The perception of a regular beat is fundamental to music processing. Here we examine whether the detection of a regular beat is pre-attentive for metrically simple, acoustically varying stimuli using the mismatch negativity (MMN), an ERP response elicited by violations of acoustic regularity irrespective of whether subjects are attending to the stimuli. Both musicians and non-musicians were presented with a varying rhythm with a clear accent structure in which occasionally a sound was omitted. We compared the MMN response to the omission of identical sounds in different metrical positions. Most importantly, we found that omissions in strong metrical positions, on the beat, elicited higher amplitude MMN responses than omissions in weak metrical positions, not on the beat. This suggests that the detection of a beat is pre-attentive when highly beat inducing stimuli are used. No effects of musical expertise were found. Our results suggest that for metrically simple rhythms with clear accents beat processing does not require attention or musical expertise. In addition, we discuss how the use of acoustically varying stimuli may influence ERP results when studying beat processing.

Beat perception is the ability to perceive temporal regularity in musical rhythm. When a beat is perceived, predictions about upcoming events can be generated. These predictions can influence processing of subsequent rhythmic events. However, statistical learning of the order of sounds in a sequence can also affect processing of rhythmic events and must be differentiated from beat perception. In the current study, using EEG, we examined the effects of attention and musical abilities on beat perception. To ensure we measured beat perception and not absolute perception of temporal intervals, we used alternating loud and soft tones to create a rhythm with two hierarchical metrical levels. To control for sequential learning of the order of the different sounds, we used temporally regular (isochronous) and jittered rhythmic sequences. The order of sounds was identical in both conditions, but only the regular condition allowed for the perception of a beat. Unexpected intensity decrements were introduced on the beat and offbeat. In the regular condition, both beat perception and sequential learning were expected to enhance detection of these deviants on the beat. In the jittered condition, only sequential learning was expected to affect processing of the deviants. ERP responses to deviants were larger on the beat than offbeat in both conditions. Importantly, this difference was larger in the regular condition than in the jittered condition, suggesting that beat perception influenced responses to rhythmic events in addition to sequential learning. The influence of beat perception was present both with and without attention directed at the rhythm. Moreover, beat perception as measured with ERPs correlated with musical abilities, but only when attention was directed at the stimuli. Our study shows that beat perception is possible when attention is not directed at a rhythm. In addition, our results suggest that attention may mediate the influence of musical abilities on beat perception.

Predicting the timing of incoming information allows the brain to optimize information processing in dynamic environments. Behaviorally, temporal expectations have been shown to facilitate processing of events at expected time points, such as sounds that coincide with the beat in musical rhythm. Yet, temporal expectations can develop based on different forms of structure in the environment, not just the regularity afforded by a musical beat. Little is still known about how different types of temporal expectations are neurally implemented and affect performance. Here, we orthogonally manipulated the periodicity and predictability of rhythmic sequences to examine the mechanisms underlying beat-based and memory-based temporal expectations, respectively. Behaviorally and using EEG, we looked at the effects of beat-based and memory-based expectations on auditory processing when rhythms were task-relevant or task-irrelevant. At expected time points, both beat-based and memory-based expectations facilitated target detection and led to attenuation of P1 and N1 responses, even when expectations were task-irrelevant (unattended). For beat-based expectations, we additionally found reduced target detection and enhanced N1 responses for events at unexpected time points (e.g., off-beat), regardless of the presence of memory-based expectations or task relevance. This latter finding supports the notion that periodicity selectively induces rhythmic fluctuations in neural excitability and furthermore indicates that, although beat-based and memory-based expectations may similarly affect auditory processing of expected events, their underlying neural mechanisms may be different.

Charles Darwin suggested the perception of rhythm to be common to all animals. While only recently experimental research is finding some support for this claim, there are also aspects of rhythm cognition that appear to be species-specific, such as the capability to perceive a regular pulse (or beat) in a varying rhythm. In the current study, using EEG, we adapted an auditory oddball paradigm that allows for disentangling the contributions of beat perception and isochrony to the temporal predictability of the stimulus. We presented two rhesus monkeys (Macaca mulatta) with a rhythmic sequence in two versions: an isochronous version, that was acoustically accented such that it could induce a duple meter (like a march), and a jittered version using the same acoustically accented sequence but that was presented in a randomly timed fashion, as such disabling beat induction. The results reveal that monkeys are sensitive to the isochrony of the stimulus, but not its metrical structure. The MMN was influenced by the isochrony of the stimulus, resulting in a larger MMN in the isochronous as opposed to the jittered condition. However, the MMN for both monkeys showed no interaction between metrical position and isochrony. So, while the monkey brain appears to be sensitive to the isochrony of the stimulus, we find no evidence in support of beat perception. We discuss these results in the context of the gradual audiomotor evolution (GAE) hypothesis (Merchant and Honing, 2014) that suggests beat-based timing to be omnipresent in humans but only weakly so or absent in non-human primates.

