Influence of Viscous Loads on Motor Planning

2007 ◽  
Vol 98 (2) ◽  
pp. 870-877 ◽  
Author(s):  
Kurt A. Thoroughman ◽  
Wei Wang ◽  
Dimitre N. Tomov
Keyword(s):  
Force Field ◽  
Human Behavior ◽  
Motor Planning ◽  
Movement Planning ◽  
Viscous Force ◽  
Learned Behavior ◽  
Viscous Forces ◽  
Minimum Jerk ◽  
Human Arm ◽  
Minimum Torque

Here we computationally investigate how encumbering the hand could alter predictions made by the minimum torque change (MTC) and minimum endpoint variance hypotheses (MEPV) of movement planning. After minutes of training, people have made arm trajectories in a robot-generated viscous force field that were similar to previous baseline trajectories without the force field. We simulate the human arm interacting with this viscous load. We found that the viscous forces clearly differentiated MTC and MEPV predictions from both minimum-jerk predictions and from human behavior. We conclude that learned behavior in the viscous environment could arise from minimizing kinematic costs but could not arise from a minimization of either torque change or endpoint variance.

scholarly journals Contribution of Viscous Forces to Avalanche Dynamics

1989 ◽  
Vol 13 ◽  
pp. 202-206 ◽  
Author(s):  
K. Nishimura ◽  
N. Maeno
Keyword(s):  
Dry Friction ◽  
Kinematic Viscosity ◽  
Viscosity Coefficient ◽  
Viscous Force ◽  
Viscous Resistance ◽  
Resistance Factors ◽  
Viscous Forces ◽  
Viscosity Coefficients ◽  
Avalanche Dynamics ◽  
The Individual

Mini-avalanche systems were constructed both in a low-temperature laboratory and in a snowfield, and the behaviour of the flowing snow was observed in each case. Velocity profiles for the individual snow particles were determined and these implied that a viscous force, which has been neglected in most previous numerical simulations of snow-avalanche motion, needs to be taken into account for many avalanches. Kinematic viscosity coefficients for the fluidized snow were also measured using a modified Stormer-type viscometer. Substituting the dry-friction value and the kinematic viscosity coefficient for fluidized snow into the equation for avalanche motion, numerical simulation of natural events was achieved for the Shiai-dani region. Taking viscous resistance factors into account led to the conclusion that the magnitude of turbulent resistance of snow in avalanche systems is probably much smaller than that represented by the values previously in use.

scholarly journals Motor learning in reaching tasks leads to homogenization of task space error distribution

2021 ◽  
Author(s):  
Puneet Singh ◽  
Oishee Ghosal ◽  
Aditya Murthy ◽  
Ashitava Ghodal
Keyword(s):  
Motor Learning ◽  
Force Field ◽  
Error Distribution ◽  
Task Space ◽  
Field Perturbation ◽  
Directional Dependence ◽  
Reaching Tasks ◽  
Space Error ◽  
Human Arm ◽  
Point To Point

A human arm, up to the wrist, is often modelled as a redundant 7 degree-of-freedom serial robot. Despite its inherent nonlinearity, we can perform point-to-point reaching tasks reasonably fast and with reasonable accuracy in the presence of external disturbances and noise. In this work, we take a closer look at the task space error during point-to-point reaching tasks and learning during an external force-field perturbation. From experiments and quantitative data, we confirm a directional dependence of the peak task space error with certain directions showing larger errors than others at the start of a force-field perturbation, and the larger errors are reduced with repeated trials implying learning. The analysis of the experimental data further shows that a) the distribution of the peak error is made more uniform across directions with trials and the error magnitude and distribution approaches the value when no perturbation is applied, b) the redundancy present in the human arm is used more in the direction of the larger error, and c) homogenization of the error distribution is not seen when the reaching task is performed with the non-dominant hand. The results support the hypothesis that not only magnitude of task space error, but the directional dependence is reduced during motor learning and the workspace is homogenized possibly to increase the control efficiency and accuracy in point-to-point reaching tasks. The results also imply that redundancy in the arm is used to homogenize the workspace, and additionally since the bio-mechanically similar dominant and non-dominant arms show different behaviours, the homogenizing is actively done in the central nervous system.

