/10.1007/s11517-022-02764-0

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