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17 pages, 1333 KiB

Open AccessArticle

Rhythmic Chanting and Mystical States across Traditions

by Gemma Perry, Vince Polito and William Forde Thompson

Brain Sci. 2021, 11(1), 101; https://doi.org/10.3390/brainsci11010101 - 13 Jan 2021

Cited by 22 | Viewed by 10682

Abstract

Chanting is a form of rhythmic, repetitive vocalization practiced in a wide range of cultures. It is used in spiritual practice to strengthen community, heal illness, and overcome psychological and emotional difficulties. In many traditions, chanting is used to induce mystical states, an [...] Read more.

Chanting is a form of rhythmic, repetitive vocalization practiced in a wide range of cultures. It is used in spiritual practice to strengthen community, heal illness, and overcome psychological and emotional difficulties. In many traditions, chanting is used to induce mystical states, an altered state of consciousness characterised by a profound sense of peace. Despite the global prevalence of chanting, its psychological effects are poorly understood. This investigation examined the psychological and contextual factors associated with mystical states during chanting. Data were analyzed from 464 participants across 33 countries who regularly engaged in chanting. Results showed that 60% of participants experienced mystical states during chanting. Absorption, altruism, and religiosity were higher among people who reported mystical states while chanting compared to those who did not report mystical states. There was no difference in mystical experience scores between vocal, silent, group or individual chanting and no difference in the prevalence of mystical states across chanting traditions. However, an analysis of subscales suggested that mystical experiences were especially characterised by positive mood and feelings of ineffability. The research sheds new light on factors that impact upon chanting experiences. A framework for understanding mystical states during chanting is proposed. Full article

(This article belongs to the Special Issue Rhythmic Motor Pattern Generation)

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16 pages, 2886 KiB

Open AccessArticle

A Re-Appraisal of the Effect of Amplitude on the Stability of Interlimb Coordination Based on Tightened Normalization Procedures

by Harjo J. de Poel, Melvyn Roerdink, C. (Lieke) E. Peper and Peter J. Beek

Brain Sci. 2020, 10(10), 724; https://doi.org/10.3390/brainsci10100724 - 13 Oct 2020

Cited by 4 | Viewed by 2427

Abstract

The stability of rhythmic interlimb coordination is governed by the coupling between limb movements. While it is amply documented how coordinative performance depends on movement frequency, theoretical considerations and recent empirical findings suggest that interlimb coupling (and hence coordinative stability) is actually mediated [...] Read more.

The stability of rhythmic interlimb coordination is governed by the coupling between limb movements. While it is amply documented how coordinative performance depends on movement frequency, theoretical considerations and recent empirical findings suggest that interlimb coupling (and hence coordinative stability) is actually mediated more by movement amplitude. Here, we present the results of a reanalysis of the data of Post, Peper, and Beek (2000), which were collected in an experiment aimed at teasing apart the effects of frequency and amplitude on coordinative stability of both steady-state and perturbed in-phase and antiphase interlimb coordination. The dataset in question was selected because we found indications that the according results were prone to artifacts, which may have obscured the potential effects of amplitude on the post-perturbation stability of interlimb coordination. We therefore redid the same analysis based on movement signals that were normalized each half-cycle for variations in oscillation center and movement frequency. With this refined analysis we found that (1) stability of both steady-state and perturbed coordination indeed seemed to depend more on amplitude than on movement frequency per se, and that (2) whereas steady-state antiphase coordination became less stable with increasing frequency for prescribed amplitudes, in-phase coordination became more stable at higher frequencies. Such effects may have been obscured in previous studies due to (1) unnoticed changes in performed amplitudes, and/or (2) artifacts related to inappropriate data normalization. The results of the present reanalysis therefore give cause for reconsidering the relation between the frequency, amplitude, and stability of interlimb coordination. Full article

(This article belongs to the Special Issue Rhythmic Motor Pattern Generation)

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16 pages, 2706 KiB

Open AccessArticle

Cadence Modulation in Walking and Running: Pacing Steps or Strides?

by Anouk Nijs, Melvyn Roerdink and Peter J. Beek

Brain Sci. 2020, 10(5), 273; https://doi.org/10.3390/brainsci10050273 - 1 May 2020

Cited by 14 | Viewed by 6024

Abstract

A change in cadence during walking or running might be indicated for a variety of reasons, among which mobility improvement and injury prevention. In a within-subject study design, we examined whether walking or running cadences are modulated best by means of step-based or [...] Read more.

