Origins of Timing Errors in Human Sensorimotor Coordination

Chen, Yanqing; Ding, Mingzhou; Kelso, J. A. Scott

doi:10.1080/00222890109601897

Cited by 92 publications

(90 citation statements)

References 19 publications

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“…62 1/f scaling and fractality were observed in a range of human activity. Standard tools used to asses the structure of variability were applied to perceptual-motor behaviors such as finger tapping, [63][64][65][66] eye movements, 67 and locomotion. [68][69][70][71] Warren 72 developed a general modeling framework for behavioral dynamics, articulated in terms of the emergence of behavioral trajectories from informational and forceful (mechanical) animalenvironment and perception-action couplings in the context of behavioral goals (modeled as attractors) and obstacles (modeled as repellers).…”

Section: Complexity and Self-organizationmentioning

confidence: 99%

Dynamics of cognition

Riley

Holden

2012

WIRES Cognitive Science

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The application of dynamical systems methods and concepts to cognitive phenomena has broadened the range of testable hypotheses and theoretical narratives available to cognitive scientists. Most research in cognitive dynamics tests the degree to which observed cognitive performance is consistent with one or another core phenomena associated with complex dynamical systems, such as tests for phase transitions, coupling among processes, or scaling laws. Early applications of dynamical systems theory to perceptual-motor performance and developmental psychology paved the way for more recent applications of dynamical systems analyses, models, and theoretical concepts in areas such as learning, memory, speech perception, decision making, problem solving, and reading, among others. Reviews of the empirical results of both foundational and contemporary cognitive dynamics are provided. © 2012 John Wiley & Sons, Ltd. How to cite this article:WIREs Cogn Sci 2012, 3:593-606. doi: 10.1002/wcs.1200 INTRODUCTION Adynamical system is simply one that changes over time (see Box 1). It is apparent that many of the processes cognitive scientists study-development, learning, the spread of activation in a semantic network, changing patterns of cortical activity, motor behavior, and so on-are intrinsically dynamical. Dynamical systems theory supplies new tools and concepts for understanding these and other cognitive phenomena. The theory offers a full complement of analytical methods (e.g., nonlinear time series analyses) and modeling strategies (e.g., differential equations). Most importantly, it motivates novel theoretical and empirical questions: One may explore the relative stability of a cognitive activity, test for meta-or multi-stability, or test for empirical patterns consistent with scaling behavior, emergence, and self-organization.These kinds of questions complement those posed by mainstream cognitive science-which traditionally has emphasized static properties of mind such as symbolic representations or structural mechanisms of information processing-by focusing explicitly on change 1-9 (see, e.g., Elman 10 for a dynamical interpretation of connectionist models). Much work in cognitive dynamics was inspired by parallel * Correspondence to: michael.riley@uc.edu Center for Cognition, Action, & Perception, Department of Psychology, University of Cincinnati, Cincinnati, OH, USA efforts to understand the dynamics of perceptionaction. [11][12][13][14][15] Early and significant progress emerged in the domain of motor coordination, where the behavioral phenomena were more obviously dynamical and high-resolution measurement technologies were more readily available. 16 The dynamical account of interlimb rhythmic coordination 12,14 is an example of an early success.Research in cognitive dynamics is often allied with some version of embodiment. [17][18][19][20][21] Dynamical systems were sometimes framed as replacements for computational-representational accounts, 8,19 as distinct but complementary, 22 or even as consistent with inform...

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Section: Complexity and Self-organizationmentioning

confidence: 99%

Dynamics of cognition

Riley

Holden

2012

WIRES Cognitive Science

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“…Considerable research has investigated the coordination dynamics and timing errors of finger taps relative to metronome pulses (e.g., Chen, Ding, & Kelso, 2001;Engstrom, Kelso, & Holroyd, 1996;Kelso et al, 1990;Kelso, Fink, DeLaplain, & Carson, 2001), but research on speech-metronome timing is sparse (Fowler, 1983;van Lieshout, 2003;van Lieshout, Hulstijn, & Peters, 1996). The pioneering research by Kelso et al (1983) explored the effects of the cross-coupling of cyclical speech and hand movements by requiring participants to spontaneously choose both a comfortable rate as well as a subharmonic rate of repetitive speech relative to cyclic finger movements.…”

