Intermittent Motor Control: The “drift-and-act” Hypothesis

Milton, John

doi:10.1007/978-1-4614-5465-6_9

Cited by 26 publications

(38 citation statements)

References 93 publications

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“…[1,2,3]). In particular, much research has been aimed at understanding the mechanisms of discontinuous, or intermittent control in the context of human balance control [4,5].…”

Section: Introductionmentioning

confidence: 99%

“…Traditionally in the models of stick balancing, control is switched on when the stick angle exceeds certain threshold value [4]. Models which incorporate threshold-driven control activation can usually explain much dynamics observed in experiments.…”

Section: Introductionmentioning

confidence: 99%

“…However, recent investigations of virtual overdamped stick balancing have revealed that control activations at large deviations occurs much more frequently then predicted by threshold-driven mechanism [6]. Besides, some of the most peculiar phenomena observed in human control behavior still remain unexplained by the models based on threshold-driven control activaProceedings of the 48th ISCIE International Symposium on Stochastic Systems Theory and Its Applications Fukuoka, Nov. [4][5]2016 tion. Importantly, such phenomena include high occurrence of large fluctuations in human-controlled systems, which result, e.g., in falls during stick balancing or quiet standing [8].…”

Section: Introductionmentioning

confidence: 99%

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Non-equilibrium phase transition in the model of human virtual stick balancing

Zgonnikov

Lubashevsky

2017

Stochastic Systems Theory and its Applications (SSS)

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Archetypal stick balancing task represents a wide class of unstable processes under human control. The currently dominant theory of human control in stick balancing is based on the concept of discontinuous, or intermittent control. Traditionally, intermittent control models involve threshold-driven control activation, however, recently it has been demonstrated that, in a simple virtual stick balancing task, some basic properties of human control activation mechanisms can only be reflected by more sophisticated, noise-driven models. The aim of the present paper is to demonstrate that the previously introduced double-well model of noise-driven intermittent control activation can reproduce the experimentally observed human behaviours under various conditions. We show that the model successfully reproduces the experimental distributions of actions points (stick angle values triggering activation of human control) obtained in two previously reported experiments. Moreover, we show that a slight change in the model's noise intensity parameter leads to a sudden shift of model distributions, that is, a non-equilibrium phase transition is observed. Our results extend the current understanding of the concept of noise-driven control activation, suggesting that it is applicable in a variety of experimental setups. The two discovered phases of the double-well model correspond to two different modes of control activation in human operators; physiological basis of these modes has to be investigated in future studies.

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“…[1,2,3]). In particular, much research has been aimed at understanding the mechanisms of discontinuous, or intermittent control in the context of human balance control [4,5].…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Non-equilibrium phase transition in the model of human virtual stick balancing

Zgonnikov

Lubashevsky

2017

Stochastic Systems Theory and its Applications (SSS)

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“…During the last decades there have been found much evidence for a novel paradigm of human actions in balancing various systems-human intermittent control (for a review see, e.g., [1,2,3,4,5]). This paradigm implies that human control is discontinuous, repeatedly switching on and off instead of being always active throughout the process.…”

Section: Introductionmentioning

confidence: 99%

“…Recently the event-driven models have become widely employed [10,1,11,4]. They are built up on the fact that humans cannot detect small deviations of the controlled system from a desired state and for this reason are not able to control the system dynamics in its close proximity.…”

Section: Introductionmentioning

confidence: 99%

Cloud Type Interpretation of Statistical Properties of Human Response Delay in Pendulum Balancing

Suzuki¹,

Lubashevsky²,

Kanemoto³

2017

Stochastic Systems Theory and its Applications (SSS)

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We present the results of our experiments on studying the probabilistic properties of human response delay in balancing virtual pendulum (stick) with over-damped dynamics. The overdamping eliminates the effects of inertia and, thereby, reduces the dimensionality of the system under control. Two types simulators were employed for studying human response in the stick balancing. One of them hides the stick when it is located in some neighborhood of the upward position, the other just makes the stick unaccessible for subject's control. It enabled us to measure directly the delay time as the time lag between the moment when the pendulum becomes visible or accessible and the moment when a subject starts to move the mouse. It is demonstrated that the response delay time is characterized by a wide distribution sensitive to the particular details of stick balancing process and its possible correlations in the sequence of actions are ignorable. Besides, in experiments with the second simulator the subject's anticipation is shown to play a significant role in human control. In particular, the formal delay time can take negative values. It poses a question about the applicability of standard formalism of delayed differential equations to describing human intermittent control.

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Random Perturbations

Milton¹,

Ohira²

2014

Mathematics as a Laboratory Tool

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Intermittent Motor Control: The “drift-and-act” Hypothesis

Cited by 26 publications

References 93 publications

Non-equilibrium phase transition in the model of human virtual stick balancing

Non-equilibrium phase transition in the model of human virtual stick balancing

Cloud Type Interpretation of Statistical Properties of Human Response Delay in Pendulum Balancing

Random Perturbations

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