Dataset Information

Auditory-motor synchronization with temporally fluctuating sequences is dependent on fractal structure but not musical expertise.

ABSTRACT: Fractal structure is a ubiquitous property found in nature and biology, and has been observed in processes at different levels of organization, including rhythmic behavior and musical structure. A temporal process is characterized as fractal when serial long-term correlations and statistical self-similarity (scaling) are present. Previous studies of sensorimotor synchronization using isochronous (non-fractal) stimuli show that participants' errors exhibit persistent structure (positive long-term correlations), while their inter-tap intervals (ITIs) exhibit anti-persistent structure (negative long-term correlations). Auditory-motor synchronization has not been investigated with anti-persistent stimuli. In the current study, we systematically investigated whether the fractal structure of auditory rhythms was reflected in the responses of participants who were asked to coordinate their taps with each event. We asked musicians and non-musicians to tap with 12 different rhythms that ranged from anti-persistent to persistent. The scaling exponents of the ITIs were strongly correlated with the scaling exponents of the stimuli, showing that the long-term structure of the participants' taps scaled with the long-term structure of the stimuli. Surprisingly, the performance of the musicians was not significantly better than that of the non-musicians. Our results imply that humans are able to readily adapt (rather than simply react) to the overall statistical structure of temporally fluctuating stimuli, regardless of musical skill.

SUBMITTER: Rankin SK

PROVIDER: S-EPMC4153026 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Short-term memory has mostly been investigated with verbal or visuospatial stimuli and less so with other categories of stimuli. Moreover, the influence of sensory modality has been explored almost solely in the verbal domain. The present study compared visual and auditory short-term memory for different types of materials, aiming to understand whether sensory modality and material type can influence short-term memory performance. Furthermore, we aimed to assess if music expertise can modulate memory performance, as previous research has reported better auditory memory (and to some extent, visual memory), and better auditory contour recognition for musicians than non-musicians. To do so, we adapted the same recognition paradigm (delayed-matching to sample) across different types of stimuli. In each trial, participants (musicians and non-musicians) were presented with two sequences of events, separated by a silent delay, and had to indicate whether the two sequences were identical or different. The performance was compared for auditory and visual materials belonging to three different categories: (1) verbal (i.e., syllables); (2) nonverbal (i.e., that could not be easily denominated) with contour (based on loudness or luminance variations); and (3) nonverbal without contour (pink noise sequences or kanji letters sequences). Contour and no-contour conditions referred to whether the sequence can entail (or not) a contour (i.e., a pattern of up and down changes) based on non-pitch features. Results revealed a selective advantage of musicians for auditory no-contour stimuli and for contour stimuli (both visual and auditory), suggesting that musical expertise is associated with specific short-term memory advantages in domains close to the trained domain, also extending cross-modally when stimuli have contour information. Moreover, our results suggest a role of encoding strategies (i.e., how the material is represented mentally during the task) for short-term-memory performance.

Dataset Information

Auditory-motor synchronization with temporally fluctuating sequences is dependent on fractal structure but not musical expertise.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets