Influence of auditory attention on sentence recognition captured by the neural phase

Measuring the cortical tracking of speech with optically-pumped magnetometers

During continuous speech listening, brain activity tracks speech rhythmicity at frequencies matching with the repetition rate of phrases (0.2-1.5 Hz), words (2-4 Hz) and syllables (4-8 Hz). Here, we evaluated the applicability of wearable MEG based on optically-pumped magnetometers (OPMs) to measure such cortical tracking of speech (CTS). Measuring CTS with OPMs is a priori challenging given the complications associated with OPM measurements at frequencies below 4 Hz, due to increased intrinsic interference and head movement artifacts. Still, this represents an important development as OPM-MEG provides lifespan compliance and substantially improved spatial resolution compared with classical MEG. In this study, four healthy right-handed adults listened to continuous speech for 9 min. The radial component of the magnetic field was recorded simultaneously with 45-46 OPMs evenly covering the scalp surface and fixed to an additively manufactured helmet which fitted all 4 participants. We estimated CTS with reconstruction accuracy and coherence, and determined the number of dominant principal components (PCs) to remove from the data (as a preprocessing step) for optimal estimation. We also identified the dominant source of CTS using a minimum norm estimate. CTS estimated with reconstruction accuracy and coherence was significant in all 4 participants at phrasal and word rates, and in 3 participants (reconstruction accuracy) or 2 (coherence) at syllabic rate. Overall, close-to-optimal CTS estimation was obtained when the 3 (reconstruction accuracy) or 10 (coherence) first PCs were removed from the data. Importantly, values of reconstruction accuracy (~0.4 for 0.2-1.5-Hz CTS and ~0.1 for 2-8-Hz CTS) were remarkably close to those previously reported in classical MEG studies. Finally, source reconstruction localized the main sources of CTS to bilateral auditory cortices. In conclusion, t his study demonstrates that OPMs can be used for the purpose of CTS assessment. This finding opens new research avenues to unravel the neural network involved in CTS across the lifespan and potential alterations in, e.g., language developmental disorders. Data also suggest that OPMs are generally suitable for recording neural activity at frequencies below 4 Hz provided PCA is used as a preprocessing step; 0.2-1.5-Hz being the lowest frequency range successfully investigated here.

Effect of Speech Rate on Neural Tracking of Speech

Speech comprehension requires effort in demanding listening situations. Selective attention may be required for focusing on a specific talker in a multi-talker environment, may enhance effort by requiring additional cognitive resources, and is known to enhance the neural representation of the attended talker in the listener's neural response. The aim of the study was to investigate the relation of listening effort, as quantified by subjective effort ratings and pupil dilation, and neural speech tracking during sentence recognition. Task demands were varied using sentences with varying levels of linguistic complexity and using two different speech rates in a picture-matching paradigm with 20 normal-hearing listeners. The participants' task was to match the acoustically presented sentence with a picture presented before the acoustic stimulus. Afterwards they rated their perceived effort on a categorical effort scale. During each trial, pupil dilation (as an indicator of listening effort) and electroencephalogram (as an indicator of neural speech tracking) were recorded. Neither measure was significantly affected by linguistic complexity. However, speech rate showed a strong influence on subjectively rated effort, pupil dilation, and neural tracking. The neural tracking analysis revealed a shorter latency for faster sentences, which may reflect a neural adaptation to the rate of the input. No relation was found between neural tracking and listening effort, even though both measures were clearly influenced by speech rate. This is probably due to factors that influence both measures differently. Consequently, the amount of listening effort is not clearly represented in the neural tracking.