Section: Attention and Coordination Dynamicsmentioning

confidence: 99%

Intentional and attentional dynamics of speech–hand coordination

Treffner

Peter

2002

Human Movement Science

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Interest is rapidly growing in the hypothesis that natural language emerged from a more primitive set of linguistic acts based primarily on manual activity and hand gestures. Increasingly, researchers are investigating how hemispheric asymmetries are related to attentional and manual asymmetries (i.e., handedness). Both speech perception and production have origins in the dynamical generative movements of the vocal tract known as articulatory gestures. Thus, the notion of a ''gesture'' can be extended to both hand movements and speech articulation. The generative actions of the hands and vocal tract can therefore provide a basis for the (direct) perception of linguistic acts. Such gestures are best described using the methods of dynamical systems analysis since both perception and production can be described using the same commensurate language. Experiments were conducted using a phase transition paradigm to examine the coordination of speech-hand gestures in both left-and right-handed individuals. Results address coordination (in-phase vs. anti-phase), hand (left vs. right), lateralization (left vs. right hemisphere), focus of attention (speech vs. tapping), and how dynamical constraints provide a foundation for human communicative acts. Predictions from the asymmetric HKB equation confirm the attentional basis of functional asymmetry. Of significance is a new understanding of the role of perceived synchrony (p-centres) during intentional cases of gestural coordination.

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“…Psychophysical time series have been known since the early 1950s to be nonrandomly clustered (2), and later studies have shown that hit-rate and/or reaction-time fluctuations in CPT data are fractal and power-law autocorrelated across hundreds of seconds (3)(4)(5)(6)(7)(8)(9). The biological origins and relevance of these dynamic, however, remain unclear (10,11).…”

mentioning

confidence: 99%

Neuronal long-range temporal correlations and avalanche dynamics are correlated with behavioral scaling laws

Zhigalov

Hirvonen

Korhonen

et al. 2013

Proc. Natl. Acad. Sci. U.S.A.

419

435

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Scale-free fluctuations are ubiquitous in behavioral performance and neuronal activity. In time scales from seconds to hundreds of seconds, psychophysical dynamics and the amplitude fluctuations of neuronal oscillations are governed by power-law-form longrange temporal correlations (LRTCs). In millisecond time scales, neuronal activity comprises cascade-like neuronal avalanches that exhibit power-law size and lifetime distributions. However, it remains unknown whether these neuronal scaling laws are correlated with those characterizing behavioral performance or whether neuronal LRTCs and avalanches are related. Here, we show that the neuronal scaling laws are strongly correlated both with each other and with behavioral scaling laws. We used source reconstructed magneto-and electroencephalographic recordings to characterize the dynamics of ongoing cortical activity. We found robust power-law scaling in neuronal LRTCs and avalanches in resting-state data and during the performance of audiovisual threshold stimulus detection tasks. The LRTC scaling exponents of the behavioral performance fluctuations were correlated with those of concurrent neuronal avalanches and LRTCs in anatomically identified brain systems. The behavioral exponents also were correlated with neuronal scaling laws derived from a resting-state condition and with a similar anatomical topography. Finally, despite the difference in time scales, the scaling exponents of neuronal LRTCs and avalanches were strongly correlated during both rest and task performance. Thus, long and short time-scale neuronal dynamics are related and functionally significant at the behavioral level. These data suggest that the temporal structures of human cognitive fluctuations and behavioral variability stem from the scaling laws of individual and intrinsic brain dynamics.spontaneous activity | threshold detection | criticality H uman cognitive and behavioral performance is highly variable and exhibits slow fluctuations that are salient in continuous performance tasks (CPTs) (1). Psychophysical time series have been known since the early 1950s to be nonrandomly clustered (2), and later studies have shown that hit-rate and/or reaction-time fluctuations in CPT data are fractal and power-law autocorrelated across hundreds of seconds (3-9). The biological origins and relevance of these dynamic, however, remain unclear (10, 11).Similar to those in behavioral performance, the fluctuations of collective neuronal activity at many levels of the nervous system are scale-free and governed by power-law scaling laws. On short time scales (10 −3 −10 −1 s), negative deflections in local field potentials form spatiotemporal cascades of activity, "neuronal avalanches" (32-34), the size and lifetime distributions of which are power laws akin to those of a critical branching process (33). Neuronal avalanches characterize spontaneous neuronal network activity in organotypic cultures (32), brain slices in vitro (35), and monkey (34) and human cortex (36) in vivo. In monkey cortex, the avalanche...

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Origins of Timing Errors in Human Sensorimotor Coordination

Cited by 92 publications

References 19 publications

Dynamics of cognition

Dynamics of cognition

Intentional and attentional dynamics of speech–hand coordination

Neuronal long-range temporal correlations and avalanche dynamics are correlated with behavioral scaling laws

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