Experimentally Confirmed Mathematical Model for Human Control of a Non-Rigid Object

2004 ◽  
Vol 91 (3) ◽  
pp. 1158-1170 ◽  
Author(s):  
Jonathan B. Dingwell ◽  
Christopher D. Mah ◽  
Ferdinando A. Mussa-Ivaldi
Keyword(s):  
Mathematical Model ◽  
Human Subjects ◽  
Movement Planning ◽  
Relative Speed ◽  
Rigid Object ◽  
Hand Motion ◽  
Human Control ◽  
Rigid Objects ◽  
Minimum Jerk ◽  
Neuroscience Research

Determining the principles used to plan and execute movements is a fundamental question in neuroscience research. When humans reach to a target with their hand, they exhibit stereotypical movements that closely follow an optimally smooth trajectory. Even when faced with various perceptual or mechanical perturbations, subjects readily adapt their motor output to preserve this stereotypical trajectory. When humans manipulate non-rigid objects, however, they must control the movements of the object as well as the hand. Such tasks impose a fundamentally different control problem than that of moving one's arm alone. Here, we developed a mathematical model for transporting a mass-on-a-spring to a target in an optimally smooth way. We demonstrate that the well-known “minimum-jerk” model for smooth reaching movements cannot accomplish this task. Our model extends the concept of smoothness to allow for the control of non-rigid objects. Although our model makes some predictions that are similar to minimum jerk, it predicts distinctly different optimal trajectories in several specific cases. In particular, when the relative speed of the movement becomes fast enough or when the object stiffness becomes small enough, the model predicts that subjects will transition from a uni-phasic hand motion to a bi-phasic hand motion. We directly tested these predictions in human subjects. Our subjects adopted trajectories that were well-predicted by our model, including all of the predicted transitions between uni- and bi-phasic hand motions. These findings suggest that smoothness of motion is a general principle of movement planning that extends beyond the control of hand trajectories.

Different Predictions by the Minimum Variance and Minimum Torque-Change Models on the Skewness of Movement Velocity Profiles

2004 ◽  
Vol 16 (10) ◽  
pp. 2021-2040 ◽  
Author(s):  
Hirokazu Tanaka ◽  
Meihua Tai ◽  
Ning Qian
Keyword(s):  
Velocity Profile ◽  
Velocity Profiles ◽  
Minimum Variance ◽  
Movement Planning ◽  
System Stability ◽  
Movement Duration ◽  
Movement Velocity ◽  
Change Models ◽  
External Forces ◽  
Minimum Torque

We investigated the differences between two well-known optimization principles for understanding movement planning: the minimum variance (MV) model of Harris and Wolpert (1998) and the minimum torque change (MTC) model of Uno, Kawato, and Suzuki (1989). Both models accurately describe the properties of human reaching movements in ordinary situations (e.g., nearly straight paths and bell-shaped velocity profiles). However, we found that the two models can make very different predictions when external forces are applied or when the movement duration is increased. We considered a second-order linear system for the motor plant that has been used previously to simulate eye movements and single-joint arm movements and were able to derive analytical solutions based on the MV and MTC assumptions. With the linear plant, the MTC model predicts that the movement velocity profile should always be symmetrical, independent of the external forces and movement duration. In contrast, the MV model strongly depends on the movement duration and the system's degree of stability; the latter in turn depends on the total forces. The MV model thus predicts a skewed velocity profile under many circumstances. For example, it predicts that the peak location should be skewed toward the end of the movement when the movement duration is increased in the absence of any elastic force. It also predicts that with appropriate viscous and elastic forces applied to increase system stability, the velocity profile should be skewed toward the beginning of the movement. The velocity profiles predicted by the MV model can even show oscillations when the plant becomes highly oscillatory. Our analytical and simulation results suggest specific experiments for testing the validity of the two models.

