Is Intermittent Control the Source of the Non-Linear Oscillatory Component (0.2–2Hz) in Human Balance Control?

Loram, Ian D.; Gollee, H.; Kamp, Cornelis van de; Gawthrop, P.J.

doi:10.1109/tbme.2022.3174927

Cited by 6 publications

(21 citation statements)

References 33 publications

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“…For the upper limb, evidence from paired perturbations at inter-stimulus-intervals (ISI) of 35, 60 and 110 ms, ruled out refractoriness (delays related to ISI) at these ISI and supported the idea that long-latency reflexes implement continuous action of controllers with fixed function ( Kurtzer, 2019 ). However, a recent analysis using high quality disturbance-balance data, showed a standard, time delayed, continuous, linear-time-invariant (LTI), state-estimation, state feedback model structure with added noise could not replicate concurrently the linear response, the remnant and observed time delays ( Loram et al, 2022 ). The remnant remaining after subtraction of the linear response comprises 70–80% of the control signal, so most of the control signal is not generated by linear processes ( Loram et al, 2022 ).…”

Section: Introductionmentioning

confidence: 99%

“…However, a recent analysis using high quality disturbance-balance data, showed a standard, time delayed, continuous, linear-time-invariant (LTI), state-estimation, state feedback model structure with added noise could not replicate concurrently the linear response, the remnant and observed time delays ( Loram et al, 2022 ). The remnant remaining after subtraction of the linear response comprises 70–80% of the control signal, so most of the control signal is not generated by linear processes ( Loram et al, 2022 ). This previous data, which sets a current benchmark representing whole body balance control, required a state-predictor (108 ± 40 ms) to reproduce the observed time delays concurrently with the linear response and remnant ( Loram et al, 2022 ).…”

Section: Introductionmentioning

confidence: 99%

“…The remnant remaining after subtraction of the linear response comprises 70–80% of the control signal, so most of the control signal is not generated by linear processes ( Loram et al, 2022 ). This previous data, which sets a current benchmark representing whole body balance control, required a state-predictor (108 ± 40 ms) to reproduce the observed time delays concurrently with the linear response and remnant ( Loram et al, 2022 ). Furthermore, the most comprehensive fit was achieved by a non-linear intermittent, rather than linear continuous, predictive control model ( Loram et al, 2022 ).…”

Section: Introductionmentioning

confidence: 99%

“…This previous data, which sets a current benchmark representing whole body balance control, required a state-predictor (108 ± 40 ms) to reproduce the observed time delays concurrently with the linear response and remnant ( Loram et al, 2022 ). Furthermore, the most comprehensive fit was achieved by a non-linear intermittent, rather than linear continuous, predictive control model ( Loram et al, 2022 ). These previous results support the hypothesis that balance is non-linear and involves processes beyond long-latency reflex control.…”

Section: Introductionmentioning

confidence: 99%

“…Here we study whole body balance with the same task and apparatus reported previously to acquire data setting current benchmark quality ( Loram et al, 2022 ). Participants use their natural senses and an integrated myoelectric control from their own leg muscles to control movement of their own body while strapped to an actuated, single segment robot ( Figure 1 ).…”

Section: Introductionmentioning

confidence: 99%

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What is the contribution of voluntary and reflex processes to sensorimotor control of balance?

Cherif

Zenzeri

Loram

2022

Front. Bioeng. Biotechnol.

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The contribution to balance of spinal and transcortical processes including the long-latency reflex is well known. The control of balance has been modelled previously as a continuous, state feedback controller representing, long-latency reflexes. However, the contribution of slower, variable delay processes has not been quantified. Compared with fixed delay processes (spinal, transcortical), we hypothesize that variable delay processes provide the largest contribution to balance and are sensitive to historical context as well as current states. Twenty-two healthy participants used a myoelectric control signal from their leg muscles to maintain balance of their own body while strapped to an actuated, inverted pendulum. We study the myoelectric control signal (u) in relation to the independent disturbance (d) comprising paired, discrete perturbations of varying inter-stimulus-interval (ISI). We fit the closed loop response, u from d, using one linear and two non-linear non-parametric (many parameter) models. Model M1 (ARX) is a generalized, high-order linear-time-invariant (LTI) process with fixed delay. Model M1 is equivalent to any parametric, closed-loop, continuous, linear-time-invariant (LTI), state feedback model. Model M2, a single non-linear process (fixed delay, time-varying amplitude), adds an optimized response amplitude to each stimulus. Model M3, two non-linear processes (one fixed delay, one variable delay, each of time-varying amplitude), add a second process of optimized delay and optimized response amplitude to each stimulus. At short ISI, the myoelectric control signals deviated systematically both from the fixed delay LTI process (M1), and also from the fixed delay, time-varying amplitude process (M2) and not from the two-process model (M3). Analysis of M3 (all fixed delay and variable delay response amplitudes) showed the variable (compared with fixed) delay process 1) made the largest contribution to the response, 2) exhibited refractoriness (increased delay related to short ISI) and 3) was sensitive to stimulus history (stimulus direction 2 relative to stimulus 1). For this whole-body balance task and for these impulsive stimuli, non-linear processes at variable delay are central to control of balance. Compared with fixed delay processes (spinal, transcortical), variable delay processes provided the largest contribution to balance and were sensitive to historical context as well as current states.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

What is the contribution of voluntary and reflex processes to sensorimotor control of balance?

Cherif

Zenzeri

Loram

2022

Front. Bioeng. Biotechnol.

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Brownian processes in human motor control support descending neural velocity commands

Tessari,

Hermus,

Sugimoto-Dimitrova

et al. 2024

Sci Rep

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The motor neuroscience literature suggests that the central nervous system may encode some motor commands in terms of velocity. In this work, we tackle the question: what consequences would velocity commands produce at the behavioral level? Considering the ubiquitous presence of noise in the neuromusculoskeletal system, we predict that velocity commands affected by stationary noise would produce “random walks”, also known as Brownian processes, in position. Brownian motions are distinctively characterized by a linearly growing variance and a power spectral density that declines in inverse proportion to frequency. This work first shows that these Brownian processes are indeed observed in unbounded motion tasks e.g., rotating a crank. We further predict that such growing variance would still be present, but bounded, in tasks requiring a constant posture e.g., maintaining a static hand position or quietly standing. This hypothesis was also confirmed by experimental observations. A series of descriptive models are investigated to justify the observed behavior. Interestingly, one of the models capable of accounting for all the experimental results must feature forward-path velocity commands corrupted by stationary noise. The results of this work provide behavioral support for the hypothesis that humans plan the motion components of their actions in terms of velocity.

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Behavioral Consequences of Velocity Commands: Brownian Processes in Human Motor Tasks

Tessari,

Hermus,

Sugimoto-Dimitrova

et al. 2023

Preprint

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Human postural control exhibits stochastic behavior resembling a random walk, which implies unbounded growth of position variance. Here we show that unbounded position variance is indeed observed in a common task, turning a crank. In postural tasks, intermittent control has been proposed to limit position variance. We further show that when position variance is unbounded, it displays a distinctive signature of underlying Brownian motion, a low-frequency power spectrum that declines at -20 dB/decade but exhibits flattening in bounded tasks. Remarkably, a descriptive model of a control system competent to account for all of these data must feature a forward-path velocity command corrupted by stationary noise. This provides independent behavioral support for the theory that the brain encodes motion commands in terms of velocity.

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Is Intermittent Control the Source of the Non-Linear Oscillatory Component (0.2–2Hz) in Human Balance Control?

Cited by 6 publications

References 33 publications

What is the contribution of voluntary and reflex processes to sensorimotor control of balance?

What is the contribution of voluntary and reflex processes to sensorimotor control of balance?

Brownian processes in human motor control support descending neural velocity commands

Behavioral Consequences of Velocity Commands: Brownian Processes in Human Motor Tasks

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