Multifractal roots of suprapostural dexterity

Kelty-Stephen

2022

J. R. Soc. Interface.

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The stochastic processes underlying the growth and stability of biological and psychological systems reveal themselves when far-from-equilibrium. Far-from-equilibrium, non-ergodicity reigns. Non-ergodicity implies that the average outcome for a group/ensemble (i.e. of representative organisms/minds) is not necessarily a reliable estimate of the average outcome for an individual over time. However, the scientific interest in causal inference suggests that we somehow aim at stable estimates of the cause that will generalize to new individuals in the long run. Therefore, the valid analysis must extract an ergodic stationary measure from fluctuating physiological data. So the challenge is to extract statistical estimates that may describe or quantify some of this non-ergodicity (i.e. of the raw measured data) without themselves (i.e. the estimates) being non-ergodic. We show that traditional linear statistics such as the standard deviation, coefficient of variation and root mean square can break ergodicity. Time series of statistics addressing sequential structure and its potential nonlinearity: fractality and multi-fractality, change in a time-independent way and fulfil the ergodic assumption. Complementing traditional linear indices with fractal and multi-fractal indices would empower the study of stochastic far-from-equilibrium biological and psychological dynamics.

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Ergodic descriptors of non-ergodic stochastic processes

Kelty-Stephen

2022

J. R. Soc. Interface.

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“…The following summary of the metrics is brief and mathematically abbreviated. We invite readers interested in a longer, more descriptive explanation to examine an open-access resource [66] for both a more conversational introduction and R syntax for estimating these metrics.…”

Section: Methodsmentioning

confidence: 99%

Perceiving and remembering speech depend on multifractal nonlinearity in movements producing and exploring speech

Bloomfield

Lane

et al. 2021

J. R. Soc. Interface.

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Speech perception and memory for speech require active engagement. Gestural theories have emphasized mainly the effect of speaker's movements on speech perception. They fail to address the effects of listener movement, focusing on communication as a boundary condition constraining movement among interlocutors. The present work attempts to break new ground by using multifractal geometry of physical movement as a common currency for supporting both sides of the speaker–listener dyads. Participants self-paced their listening to a narrative, after which they completed a test of memory querying their narrative comprehension and their ability to recognize words from the story. The multifractal evidence of nonlinear interactions across timescales predicted the fluency of speech perception. Self-pacing movements that enabled listeners to control the presentation of speech sounds constituted a rich exploratory process. The multifractal nonlinearity of this exploration supported several aspects of memory for the perceived spoken language. These findings extend the role of multifractal geometry in the speaker's movements to the narrative case of speech perception. In addition to posing novel basic research questions, these findings make a compelling case for calibrating multifractal structure in text-to-speech synthesizers for better perception and memory of speech.

“…Thus, it is believed that instructing athletes by directing their perceptual linkages outward to the visual field supports higher task performance as well as leads to more expert-like movement and physiology. QE research opens a fascinating vantage point to situate ongoing research on linkages anchoring organisms to their visual contexts and the synergies transforming visual information into action (e.g., [14][15][16]). Research on QE has mostly examined the visual-cognitive bases for the relatively more extraverted gaze into the task context [8,17,18], and the relationship of QE to the body, the brain, and the nervous system has received relatively less attention [19][20][21].…”

Section: Quiet Eye Versus Technical Trainingmentioning

confidence: 99%

“…QE research opens a fascinating vantage point on the perceptual linkages anchoring organisms to their visual contexts and the synergies transforming visual information into action (e.g., Kelty-Stephen et al, 2020; Mangalam, Lee, et al, 2021; Profeta & Turvey, 2018). Research on QE has mostly examined the visual-cognitive bases for the relatively more extraverted gaze into the task context (Panchuk & Vickers, 2006; Rienhoff et al, 2016; Vickers, 2011), and the relationship of QE to the body, the brain, and the nervous system has received relatively less attention (Davids & Araújo, 2016; Renshaw et al, 2019; Shine et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Multifractality in postural sway supports quiet eye training in aiming tasks: A study of golf putting

Jacobson¹,

Berleman-Paul²,

et al. 2020

Preprint

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The 'quiet eye' (QE) approach to visually-guided aiming behavior invests fully in perceptual information's potential to organize coordinated action. Sports psychologists refer to QE as the stillness of the eyes during aiming tasks and increasingly into self- and externally-paced tasks. Amidst the 'noisy' fluctuations of the athlete's body, quiet eyes might leave fewer saccadic interruptions to the coupling between postural sway and optic flow. Multifractality in postural sway is a robust predictor of both visual and haptic perceptual responses. Postural sway generates optic flow centered on an individual's eye height. So, we manipulated the eye height part way through a golf-putting task for participants trained in QE or trained technically as per conventional golf putting. We predicted that perturbing the eye height by attaching wooden blocks below the feet would perturb the putting more so in QE-trained participants than in those trained technically. We also predicted that responses to this perturbation would depend on multifractality in postural sway. Specifically, we predicted that less multifractality would predict more adaptive responses to the perturbation and higher putting accuracy. Results supported both predictions. QE training and lower multifractality led to more frequent successful putts, and the perturbation of eye height led to less frequent successful putts, particularly for QE-trained participants. Models of radial error (i.e., the distance between the ball's final position and the hole) indicated that lower estimates of multifractality due to nonlinearity coincided with a more adaptive response to the perturbation. These results challenge the past suggestions that reduced multifractality might be a signature of diseased posture. Instead, they suggest that reduced multifractality may act in a context-sensitive manner to restrain motoric degrees of freedom to achieve the task goal.