Colored context cues can facilitate the ability to learn and to switch between multiple dynamical force fields

2011 ◽  
Vol 106 (1) ◽  
pp. 163-183 ◽  
Author(s):  
Touria Addou ◽  
Nedialko Krouchev ◽  
John F. Kalaska
Keyword(s):  
Force Field ◽  
Color Change ◽  
Force Fields ◽  
Human Subjects ◽  
Elbow Flexion ◽  
Motor Output ◽  
Viscous Force ◽  
Dynamic Force ◽  
Flexion Extension ◽  
Context Cues

We tested the efficacy of color context cues during adaptation to dynamic force fields. Four groups of human subjects performed elbow flexion/extension movements to move a cursor between targets on a monitor while encountering a resistive (Vr) or assistive (Va) viscous force field. They performed two training sets of 256 trials daily, for 10 days. The monitor background color changed (red, green) every four successful trials but provided different degrees of force field context information to each group. For the irrelevant-cue groups, the color changed every four trials, but one group encountered only the Va field and the other only the Vr field. For the reliable-cue group, the force field alternated between Va and Vr each time the monitor changed color (Vr, red; Va, green). For the unreliable-cue group, the force field changed between Va and Vr pseudorandomly at each color change. All subjects made increasingly stereotyped movements over 10 training days. Reliable-cue subjects typically learned the association between color cues and fields and began to make predictive changes in motor output at each color change during the first day. Their performance continued to improve over the remaining days. Unreliable-cue subjects also improved their performance across training days but developed a strategy of probing the nature of the field at each color change by emitting a default motor response and then adjusting their motor output in subsequent trials. These findings show that subjects can extract explicit and implicit information from color context cues during force field adaptation.

Application of Virtual Environments to Assessment of Human Motor Learning During Reaching Movements

2009 ◽  
Vol 18 (2) ◽  
pp. 112-124 ◽  
Author(s):  
Ali Asadi Nikooyan ◽  
Amir Abbas Zadpoor
Keyword(s):  
Force Field ◽  
Force Fields ◽  
Physical World ◽  
Reaching Movements ◽  
Viscous Force ◽  
Virtual Object ◽  
Learning Mechanisms ◽  
Reaching Task ◽  
Third Phase ◽  
Virtual Force

This paper studies learning of reaching movements in a dynamically variable virtual environment specially designed for this purpose. Learning of reaching movements in the physical world has been extensively studied by several researchers. In most of those studies, the subjects are asked to exercise reaching movements while being exposed to real force fields exerted through a robotic manipulandum. Those studies have contributed to our understanding of the mechanisms used by the human cognitive system to learn reaching movements in the physical world. The question that remains to be answered is how the learning mechanism in the physical world relates to its counterpart in the virtual world where the real force fields are replaced by virtual force fields. A limited number of studies have already addressed this question and have shown that there are, actually, quite a number of relationships between the learning mechanisms in these two different environments. In this study, we are focused on gaining a more in-depth understanding of these relationships. In our experiments, the subjects are asked to guide a virtual object to a desired target on a computer screen using a mouse. The movement of the virtual object is affected by a viscous virtual force field that is sensed by the examinees through their visual system. Three groups of examinees are used for the experiments. All the examinees are first trained in the null-field condition. Then, the viscous force field is introduced either suddenly (for the two first groups) or gradually (for the last group). While the first and third groups of the examinees used their dominant arm to guide the virtual object in the second step, the second group used their nondominant arm. Generalization of the learning from the dominant to the nondominant arm and vice versa was studied in the third phase of the experiments. Finally, the force field was removed and the examinees were asked to repeat the reaching task to study the so-called aftereffects phenomenon. The results of the experiments are compared with the studies performed in the physical world. It is shown that the trends of learning and generalization are similar to what is observed in the physical world for a sudden application of the virtual force field. However, the generalization behavior of the examinees is somewhat different from the physical world if the force field is gradually applied.