A change in cadence during walking or running might be indicated for a variety of reasons, among which mobility improvement and injury prevention. In a within-subject study design, we examined whether walking or running cadences are modulated best by means of step-based or stride-based auditory pacing. Sixteen experienced runners walked and ran on a treadmill while synchronizing with step-based and stride-based pacing at slow, preferred and fast pacing frequencies in synchronization-perturbation and synchronization-continuation conditions. We quantified the variability of the relative phase between pacing cues and footfalls and the responses to perturbations in the pacing signal as measures of coordinative stability; the more stable the auditory-motor coordination, the stronger the modulating effect of pacing. Furthermore, we quantified the deviation from the prescribed cadence after removal of the pacing signal as a measure of internalization of this cadence. Synchronization was achieved less often in running, especially at slow pacing frequencies. If synchronization was achieved, coordinative stability was similar, and the paced cadence was well internalized for preferred and fast pacing frequencies. Step-based pacing led to more stable auditory-motor coordination than stride-based pacing in both walking and running. We therefore concluded that step-based auditory pacing deserves preference as a means to modulate cadence in walking and running. Full article

(This article belongs to the Special Issue Rhythmic Motor Pattern Generation)

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Review

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18 pages, 3045 KiB

Open AccessReview

Hopf Bifurcations in Complex Multiagent Activity: The Signature of Discrete to Rhythmic Behavioral Transitions

by Gaurav Patil, Patrick Nalepka, Rachel W. Kallen and Michael J. Richardson

Brain Sci. 2020, 10(8), 536; https://doi.org/10.3390/brainsci10080536 - 9 Aug 2020

Cited by 12 | Viewed by 5131

Abstract

Most human actions are composed of two fundamental movement types, discrete and rhythmic movements. These movement types, or primitives, are analogous to the two elemental behaviors of nonlinear dynamical systems, namely, fixed-point and limit cycle behavior, respectively. Furthermore, there is now a growing [...] Read more.

Most human actions are composed of two fundamental movement types, discrete and rhythmic movements. These movement types, or primitives, are analogous to the two elemental behaviors of nonlinear dynamical systems, namely, fixed-point and limit cycle behavior, respectively. Furthermore, there is now a growing body of research demonstrating how various human actions and behaviors can be effectively modeled and understood using a small set of low-dimensional, fixed-point and limit cycle dynamical systems (differential equations). Here, we provide an overview of these dynamical motorprimitives and detail recent research demonstrating how these dynamical primitives can be used to model the task dynamics of complex multiagent behavior. More specifically, we review how a task-dynamic model of multiagent shepherding behavior, composed of rudimentary fixed-point and limit cycle dynamical primitives, can not only effectively model the behavior of cooperating human co-actors, but also reveals how the discovery and intentional use of optimal behavioral coordination during task learning is marked by a spontaneous, self-organized transition between fixed-point and limit cycle dynamics (i.e., via a Hopf bifurcation). Full article

(This article belongs to the Special Issue Rhythmic Motor Pattern Generation)

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12 pages, 886 KiB

Open AccessReview

Cerebral Substrates for Controlling Rhythmic Movements

by Naho Konoike and Katsuki Nakamura

Brain Sci. 2020, 10(8), 514; https://doi.org/10.3390/brainsci10080514 - 3 Aug 2020

Cited by 9 | Viewed by 3989

Abstract

Our daily lives are filled with rhythmic movements, such as walking, sports, and dancing, but the mechanisms by which the brain controls rhythmic movements are poorly understood. In this review, we examine the literature on neuropsychological studies of patients with focal brain lesions, [...] Read more.

Our daily lives are filled with rhythmic movements, such as walking, sports, and dancing, but the mechanisms by which the brain controls rhythmic movements are poorly understood. In this review, we examine the literature on neuropsychological studies of patients with focal brain lesions, and functional brain imaging studies primarily using finger-tapping tasks. These studies suggest a close connection between sensory and motor processing of rhythm, with no apparent distinction between the two functions. Thus, we conducted two functional brain imaging studies to survey the rhythm representations relatively independent of sensory and motor functions. First, we determined brain activations related to rhythm processing in a sensory modality-independent manner. Second, we examined body part-independent brain activation related to rhythm reproduction. Based on previous literature, we discuss how brain areas contribute rhythmic motor control. Furthermore, we also discuss the mechanisms by which the brain controls rhythmic movements. Full article

(This article belongs to the Special Issue Rhythmic Motor Pattern Generation)

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19 pages, 2744 KiB

Open AccessReview

Towards an Understanding of Control of Complex Rhythmical “Wavelike” Coordination in Humans

by Ross Howard Sanders and Daniel J. Levitin

Brain Sci. 2020, 10(4), 215; https://doi.org/10.3390/brainsci10040215 - 5 Apr 2020

Cited by 3 | Viewed by 4849

Abstract

How does the human neurophysiological system self-organize to achieve optimal phase relationships among joints and limbs, such as in the composite rhythms of butterfly and front crawl swimming, drumming, or dancing? We conducted a systematic review of literature relating to central nervous system [...] Read more.

