Literature DB >> 33571299

Effect of number and placement of EEG electrodes on measurement of neural tracking of speech.

Jair Montoya-Martínez1,2, Jonas Vanthornhout1, Alexander Bertrand3, Tom Francart1.   

Abstract

Measurement of neural tracking of natural running speech from the electroencephalogram (EEG) is an increasingly popular method in auditory neuroscience and has applications in audiology. The method involves decoding the envelope of the speech signal from the EEG signal, and calculating the correlation with the envelope of the audio stream that was presented to the subject. Typically EEG systems with 64 or more electrodes are used. However, in practical applications, set-ups with fewer electrodes are required. Here, we determine the optimal number of electrodes, and the best position to place a limited number of electrodes on the scalp. We propose a channel selection strategy based on an utility metric, which allows a quick quantitative assessment of the influence of a channel (or a group of channels) on the reconstruction error. We consider two use cases: a subject-specific case, where the optimal number and position of the electrodes is determined for each subject individually, and a subject-independent case, where the electrodes are placed at the same positions (in the 10-20 system) for all the subjects. We evaluated our approach using 64-channel EEG data from 90 subjects. In the subject-specific case we found that the correlation between actual and reconstructed envelope first increased with decreasing number of electrodes, with an optimum at around 20 electrodes, yielding 29% higher correlations using the optimal number of electrodes compared to all electrodes. This means that our strategy of removing electrodes can be used to improve the correlation metric in high-density EEG recordings. In the subject-independent case, we obtained a stable decoding performance when decreasing from 64 to 22 channels. When the number of channels was further decreased, the correlation decreased. For a maximal decrease in correlation of 10%, 32 well-placed electrodes were sufficient in 91% of the subjects.

Entities:  

Year:  2021        PMID: 33571299      PMCID: PMC7877609          DOI: 10.1371/journal.pone.0246769

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.240


  27 in total

1.  Emergence of neural encoding of auditory objects while listening to competing speakers.

Authors:  Nai Ding; Jonathan Z Simon
Journal:  Proc Natl Acad Sci U S A       Date:  2012-07-02       Impact factor: 11.205

2.  Analysis of Miniaturization Effects and Channel Selection Strategies for EEG Sensor Networks With Application to Auditory Attention Detection.

Authors:  Abhijith Mundanad Narayanan; Alexander Bertrand
Journal:  IEEE Trans Biomed Eng       Date:  2019-04-17       Impact factor: 4.538

3.  Decoding the auditory brain with canonical component analysis.

Authors:  Alain de Cheveigné; Daniel D E Wong; Giovanni M Di Liberto; Jens Hjortkjær; Malcolm Slaney; Edmund Lalor
Journal:  Neuroimage       Date:  2018-01-31       Impact factor: 6.556

4.  Speech Intelligibility Predicted from Neural Entrainment of the Speech Envelope.

Authors:  Jonas Vanthornhout; Lien Decruy; Jan Wouters; Jonathan Z Simon; Tom Francart
Journal:  J Assoc Res Otolaryngol       Date:  2018-02-20

5.  The association between hearing impairment and neural envelope encoding at different ages.

Authors:  Tine Goossens; Charlotte Vercammen; Jan Wouters; Astrid van Wieringen
Journal:  Neurobiol Aging       Date:  2018-10-11       Impact factor: 4.673

6.  Cortical Response to the Natural Speech Envelope Correlates with Neuroimaging Evidence of Cognition in Severe Brain Injury.

Authors:  Chananel Braiman; Esteban A Fridman; Mary M Conte; Henning U Voss; Chagit S Reichenbach; Tobias Reichenbach; Nicholas D Schiff
Journal:  Curr Biol       Date:  2018-11-21       Impact factor: 10.834

7.  Theta, beta and gamma rate modulations in the developing auditory system.

Authors:  Sophie Vanvooren; Michael Hofmann; Hanne Poelmans; Pol Ghesquière; Jan Wouters
Journal:  Hear Res       Date:  2015-06-25       Impact factor: 3.208

8.  Human cortical responses to the speech envelope.

Authors:  Steven J Aiken; Terence W Picton
Journal:  Ear Hear       Date:  2008-04       Impact factor: 3.570

Review 9.  Cortical entrainment to continuous speech: functional roles and interpretations.

Authors:  Nai Ding; Jonathan Z Simon
Journal:  Front Hum Neurosci       Date:  2014-05-28       Impact factor: 3.169

10.  The Multivariate Temporal Response Function (mTRF) Toolbox: A MATLAB Toolbox for Relating Neural Signals to Continuous Stimuli.

Authors:  Michael J Crosse; Giovanni M Di Liberto; Adam Bednar; Edmund C Lalor
Journal:  Front Hum Neurosci       Date:  2016-11-30       Impact factor: 3.169

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  3 in total

Review 1.  Linear Modeling of Neurophysiological Responses to Speech and Other Continuous Stimuli: Methodological Considerations for Applied Research.

Authors:  Michael J Crosse; Nathaniel J Zuk; Giovanni M Di Liberto; Aaron R Nidiffer; Sophie Molholm; Edmund C Lalor
Journal:  Front Neurosci       Date:  2021-11-22       Impact factor: 4.677

2.  Behavioral Account of Attended Stream Enhances Neural Tracking.

Authors:  Moïra-Phoebé Huet; Christophe Micheyl; Etienne Parizet; Etienne Gaudrain
Journal:  Front Neurosci       Date:  2021-12-13       Impact factor: 4.677

3.  Assessing Distinct Cognitive Workload Levels Associated with Unambiguous and Ambiguous Pronoun Resolutions in Human-Machine Interactions.

Authors:  Mengyuan Zhao; Zhangyifan Ji; Jing Zhang; Yiwen Zhu; Chunhua Ye; Guangying Wang; Zhong Yin
Journal:  Brain Sci       Date:  2022-03-11
  3 in total

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