EEG-based classification of natural sounds reveals specialized responses to speech and music

Abstract

Humans can easily distinguish many sounds in the environment, but speech and music are uniquely important. Previous studies, mostly using fMRI, have identified separate regions of the brain that respond selectively for speech and music. Yet there is little evidence that brain responses are larger and more temporally precise for human-specific sounds like speech and music, as has been found for responses to species-specific sounds in other animals. We recorded EEG as healthy, adult subjects listened to various types of two-second-long natural sounds. By classifying each sound based on the EEG response, we found that speech, music, and impact sounds were classified better than other natural sounds. But unlike impact sounds, the classification accuracy for speech and music dropped for synthesized sounds that have identical “low-level” acoustic statistics based on a subcortical model, indicating a selectivity for higher-order features in these sounds. Lastly, the trends in average power and phase consistency of the two-second EEG responses to each sound replicated the patterns of speech and music selectivity observed with classification accuracy. Together with the classification results, this suggests that the brain produces temporally individualized responses to speech and music sounds that are stronger than the responses to other natural sounds. In addition to highlighting the importance of speech and music for the human brain, the techniques used here could be a cost-effective and efficient way to study the human brain’s selectivity for speech and music in other populations.HighlightsEEG responses are stronger to speech and music than to other natural soundsThis selectivity was not replicated using stimuli with the same acoustic statisticsThese techniques can be a cost-effective way to study speech and music selectivity

Individual differences in perception of the speech-to-song illusion are linked to musical aptitude but not musical training.

“…A deeper understanding of these individual differences would help researchers predict whether a given listener will experience a particular spoken phrase as sung when repeated. This in turn would provide a powerful tool for exploring the cognitive and brain mechanisms underlying selective neural responses to speech and music (Ogg, Moraczewski, Kuchinsky, & Slevc, 2019;Zuk, Teoh, & Lalor, 2020;Boebinger, Norman-Haignere, McDermott, & Kanwisher, 2021), by using the same physical stimuli to elicit categorically different perceptual experiences.…”

“…Music often has acoustic patterns which distinguish it from speech or other sounds (Ding et al, 2017), and also elicits distinct neural responses compared to other sounds (Norman-Haignere et al 2015;Zuk et al, 2020). Nevertheless, studies over the past decade have demonstrated that listeners sometimes report perceiving non-musical sounds (i.e., sounds not originally intended to be heard as music) as sounding like music.…”

Music-selective neural populations arise without musical training

“…Speech and music are known to differ in their temporal modulation spectra, peaking at 5 Hz and 2 Hz, respectively (Ding et al, 2017). However, standard auditory models based on spectrotemporal modulation do not capture perception of speech and music (McDermott and Simoncelli, 2011) or neural responses selective for speech and music (Overath et al, 2015;Kell et al, 2018;Norman-Haignere and McDermott, 2018;Zuk et al, 2020). In particular, the music-selective component responds substantially less to sounds that have been synthesized to have the same spectrotemporal modulation statistics as natural music, suggesting that the music component does not simply represent the audio or modulation frequencies that are prevalent in music (Norman-Haignere and McDermott, 2018).…”

Real-time audio processing of real-life soundscapes for EEG analysis: ERPs based on natural sound onsets

“…By relating naturally occurring sounds in everyday life to ongoing EEG activity, we can investigate questions about auditory perception and attention in real world scenarios. There is an increasing number of studies using naturalistic stimuli to study auditory perception (e.g., De Lucia, Tzovara, Bernasconi, Spierer, & Murray, 2012;Perrin et al, 2005;Roye, Jacobsen, & Schröger, 2013;Scheer, Bülthoff, & Chuang, 2018;Zuk, Teoh, & Lalor, 2020). However, to gain experimental control in this lab-based research, everyday life sounds and contexts are approximated by using artificial stimuli and conditions.…”