Adaptation to sequence force perturbation during vertical and horizontal reaching movement—averaging the past or predicting the future?

Mawase, Firas; Karniel, Amir

doi:10.3389/fnsys.2012.00060

Cited by 8 publications

(8 citation statements)

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“…Accordingly, MF control is largely based on estimates of the expected value of dynamics (Scheidt et al, 2001;Takahashi et al, 2001;Mawase and Karniel, 2012) without a safety margin. We thus designed a series of experiments to compare how the control of GFs and MFs is affected by environmental variability.…”

Section: Introductionmentioning

confidence: 99%

Flexible Control of Safety Margins for Action Based on Environmental Variability

Hadjiosif¹,

Smith

2015

Journal of Neuroscience

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To reduce the risk of slip, grip force (GF) control includes a safety margin above the force level ordinarily sufficient for the expected load force (LF) dynamics. The current view is that this safety margin is based on the expected LF dynamics, amounting to a static safety factor like that often used in engineering design. More efficient control could be achieved, however, if the motor system reduces the safety margin when LF variability is low and increases it when this variability is high. Here we show that this is indeed the case by demonstrating that the human motor system sizes the GF safety margin in proportion to an internal estimate of LF variability to maintain a fixed statistical confidence against slip. In contrast to current models of GF control that neglect the variability of LF dynamics, we demonstrate that GF is threefold more sensitive to the SD than the expected value of LF dynamics, in line with the maintenance of a 3-sigma confidence level. We then show that a computational model of GF control that includes a variability-driven safety margin predicts highly asymmetric GF adaptation between increases versus decreases in load. We find clear experimental evidence for this asymmetry and show that it explains previously reported differences in how rapidly GFs and manipulatory forces adapt. This model further predicts bizarre nonmonotonic shapes for GF learning curves, which are faithfully borne out in our experimental data. Our findings establish a new role for environmental variability in the control of action.

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Section: Introductionmentioning

confidence: 99%

Flexible Control of Safety Margins for Action Based on Environmental Variability

Hadjiosif¹,

Smith

2015

Journal of Neuroscience

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“…If the reaching speed would be quite different due to anticipation, then the perturbation applied by a velocity-dependent force field would differ across trials and participants as a result. Donchin and Shadmehr (2002) found participants were not able to learn random peak velocity force fields, another study also supported their findings (Mawase & Karniel, 2012). Therefore, using a distance-dependent force field, we ensured that all participants would experience the same peak sensorimotor perturbation, regardless of the reaching speed and added anticipatory information.…”

Section: Sensorimotor Adaptation Occurred Under Complex Force Fields 2mentioning

confidence: 57%

“…Force magnitudes could be another such variable, as it is related to the sensorimotor perturbation itself. Previous studies found participants were not able to adapt to randomly changing force magnitudes (Donchin & Shadmehr, 2002;Mawase & Karniel, 2012), so there may be limitations to this. A systematic study of different combinations of the two is needed.…”

Section: Implications and Future Directionsmentioning

confidence: 95%

“…The individual reaching directions examined in experiment 1 showed different adaptation magnitudes. Many force field adaptation tasks investigate only one reaching direction (e.g., forward reaching) (Mawase & Karniel, 2012), or average reaching errors from all directions (e.g., center-out reaching) (Criscimagna-Hemminger, Bastian, & Shadmehr, 2010). In experiment 1,…”

Section: Sensorimotor Adaptation Occurred Under Complex Force Fields 2mentioning

confidence: 99%

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The effect of sequence learning on sensorimotor adaptation

Liu

Block

2020

Preprint

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AbstractMotor skill learning involves both sensorimotor adaptation (calibrating the response to task dynamics and kinematics), and sequence learning (executing the task elements in the correct order at the necessary speed). These processes typically occur together in natural behavior and share much in common, such as working memory demands, development, and possibly neural substrates. However, sensorimotor and sequence learning are usually studied in isolation in research settings, for example as force field adaptation or serial reaction time tasks (SRTT), respectively. It is therefore unclear whether having predictive sequence information during sensorimotor adaptation would facilitate performance, perhaps by improving sensorimotor planning, or if it would impair performance, perhaps by occupying neural resources needed for sensorimotor learning. Here we evaluated adaptation to a distance-dependent force field in two different SRTT contexts: In Experiment 1, 28 subjects reached between 4 targets in a sequenced or random order. In Experiment 2, 40 subjects reached to one target, but 3 force field directions were applied in a sequenced or random order. We did not observe any consistent influence of target position sequence on force field adaptation in Experiment 1. However, sequencing of force field directions facilitated sensorimotor adaptation and retention in Experiment 2. This is inconsistent with the idea that sensorimotor and sequence learning share neural resources in any mutually exclusive fashion. These findings indicate that under certain conditions, perhaps especially when the sequence is related to the sensorimotor perturbation itself as in Experiment 2, sequence learning may interact with sensorimotor learning in a facilitatory manner.

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“…Several studies showed that when exposed to novel load forces, manipulation and grip forces are adjusted in a different manner. Manipulation force control is mainly based on the estimation of the averaged external load forces [76,77]. In contrast, the predictive grip force control is highly sensitive to load variability [6], and is primarily operated to maintain a consistent GF/LF ratio with an additional safety margin to prevent slippage [22,23].…”

Section: Discussionmentioning

confidence: 99%

The effect of tactile augmentation on manipulation and grip force control during force-field adaptation

Avraham

Nisky

2020

J NeuroEngineering Rehabil

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Background: When exposed to a novel dynamic perturbation, participants adapt by changing their movements' dynamics. This adaptation is achieved by constructing an internal representation of the perturbation, which allows for applying forces that compensate for the novel external conditions. To form an internal representation, the sensorimotor system gathers and integrates sensory inputs, including kinesthetic and tactile information about the external load. The relative contribution of the kinesthetic and tactile information in force-field adaptation is poorly understood. Methods: In this study, we set out to establish the effect of augmented tactile information on adaptation to forcefield. Two groups of participants received a velocity-dependent tangential skin deformation from a custom-built skin-stretch device together with a velocity-dependent force-field from a kinesthetic haptic device. One group experienced a skin deformation in the same direction of the force, and the other in the opposite direction. A third group received only the velocity-dependent force-field. Results: We found that adding a skin deformation did not affect the kinematics of the movement during adaptation. However, participants who received skin deformation in the opposite direction adapted their manipulation forces faster and to a greater extent than those who received skin deformation in the same direction of the force. In addition, we found that skin deformation in the same direction to the force-field caused an increase in the applied grip-force per amount of load force, both in response and in anticipation of the stretch, compared to the other two groups. Conclusions: Augmented tactile information affects the internal representations for the control of manipulation and grip forces, and these internal representations are likely updated via distinct mechanisms. We discuss the implications of these results for assistive and rehabilitation devices.

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Adaptation to sequence force perturbation during vertical and horizontal reaching movement—averaging the past or predicting the future?

Cited by 8 publications

References 50 publications

Flexible Control of Safety Margins for Action Based on Environmental Variability

Flexible Control of Safety Margins for Action Based on Environmental Variability

The effect of sequence learning on sensorimotor adaptation

The effect of tactile augmentation on manipulation and grip force control during force-field adaptation

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