The processing of rhythmic events in music is influenced by the induced metrical structure. Two mechanisms underlying this may be temporal attending and temporal prediction. Temporal fluctuations in attentional resources may influence the processing of rhythmic events by heightening sensitivity at metrically strong positions. Temporal predictions may attenuate responses to events that are highly expected within a metrical structure. In the current study we aimed to disentangle these two mechanisms by examining responses to unexpected sounds, using intensity increments and decrements as deviants. Temporal attending was hypothesized to lead to better detection of deviants in metrically strong (on the beat) than weak (offbeat) positions due to heightened sensitivity on the beat. Temporal prediction was hypothesized to lead to best detection of increments in offbeat positions and decrements on the beat, as they would be most unexpected in these positions. We used a speeded detection task to measure detectability of the deviants under attended conditions (Experiment 1). Under unattended conditions (Experiment 2), we used EEG to measure the mismatch negativity (MMN), an ERP component known to index the detectability of unexpected auditory events. Furthermore, we examined the amplitude of the auditory evoked P1 and N1 responses, which are known to be sensitive to both attention and prediction. We found better detection of small increments in offbeat positions than on the beat, consistent with the influence of temporal prediction (Experiment 1). In addition, we found faster detection of large increments on the beat as opposed to offbeat (Experiment 1), and larger amplitude P1 responses on the beat as compared to offbeat, both in support of temporal attending (Experiment 2). As such, we showed that both temporal attending and temporal prediction shape our processing of metrical rhythm.

Perception of a regular beat in music is inferred from different types of accents. For example, increases in loudness cause intensity accents, and the grouping of time intervals in a rhythm creates temporal accents. Accents are expected to occur on the beat: when accents are “missing” on the beat, the beat is more difficult to find. However, it is unclear whether accents occurring off the beat alter beat perception similarly to missing accents on the beat. Moreover, no one has examined whether intensity accents influence beat perception more or less strongly than temporal accents, nor how musical expertise affects sensitivity to each type of accent. In two experiments, we obtained ratings of difficulty in finding the beat in rhythms with either temporal or intensity accents, and which varied in the number of accents on the beat as well as the number of accents off the beat. In both experiments, the occurrence of accents on the beat facilitated beat detection more in musical experts than in musical novices. In addition, the number of accents on the beat affected beat finding more in rhythms with temporal accents than in rhythms with intensity accents. The effect of accents off the beat was much weaker than the effect of accents on the beat and appeared to depend on musical expertise, as well as on the number of accents on the beat: when many accents on the beat are missing, beat perception is quite difficult, and adding accents off the beat may not reduce beat perception further. Overall, the different types of accents were processed qualitatively differently, depending on musical expertise. Therefore, these findings indicate the importance of designing ecologically valid stimuli when testing beat perception in musical novices, who may need different types of accent information than musical experts to be able to find a beat. Furthermore, our findings stress the importance of carefully designing rhythms for social and clinical applications of beat perception, as not all listeners treat all rhythms alike.

The aim of this chapter is to give an overview of how the perception of a regular beat in music can be studied in humans adults, human newborns, and nonhuman primates using event-related brain potentials (ERPs). Next to a review of the recent literature on the perception of temporal regularity in music, we will discuss in how far ERPs, and especially the component called mismatch negativity (MMN), can be instrumental in probing beat perception. We conclude with a discussion on the pitfalls and prospects of using ERPs to probe the perception of a regular beat, in which we present possible constraints on stimulus design and discuss future perspectives.

Rhythmic behaviour is ubiquitous in both human and non-human animals, but it is unclear whether the cognitive mechanisms underlying the specific rhythmic behaviours observed in different species are related. Laboratory experiments combined with highly controlled stimuli and tasks can be very effective in probing the cognitive architecture underlying rhythmic abilities. Rhythmic abilities have been examined in the laboratory with explicit and implicit perception tasks, and with production tasks, such as sensorimotor synchronization, with stimuli ranging from isochronous sequences of artificial sounds to human music. Here, we provide an overview of experimental findings on rhythmic abilities in human and non-human animals, while critically considering the wide variety of paradigms used. We identify several gaps in what is known about rhythmic abilities. Many bird species have been tested on rhythm perception, but research on rhythm production abilities in the same birds is lacking. By contrast, research in mammals has primarily focused on rhythm production rather than perception. Many experiments also do not differentiate between possible components of rhythmic abilities, such as processing of single temporal intervals, rhythmic patterns, a regular beat or hierarchical metrical structures. For future research, we suggest a careful choice of paradigm to aid cross-species comparisons, and a critical consideration of the multifaceted abilities that underlie rhythmic behaviour. This article is part of the theme issue ‘Synchrony and rhythm interaction: from the brain to behavioural ecology’.