Topic
Rhythm
About: Rhythm is a research topic. Over the lifetime, 2730 publications have been published within this topic receiving 65903 citations. The topic is also known as: musical rhythm.
Papers published on a yearly basis
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Papers
TL;DR: This review examines the physiological foundations of sympathovagal balance, a model whose order (the number of parameters) is selected automatically to minimize Akaike’s information criterion statistic.
Abstract: Given the importance of the autonomic nervous system to cardiovascular health, it is not surprising that there is and has been great interest in measurements of human sympathetic and vagus nerve traffic as tools that might inform physiological and pathophysiological mechanisms. Pagani and coworkers1 advanced the provocative notion that the instantaneous balance between sympathetic and vagal nerve activities can be captured by a single number, obtained by dividing RR-interval spectral power centered at ≈0.1 Hz by spectral power centered at higher, primarily respiratory frequencies. This ratio, or sympathovagal balance, has been embraced with great enthusiasm2 because it offers new possibilities for understanding dynamic, critically important autonomic interrelations in humans by the use of totally noninvasive, unobtrusive means.3
The broad bases for this mathematical treatment are as follows: (1) 0.1-Hz RR intervals are importantly mediated by fluctuations of sympathetic nerve activity; (2) higher-frequency RR-interval rhythms are mediated almost exclusively by fluctuations of vagal-cardiac nerve activity; and (3) physiological interventions tend to provoke reciprocal changes of sympathetic and vagal neural outflows. Sympathovagal balance, the ratio of these periodicities, is taken to reflect the balance between the opposing neural mechanisms. This review examines the physiological foundations of sympathovagal balance.
The ECG is recorded with the subject in a steady state (when rhythms are stationary) for a period sufficiently long to define events occurring over frequencies of interest. RR-interval spectral power is calculated from this series of intervals with an autoregressive algorithm, which yields center frequencies and absolute power of component fluctuations, based on a model whose order (the number of parameters) is selected automatically to minimize Akaike’s information criterion statistic.4 (The statistical uncertainty and consequences of the automatic selection of the autoregressive model have not been defined fully; however, it is clear that the model order importantly determines both …
1,112 citations
TL;DR: It is concluded that, in addition to their role in movement production, the basal ganglia and SMAs may mediate beat perception.
Abstract: When we listen to rhythm, we often move spontaneously to the beat. This movement may result from processing of the beat by motor areas. Previous studies have shown that several motor areas respond when attending to rhythms. Here we investigate whether specific motor regions respond to beat in rhythm. We predicted that the basal ganglia and supplementary motor area (SMA) would respond in the presence of a regular beat. To establish what rhythm properties induce a beat, we asked subjects to reproduce different types of rhythmic sequences. Improved reproduction was observed for one rhythm type, which had integer ratio relationships between its intervals and regular perceptual accents. A subsequent functional magnetic resonance imaging study found that these rhythms also elicited higher activity in the basal ganglia and SMA. This finding was consistent across different levels of musical training, although musicians showed activation increases unrelated to rhythm type in the premotor cortex, cerebellum, and SMAs (pre-SMA and SMA). We conclude that, in addition to their role in movement production, the basal ganglia and SMAs may mediate beat perception.
1,019 citations
TL;DR: Evidence that motor imagery could play an important role in EEG-based communication is supplied, and it is suggested that mu and beta rhythms might provide independent control signals.
Abstract: People can learn to control the 8-12 Hz mu rhythm and/or the 18-25 Hz beta rhythm in the EEG recorded over sensorimotor cortex and use it to control a cursor on a video screen. Subjects often report using motor imagery to control cursor movement, particularly early in training. We compared in untrained subjects the EEG topographies associated with actual hand movement to those associated with imagined hand movement. Sixty-four EEG channels were recorded while each of 33 adults moved left- or right-hand or imagined doing so. Frequency-specific differences between movement or imagery and rest, and between right- and left-hand movement or imagery, were evaluated by scalp topographies of voltage and r spectra, and principal component analysis. Both movement and imagery were associated with mu and beta rhythm desynchronization. The mu topographies showed bilateral foci of desynchronization over sensorimotor cortices, while the beta topographies showed peak desynchronization over the vertex. Both mu and beta rhythm left/right differences showed bilateral central foci that were stronger on the right side. The independence of mu and beta rhythms was demonstrated by differences for movement and imagery for the subjects as a group and by principal components analysis. The results indicated that the effects of imagery were not simply an attenuated version of the effects of movement. They supply evidence that motor imagery could play an important role in EEG-based communication, and suggest that mu and beta rhythms might provide independent control signals.
903 citations
TL;DR: Results reveal a direct link between cortical and behavioral measures of rhythmic entrainment, thus providing evidence that frequency-tagged brain activity has functional relevance for beat perception and synchronization.
Abstract: The current study aims at characterizing the mechanisms that allow humans to entrain the mind and body to incoming rhythmic sensory inputs in real time. We addressed this unresolved issue by examining the relationship between covert neural processes and overt behavior in the context of musical rhythm. We measured temporal prediction abilities, sensorimotor synchronization accuracy and neural entrainment to auditory rhythms as captured using an EEG frequency-tagging approach. Importantly, movement synchronization accuracy with a rhythmic beat could be explained by the amplitude of neural activity selectively locked with the beat period when listening to the rhythmic inputs. Furthermore, stronger endogenous neural entrainment at the beat frequency was associated with superior temporal prediction abilities. Together, these results reveal a direct link between cortical and behavioral measures of rhythmic entrainment, thus providing evidence that frequency-tagged brain activity has functional relevance for beat perception and synchronization.
848 citations
TL;DR: It is demonstrated that the perception of musical rhythm is a multisensory experience in infancy, in particular, movement of the body, by bouncing on every second versus every third beat of an ambiguous auditory rhythm pattern, influences whether that auditory rhythm patterns are encoded in duple form or in triple form.
Abstract: We hear the melody in music, but we feel the beat. We demonstrate that the perception of musical rhythm is a multisensory experience in infancy. In particular, movement of the body, by bouncing on every second versus every third beat of an ambiguous auditory rhythm pattern, influences whether that auditory rhythm pattern is encoded in duple form (a march) or in triple form (a waltz). Visual information is not necessary for the effect, indicating that it likely reflects a strong, early-developing interaction between auditory and vestibular information in the human nervous system.
652 citations
Related Topics (5)
Performance Metrics
| Year | Papers |
|---|---|
| 2026 | 2 |
| 2025 | 1,341 |
| 2024 | 1,776 |
| 2023 | 1,765 |
| 2022 | 2,292 |
| 2021 | 233 |