Music often evokes spontaneous movements in listeners that are synchronized with the music, a phenomenon that has been characterized as being in "the groove." However, the musical factors that contribute to listeners' initiation of stimulus-coupled action remain unclear. Evidence suggests that newly appearing objects in auditory scenes orient listeners' attention, and that in multipart music, newly appearing instrument or voice parts can engage listeners' attention and elicit arousal. We posit that attentional engagement with music can influence listeners' spontaneous stimulus-coupled movement. Here, 2 experiments-involving participants with and without musical training-tested the effect of staggering instrument entrances across time and varying the number of concurrent instrument parts within novel multipart music on listeners' engagement with the music, as assessed by spontaneous sensorimotor behavior and self-reports. Experiment 1 assessed listeners' moment-to-moment ratings of perceived groove, and Experiment 2 examined their spontaneous tapping and head movements. We found that, for both musically trained and untrained participants, music with more instruments led to higher ratings of perceived groove, and that music with staggered instrument entrances elicited both increased sensorimotor coupling and increased reports of perceived groove. Although untrained participants were more likely to rate music as higher in groove, trained participants showed greater propensity for tapping along, and they did so more accurately. The quality of synchronization of head movements with the music, however, did not differ as a function of training. Our results shed new light on the relationship between complex musical scenes, attention, and spontaneous sensorimotor behavior.

Rhythm is a ubiquitous feature of music that induces specific neural modes of processing. In this paper, we assess the potential of a stimulus-driven linear oscillator model (Tomic & Janata, 2008) to predict dynamic attention to complex musical rhythms on an instant-by-instant basis. We use perceptual thresholds and pupillometry as attentional indices against which to test our model pre- dictions. During a deviance detection task, participants listened to continuously looping, multi- instrument, rhythmic patterns, while being eye-tracked. Their task was to respond anytime they heard an increase in intensity (dB SPL). An adaptive thresholding algorithm adjusted deviant in- tensity at multiple probed temporal locations throughout each rhythmic stimulus. The oscillator model predicted participants’ perceptual thresholds for detecting deviants at probed locations, with a low temporal salience prediction corresponding to a high perceptual threshold and vice versa. A pupil dilation response was observed for all deviants. Notably, the pupil dilated even when partic- ipants did not report hearing a deviant. Maximum pupil size and resonator model output were sig- nificant predictors of whether a deviant was detected or missed on any given trial. Besides the evoked pupillary response to deviants, we also assessed the continuous pupillary signal to the rhythmic patterns. The pupil exhibited entrainment at prominent periodicities present in the stimuli and followed each of the different rhythmic patterns in a unique way. Overall, these results repli- cate previous studies using the linear oscillator model to predict dynamic attention to complex auditory scenes and extend the utility of the model to the prediction of neurophysiological signals, in this case the pupillary time course; however, we note that the amplitude envelope of the acoustic patterns may serve as a similarly useful predictor. To our knowledge, this is the first paper to show entrainment of pupil dynamics by demonstrating a phase relationship between musical stimuli and the pupillary signal.

Many environmental sounds, such as music or speech, are patterned in time. Dynamic attending theory, and supporting empirical evidence, suggests that a stimulus's temporal structure serves to orient attention to specific moments in time. One instantiation of this theory posits that attention synchronizes to the temporal structure of a stimulus in an oscillatory fashion, with optimal perception at salient time points or oscillation peaks. We examined whether a model consisting of damped linear oscillators succeeds at predicting temporal attention behavior in rhythmic multi-instrumental music. We conducted 3 experiments in which we mapped listeners' perceptual sensitivity by estimating detection thresholds for intensity deviants embedded at multiple time points within a stimulus pattern. We compared participants' thresholds for detecting intensity changes at various time points with the modeled salience prediction at each of those time points. Across all experiments, results showed that the resonator model predicted listener thresholds, such that listeners were more sensitive to probes at time points corresponding to greater model-predicted salience. This effect held for both intensity increment and decrement probes and for metrically simple and complex stimuli. Moreover, the resonator model explained the data better than did predictions based on canonical metric hierarchy or auditory scene density. Our results offer new insight into the temporal orienting of attention in complex auditory scenes using a parsimonious computational model for predicting attentional dynamics. (PsycINFO Database Record (c) 2018 APA, all rights reserved).