How does the human neurophysiological system self-organize to achieve optimal phase relationships among joints and limbs, such as in the composite rhythms of butterfly and front crawl swimming, drumming, or dancing? We conducted a systematic review of literature relating to central nervous system (CNS) control of phase among joint/limbs in continuous rhythmic activities. SCOPUS and Web of Science were searched using keywords “Phase AND Rhythm AND Coordination”. This yielded 1039 matches from which 23 papers were extracted for inclusion based on screening criteria. The empirical evidence arising from in-vivo, fictive, in-vitro, and modelling of neural control in humans, other species, and robots indicates that the control of movement is facilitated and simplified by innervating muscle synergies by way of spinal central pattern generators (CPGs). These typically behave like oscillators enabling stable repetition across cycles of movements. This approach provides a foundation to guide the design of empirical research in human swimming and other limb independent activities. For example, future research could be conducted to explore whether the Saltiel two-layer CPG model to explain locomotion in cats might also explain the complex relationships among the cyclical motions in human swimming. Full article

(This article belongs to the Special Issue Rhythmic Motor Pattern Generation)

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14 pages, 2256 KiB

Open AccessFeature PaperReview

Locomotor Coordination, Visual Perception and Head Stability during Running

by Joseph Hamill, Jongil Lim and Richard van Emmerik

Brain Sci. 2020, 10(3), 174; https://doi.org/10.3390/brainsci10030174 - 18 Mar 2020

Cited by 9 | Viewed by 6453

Abstract

Perception and action are coupled such that information from the perceptual system is related to the dynamics of action in order to regulate behavior adaptively. Using running as a model of a cyclic behavior, this coupling involves a continuous, cyclic relationship between the [...] Read more.

Perception and action are coupled such that information from the perceptual system is related to the dynamics of action in order to regulate behavior adaptively. Using running as a model of a cyclic behavior, this coupling involves a continuous, cyclic relationship between the runner’s perception of the environment and the necessary adjustments of the body that ultimately result in a stable pattern of behavior. The purpose of this paper is to illustrate how individuals relate visual perception to rhythmic locomotor coordination patterns in conditions during which foot–ground collisions and visual task demands are altered. We review the findings of studies conducted to illustrate how humans change their behavior to maintain head stability during running with and without various degrees of visual challenge from the environment. Finally, we show that the human body adapts specific segment/joint configuration and coordination patterns to maintain head stability, both in the lower extremity and upper body segments, together with an increase in coordinative variability. These results indicate that in human locomotion, under higher speed (running) and visual task demands, systematic adaptations occur in the rhythmic coupling between the perceptual and movement systems. Full article

(This article belongs to the Special Issue Rhythmic Motor Pattern Generation)

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15 pages, 3230 KiB

Open AccessReview

Cortical Oscillations during Gait: Wouldn’t Walking Be So Automatic?

by Arnaud Delval, Madli Bayot, Luc Defebvre and Kathy Dujardin

Brain Sci. 2020, 10(2), 90; https://doi.org/10.3390/brainsci10020090 - 9 Feb 2020

Cited by 16 | Viewed by 5276

Abstract

Gait is often considered as an automatic movement but cortical control seems necessary to adapt gait pattern with environmental constraints. In order to study cortical activity during real locomotion, electroencephalography (EEG) appears to be particularly appropriate. It is now possible to record changes [...] Read more.

Gait is often considered as an automatic movement but cortical control seems necessary to adapt gait pattern with environmental constraints. In order to study cortical activity during real locomotion, electroencephalography (EEG) appears to be particularly appropriate. It is now possible to record changes in cortical neural synchronization/desynchronization during gait. Studying gait initiation is also of particular interest because it implies motor and cognitive cortical control to adequately perform a step. Time-frequency analysis enables to study induced changes in EEG activity in different frequency bands. Such analysis reflects cortical activity implied in stabilized gait control but also in more challenging tasks (obstacle crossing, changes in speed, dual tasks…). These spectral patterns are directly influenced by the walking context but, when analyzing gait with a more demanding attentional task, cortical areas other than the sensorimotor cortex (prefrontal, posterior parietal cortex, etc.) seem specifically implied. While the muscular activity of legs and cortical activity are coupled, the precise role of the motor cortex to control the level of muscular contraction according to the gait task remains debated. The decoding of this brain activity is a necessary step to build valid brain–computer interfaces able to generate gait artificially. Full article

(This article belongs to the Special Issue Rhythmic Motor Pattern Generation)

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