Neural entrainment to music is sensitive to melodic spectral complexity

Abstract

During auditory perception, neural oscillations are known to entrain to acoustic dynamics but their role in the processing of auditory information remains unclear. As a complex temporal structure that can be parameterized acoustically, music is particularly suited to address this issue. In a combined behavioral and EEG experiment in human participants, we investigated the relative contribution of temporal (acoustic dynamics) and nontemporal (melodic spectral complexity) dimensions of stimulation on neural entrainment, a stimulus-brain coupling phenomenon operationally defined here as the temporal coherence between acoustical and neural dynamics. We first highlight that low-frequency neural oscillations robustly entrain to complex acoustic temporal modulations, which underscores the fine-grained nature of this coupling mechanism. We also reveal that enhancing melodic spectral complexity, in terms of pitch, harmony, and pitch variation, increases neural entrainment. Importantly, this manipulation enhances activity in the theta (5 Hz) range, a frequency-selective effect independent of the note rate of the melodies, which may reflect internal temporal constraints of the neural processes involved. Moreover, while both emotional arousal ratings and neural entrainment were positively modulated by spectral complexity, no direct relationship between arousal and neural entrainment was observed. Overall, these results indicate that neural entrainment to music is sensitive to the spectral content of auditory information and indexes an auditory level of processing that should be distinguished from higher-order emotional processing stages. NEW & NOTEWORTHY Low-frequency (<10 Hz) cortical neural oscillations are known to entrain to acoustic dynamics, the so-called neural entrainment phenomenon, but their functional implication in the processing of auditory information remains unclear. In a behavioral and EEG experiment capitalizing on parameterized musical textures, we disentangle the contribution of stimulus dynamics, melodic spectral complexity, and emotional judgments on neural entrainment and highlight their respective spatial and spectral neural signature.

Stimulating Music Supports Attention in Listeners with Attentional Difficulties

“…Brain stimulation methods with controlled frequencies have been used to enhance cognitive performance in recent years [59][60][61][62] . Sound is another means by which to stimulate the brain [63][64][65] ; however, the frequency of sound stimulation has often resulted in stimuli that are perceptually unpleasant (e.g., click trains, binaural beats). The observation that music strongly affects neural oscillations 32,65,66 motivates an approach whereby targeted acoustic modulation added to music might be used for neuromodulation, with particular goals outside the aesthetic and/or social uses of music (i.e., 'functional' music rather than 'art' music).…”

“…Sound is another means by which to stimulate the brain [63][64][65] ; however, the frequency of sound stimulation has often resulted in stimuli that are perceptually unpleasant (e.g., click trains, binaural beats). The observation that music strongly affects neural oscillations 32,65,66 motivates an approach whereby targeted acoustic modulation added to music might be used for neuromodulation, with particular goals outside the aesthetic and/or social uses of music (i.e., 'functional' music rather than 'art' music). One barrier to this has been individual variability, as different neurotypes and cognitive functions may require a range of targets for their mechanisms.…”

Neural synchronization is strongest to the spectral flux of slow music and depends on familiarity and beat salience

“…Music is highly rhythmic, and neural oscillations can be entrained by the beat, the most prominent isochronous pulse in music, to which listeners would sway their bodies or tap their feet (Tierney and Kraus, 2015, Nozaradan et al, 2012, Large and Snyder, 2009, Doelling and Poeppel, 2015). Most studies that have examined cortical tracking of musical rhythm used simplified musical stimuli, such as MIDI melodies or click tracks (Kumagai et al, 2018, Nozaradan et al, 2012, Di Liberto et al, 2020, Nozaradan et al, 2011, Wollman et al, 2020) or monophonic melodies (Doelling and Poeppel, 2015); only a few studies have focused on naturalistic, polyphonic music (Tierney and Kraus, 2015, Madsen et al, 2019, Kaneshiro et al, 2020). Listeners show a strong preference for music at beat rates around 2 Hz (here, we use the term tempo to refer to the beat rate).…”

“…Most studies assessing neural synchronization to music have examined synchronization to either the stimulus amplitude envelope, which quantifies intensity fluctuations over time (Doelling and Poeppel, 2015, Kaneshiro et al, 2020, Wollman et al, 2020), or “higher order” musical features such as surprise and expectation (Di Liberto et al, 2020). This mimics approaches used for studying neural synchronization to speech, where neural activity has been shown to synchronize with the amplitude envelope (Peelle and Davis, 2012), which roughly corresponds to syllabic fluctuations (Doelling et al, 2014), as well as to “higher order” semantic information (Broderick et al, 2019).…”

“…This mimics approaches used for studying neural synchronization to speech, where neural activity has been shown to synchronize with the amplitude envelope (Peelle and Davis, 2012), which roughly corresponds to syllabic fluctuations (Doelling et al, 2014), as well as to “higher order” semantic information (Broderick et al, 2019). Notably, most studies that have examined neural synchronization to musical rhythm have used simplified musical stimuli, such as MIDI melodies (Kumagai et al, 2018) and monophonic melodies (Di Liberto et al, 2020), or rhythmic lines comprising clicks or sine tones (Nozaradan et al, 2012, Nozaradan et al, 2011, Wollman et al, 2020); only a few studies have focused on naturalistic, polyphonic music (Tierney and Kraus, 2015, Madsen et al, 2019, Kaneshiro et al, 2020, Doelling and Poeppel, 2015). “Higher order” musical features are difficult to compute for naturalistic music, which is typically polyphonic and has complex spectro-temporal properties (Zatorre et al, 2002).…”