Comparing the potential of MEG and EEG to uncover brain tracking of speech temporal envelope

Available online 8 September 2018.During connected speech listening, brain activity tracks speech rhythmicity at delta (∼0.5 Hz) and theta (4–8 Hz) frequencies. Here, we compared the potential of magnetoencephalography (MEG) and high-density electroencephalography (EEG) to uncover such speech brain tracking. Ten healthy right-handed adults listened to two different 5-min audio recordings, either without noise or mixed with a cocktail-party noise of equal loudness. Their brain activity was simultaneously recorded with MEG and EEG. We quantified speech brain tracking channel-by-channel using coherence, and with all channels at once by speech temporal envelope reconstruction accuracy. In both conditions, speech brain tracking was significant at delta and theta frequencies and peaked in the temporal regions with both modalities (MEG and EEG). However, in the absence of noise, speech brain tracking estimated from MEG data was significantly higher than that obtained from EEG. Furthemore, to uncover significant speech brain tracking, recordings needed to be ∼3 times longer in EEG than MEG, depending on the frequency considered (delta or theta) and the estimation method. In the presence of noise, both EEG and MEG recordings replicated the previous finding that speech brain tracking at delta frequencies is stronger with attended speech (i.e., the sound subjects are attending to) than with the global sound (i.e., the attended speech and the noise combined). Other previously reported MEG findings were replicated based on MEG but not EEG recordings: 1) speech brain tracking at theta frequencies is stronger with attended speech than with the global sound, 2) speech brain tracking at delta frequencies is stronger in noiseless than noisy conditions, and 3) when noise is added, speech brain tracking at delta frequencies dampens less in the left hemisphere than in the right hemisphere. Finally, sources of speech brain tracking reconstructed from EEG data were systematically deeper and more posterior than those derived from MEG. The present study demonstrates that speech brain tracking is better seen with MEG than EEG. Quantitatively, EEG recordings need to be ∼3 times longer than MEG recordings to uncover significant speech brain tracking. As a consequence, MEG appears more suited than EEG to pinpoint subtle effects related to speech brain tracking in a given recording time.Florian Destoky, Julie Bertels, and Mathieu Bourguignon are supported by the program Attract of Innoviris (grant 2015-BB2B-10). Marc Vander Ghinst was supported by a research grant from the Fonds Erasme (Brussels, Belgium). Xavier De Tiège is Post-doctorate Clinical Master Specialist at the FRS-FNRS. Mathieu Bourguignon is supported by the Marie Skłodowska-Curie Action of the European Commission (grant 743562) and by the Spanish Ministry of Economy and Competitiveness (grant PSI2016-77175-P). This research project and the MEG project at the CUB Hôpital Erasme are financially supported by the Fonds Erasme (Research convention “Les Voies du Savoir”, Fonds Erasme, Brussels, Belgium)