Attention affects overall gain but not selective contrast at meter frequencies in the neural processing of rhythm

Abstract

When listening to music, humans spontaneously perceive and synchronize movement to periodic pulses of meter. A growing body of evidence suggests that this widespread ability is related to neural processes that selectively enhance meter periodicities. However, to what extent these neural processes are affected by the attentional state of the listener remains largely unknown. Here, we recorded EEG while participants listened to auditory rhythms and detected small changes in tempo or pitch of the stimulus, or performed a visual task. The overall neural response to the auditory input decreased when participants attended the visual modality, indicating generally lower sensitivity to acoustic information. However, the selective contrast at meter periodicities did not differ across the three tasks. Moreover, this selective contrast could be trivially accounted for by biologically-plausible models of subcortical auditory processing, but only when meter periodicities were already prominent in the acoustic input. However, when meter periodicities were not prominent in the auditory input, the EEG responses could not be explained by low-level processing. This was also confirmed by early auditory responses that originate predominantly in early auditory areas and were recorded in the same EEG. The contrast at meter periodicities in these early responses was consistently smaller than in the EEG responses originating mainly from higher-level processing stages. Together, these results demonstrate that selective contrast at meter periodicities involves higher-level neural processes that may be engaged automatically, irrespective of behavioral context. This robust shaping of the neural representation of rhythm might thus contribute to spontaneous and effortless synchronization to musical meter in humans across cultures.

Mapping between sound, brain and behaviour: four-level framework for understanding rhythm processing in humans and non-human primates

“…brainstem auditory responses) isolated from scalp EEG signals closely track the acoustic input, hence showing little prominence of metric pulses for weakly periodic inputs [83]. This result is also corroborated by computational models of subcortical auditory processing, which provide a biologically plausible estimate of the output of neural populations at the level of the inferior colliculus in response to weakly periodic inputs [100]. By contrast, these neural representations are critically transformed at the cortical level, as reflected by significantly enhanced pulse periodicities in responses to weakly periodic inputs captured directly from Heschl's gyrus (primary auditory cortex) in human participants using intracerebral EEG [77].…”

“…This is valid if the measure under comparison is sensitive to signal properties that are relevant to the functional definition of the phenomenon (here the three properties making up periodic recurrence: self-similarity, contrast and regularity), while generalizing across units, scales and different possible representation formats [ 99 ]. As discussed in the electronic supplementary material, if used carefully, measures of pulse prominence based on frequency domain may fulfil these criteria [ 72 , 100 ]. Moreover, these methods can be used to make valid comparisons between signals captured from different brain regions at different spatial scales (including neuronal firing rates, local field potentials, narrow-band power fluctuations), as well as overt behaviour (e.g.…”

Steady state‐evoked potentials of subjective beat perception in musical rhythms

“…It is possible that this substantially greater power at the stimulus frequency in the slow tempo served as a greater attractor for the listener's attention, thus limiting the attention allocated to the beat frequency in these conditions. Furthermore, evidence from a recent frequency-tagging experiment that manipulated attention via task demands suggests that listeners' attention to different stimulus features can affect the overall change in amplitude of the SSEP (Lenc et al, 2020). Further research is necessary to understand how attention plays a role in the neural responses underlying subjective beat perception, as well as what other neural correlates may be predictors of listener perception.…”

“…One critical attribute of SSEPs is that they can reflect both propagated stimulus-driven neural processing from early areas of the auditory pathway, such as brainstem and midbrain sources (Rajendran et al, 2017;Tierney & Kraus, 2013), as well as top-down influences such as task-manipulated attentional demands (see preprint, Lenc et al, 2020), mental imagery (Iversen et al, 2009;Nozaradan et al, 2011), and subsequent tapping behavior (Nozaradan et al, 2016;Tal et al, 2017). In order to confidently say that a measured SSEP response is directly related to the listener's perception of the stimulus, one must confidently control for the contribution of stimulus features.…”

Meter without rhythmic pattern repetitions increases pre-attentive processing

“…Here, METER WITHOUT RHYTHMIC PATTERN REPETITIONS INCREASES PRE-ATTENTIVE PROCESSING results become mixed. Some studies suggest that meter is perceived under pre-attentive conditions (Bouwer et al, 2014(Bouwer et al, , 2016Geiser et al, 2010;Vuust et al, 2009;Winkler et al, 2009;Zhao et al, 2017), and direct comparisons between different levels of attention to temporal information (attention to tempo vs. pitch vs. arithmetic task) indicated similar levels of entrainment to meter (Celma-Miralles & Toro, 2019;Lenc et al, 2020). In contrast, Geiser et al (2009) asked participants to focus on meter itself (attentive) vs. pitch (pre-attentive), and ERPs showed that meter processing occurs only under attentive conditions.…”