Enhanced neural tracking of the fundamental frequency of the voice

Objective ‘F0 tracking’ is a novel method that investigates the neural processing of the fundamental frequency of the voice (f0) in continuous speech. Through linear modelling, a feature that reflects the stimulus f0 is predicted from the EEG data. Then, the neural response strength is evaluated through the correlation between the predicted and actual f0 feature. The aim of this study was to improve upon this ‘f0 tracking’ method by optimizing the f0 feature. Approach Specifically, we aimed to design a feature that approximates the expected EEG responses to the f0. We hypothesized that this would improve neural tracking results, because the more similar the feature and the neural response are, the easier it will be to reconstruct the one from the other. Two techniques were explored: a phenomenological model to simulate neural processing in the auditory periphery and a low-pass filter to approximate the effect of more central processing on the f0 response. Since these optimizations target different aspects of the auditory system, they were also applied in a cumulative fashion. Results Results obtained from EEG evoked by a Flemish story in 34 subjects indicated that both the use of the auditory model and the addition of the low-pass filter significantly improved the correlations between the actual and reconstructed feature. The combination of both strategies almost doubled the mean correlation over subjects, from 0.78 to 0.13. Moreover, canonical correlation analysis with the modelled feature revealed two distinct processes contributing to the f0 response: one driven by the compound activity of auditory nerve fibers with center frequency up to 8 kHz and one driven predominantly by the auditory nerve fibers with center frequency below 1 kHz. Significance The optimized f0 features developed in this study enhance the analysis of f0-tracking responses and facilitate future research and applications.