Two-dimensional sink flow of a stratified fluid contained in a duct

1972 ◽  
Vol 53 (2) ◽  
pp. 329-349 ◽  
Author(s):  
Jorg Imberger
Keyword(s):  
Layer Thickness ◽  
Schmidt Number ◽  
Critical Distance ◽  
Force Balance ◽  
Viscous Force ◽  
Order Unity ◽  
Outer Flow ◽  
Viscous Forces ◽  
Primary Focus ◽  
Inertia Forces

A reservoir is assumed to be filled with water which has a linear variation of density with depth. The geometry of the boundaries is simplified to a parallel walled duct with the line sink at the centre of the fluid. The primary focus is on partitioning the flow into distinct flow regimes and predicting the withdrawal-layer thickness as a function of the distance from the sink; the predictions are verified experimentally.For fluids with a Schmidt number of order unity, the withdrawal layer is shown to be composed of distinct regions in each of which a definite force balance prevails. The outer flow, where inertia forces are neglected, changes from a parallel uniform flow upstream to a symmetric self-similar withdrawal layer near the sink. For distances from the sink smaller than a critical distance, dependent on the flow parameters, inertia forces become of equal importance to buoyancy and viscous forces. The equations valid in this inner region are derived. Using the inner limit of the outer flow as the upstream boundary condition, these inner equations are solved approximately for the withdrawal-layer thickness by an integral method. The inner and outer variations of δ, the withdrawal-layer thickness, are combined to yield a composite solution and it is seen that the inclusion of inertia forces yields layers thicker than those obtained from a strict buoyancy-viscous force balance. In terms of the inner variables the only parameter remaining is the Schmidt number.Laboratory experiments were carried out to verify the theoretical conclusions. The observed withdrawal-layer thicknesses were shown to be closely predicted by the integral solution. Furthermore, the data could be represented in terms of the inner variables by a single curve dependent only on the Schmidt number.

scholarly journals Motor planning brings human primary somatosensory cortex into action-specific preparatory states

eLife ◽  
2022 ◽  
Vol 11 ◽  
Author(s):  
Giacomo Ariani ◽  
J Andrew Pruszynski ◽  
Jörn Diedrichsen
Keyword(s):  
Somatosensory Cortex ◽  
Motor Neurons ◽  
Primary Motor Cortex ◽  
Specific Activity ◽  
Activity Patterns ◽  
Critical Role ◽  
Motor Planning ◽  
Movement Control ◽  
Movement Planning ◽  
Primary Somatosensory Cortex

Motor planning plays a critical role in producing fast and accurate movement. Yet, the neural processes that occur in human primary motor and somatosensory cortex during planning, and how they relate to those during movement execution, remain poorly understood. Here we used 7T functional magnetic resonance imaging (fMRI) and a delayed movement paradigm to study single finger movement planning and execution. The inclusion of no-go trials and variable delays allowed us to separate what are typically overlapping planning and execution brain responses. Although our univariate results show widespread deactivation during finger planning, multivariate pattern analysis revealed finger-specific activity patterns in contralateral primary somatosensory cortex (S1), which predicted the planned finger action. Surprisingly, these activity patterns were as informative as those found in contralateral primary motor cortex (M1). Control analyses ruled out the possibility that the detected information was an artifact of subthreshold movements during the preparatory delay. Furthermore, we observed that finger-specific activity patterns during planning were highly correlated to those during execution. These findings reveal that motor planning activates the specific S1 and M1 circuits that are engaged during the execution of a finger press, while activity in both regions is overall suppressed. We propose that preparatory states in S1 may improve movement control through changes in sensory processing or via direct influence of spinal motor neurons.

scholarly journals Modulation of Initial Movement for Double Potential Targets With Specific Time Constraints

2021 ◽  
Author(s):  
Ryoji Onagawa ◽  
Kazutoshi Kudo
Keyword(s):  
Motor Planning ◽  
Time Constraint ◽  
Movement Planning ◽  
Time Constraints ◽  
Specific Time ◽  
Target Condition ◽  
Single Target ◽  
Goal Directed Behavior ◽  
Initial Movement

Abstract In goal-directed behavior, individuals are often required to plan and execute a movement with multiple competing reach targets simultaneously. The time constraint assigned to the target is an important factor that affect the initial movement planning, but the adjustments made to the starting behavior considering the time constraints specific to each target have not yet been clarified. The current study examined how humans adjusted their motor planning for double potential targets with independent time constraints under a go-before-you-know situation. The results revealed that the initial movements were modulated depending on the time constraints for potential targets. However, under tight time constraints, the performance in the double-target condition was lower than the single-target condition, which was a control condition implemented to estimate performance when one target is ignored. These results indicate that the initial movement for multiple potential targets with independent time constraints can be modified, but the planning is suboptimal.

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