Sounds familiar(?): Expertise with specific musical genres modulates timing perception and micro-level synchronization to auditory stimuli.

Musical expertise improves the precision of timing perception and performance - but is this expertise generic, or is it tied to the specific style(s) and genre(s) of one's musical training? We asked expert musicians from three musical genres (folk, jazz, and EDM/hip-hop) to align click tracks and tap in synchrony with genre-specific and genre-neutral sound stimuli to determine the perceptual center ("P-center") and variability ("beat bin") for each group of experts. We had three stimulus categories - Organic, Electronic, and Neutral sounds - each of which had a 2 × 2 design of the acoustic factors Attack (fast/slow) and Duration (short/long). We found significant effects of Genre expertise, and a significant interaction for both P-center and P-center variability: folk and jazz musicians synchronize to sounds typical of folk and jazz in a different manner than the EDM/hip-hop producers.

Extreme precision in rhythmic interaction is enabled by role-optimized sensorimotor coupling: analysis and modelling of West African drum ensemble music.

Human social interactions often involve carefully synchronized behaviours. Musical performance in particular features precise timing and depends on the differentiation and coordination of musical/social roles. Here, we study the influence of musical/social roles, individual musicians and different ensembles on rhythmic synchronization in Malian drum ensemble music, which features synchronization accuracy near the limits of human performance.

A comparison of methods for investigating the perceptual center of musical sounds.

In speech and music, the acoustic and perceptual onset(s) of a sound are usually not congruent with its perceived temporal location. Rather, these "P-centers" are heard some milliseconds after the acoustic onset, and a variety of techniques have been used in speech and music research to find them. Here we report on a comparative study that uses various forms of the method of adjustment (aligning a click or filtered noise in-phase or anti-phase to a repeated target sound), as well as tapping in synchrony with a repeated target sound.

Tapping doesn't help: Synchronized self-motion and judgments of musical tempo.

For both musicians and music psychologists, beat rate (BPM) has often been regarded as a transparent measure of musical speed or tempo, yet recent research has shown that tempo is more than just BPM. In a previous study, London, Burger, Thompson, and Toiviainen (Acta Psychologica, 164, 70-80, 2016) presented participants with original as well as "time-stretched" versions of classic R&B songs; time stretching slows down or speeds up a recording without changing its pitch or timbre. In that study we discovered a tempo anchoring effect (TAE): Although relative tempo judgments (original vs.

Where is the beat in that note? Effects of attack, duration, and frequency on the perceived timing of musical and quasi-musical sounds.

The perceptual center (P-center) of a sound is typically understood as the specific moment at which it is perceived to occur. Using matched sets of real and artificial musical sounds as stimuli, we probed the influence of attack (rise time), duration, and frequency (center frequency) on perceived P-center location and P-center variability. Two different methods to determine the P-centers were used: Clicks aligned in-phase with the target sounds via the method of adjustment, and tapping in synchrony with the target sounds.

The Psychology of Music: Rhythm and Movement.

The urge to move to music is universal among humans. Unlike visual art, which is manifest across space, music is manifest across time. When listeners get carried away by the music, either through movement (such as dancing) or through reverie (such as trance), it is usually the temporal qualities of the music-its pulse, tempo, and rhythmic patterns-that put them in this state.

Synchronization to metrical levels in music depends on low-frequency spectral components and tempo.

Previous studies have found relationships between music-induced movement and musical characteristics on more general levels, such as tempo or pulse clarity. This study focused on synchronization abilities to music of finely-varying tempi and varying degrees of low-frequency spectral change/flux. Excerpts from six classic Motown/R&B songs at three different tempos (105, 115, and 130 BPM) were used as stimuli in this experiment.

Artificial grammar learning in tamarins (Saguinus oedipus) in varying stimulus contexts.

The human ability to detect regularities in sound sequences is a fundamental substrate of our language faculty. However, is this an ability exclusive to human language processing, or have we usurped a more general learning mechanism for this purpose, one shared with other species? The current study is an attempt to replicate and extend Hauser, Weiss, and Marcus's (2002) retracted study (2010) of artificial grammar learning in tamarins to determine if tamarins can detect an underlying grammatical structure in a pattern of sounds. Human language consonant-vowel (CV) combinations from Hauser et al.

Conscientiousness and Extraversion relate to responsiveness to tempo in dance.

Previous research has shown broad relationships between personality and dance, but the relationship between personality and specific structural features of music has not been explored. The current study explores the influence of personality and trait empathy on dancers' responsiveness to small tempo differences between otherwise musically identical stimuli, measured by difference in the amount in acceleration of key joints. Thirty participants were recorded using motion capture while dancing to excerpts from six popular songs that were time-stretched to be slightly faster or slower than their original tempi.

Both Isochronous and Non-Isochronous Metrical Subdivision Afford Precise and Stable Ensemble Entrainment: A Corpus Study of Malian Jembe Drumming.

Most approaches to musical rhythm, whether in music theory, music psychology, or musical neuroscience, presume that musical rhythms are based on isochronous (temporally equidistant) beats and/or beat subdivisions. However, rhythms that are based on non-isochronous, or unequal patterns of time are prominent in the music of Southeast Europe, the Near East and Southern Asia, and in the music of Africa and the African diaspora. The present study examines one such style found in contemporary Malian jembe percussion music.

Rhythm histograms and musical meter: A corpus study of Malian percussion music.

Studies of musical corpora have given empirical grounding to the various features that characterize particular musical styles and genres. Palmer & Krumhansl (1990) found that in Western classical music the likeliest places for a note to occur are the most strongly accented beats in a measure, and this was also found in subsequent studies using both Western classical and folk music corpora (Huron & Ommen, 2006; Temperley, 2010). We present a rhythmic analysis of a corpus of 15 performances of percussion music from Bamako, Mali.

Speed on the dance floor: Auditory and visual cues for musical tempo.

Musical tempo is most strongly associated with the rate of the beat or "tactus," which may be defined as the most prominent rhythmic periodicity present in the music, typically in a range of 1.67-2 Hz. However, other factors such as rhythmic density, mean rhythmic inter-onset interval, metrical (accentual) structure, and rhythmic complexity can affect perceived tempo (Drake, Gros, & Penel, 1999; London, 2011 Drake, Gros, & Penel, 1999; London, 2011).

Perception-production relationships and phase correction in synchronization with two-interval rhythms.

Two experiments investigated the effects of interval duration ratio on perception of local timing perturbations, accuracy of rhythm production, and phase correction in musicians listening to or tapping in synchrony with cyclically repeated auditory two-interval rhythms. Ratios ranged from simple (1:2) to complex (7:11, 5:13), and from small (5:13 = 0.38) to large (6:7 = 0.