scholarly journals Online modification of goal-directed control in human reaching movements

2020 ◽  
Author(s):  
Antoine De Comite ◽  
Frédéric Crevecoeur ◽  
Philippe Lefèvre
Keyword(s):  
Control Strategies ◽  
Control Policy ◽  
Visual Display ◽  
Movement Planning ◽  
Reaching Movements ◽  
Planning Stage ◽  
Reaching Movement ◽  
Flexible Control ◽  
Task Goal ◽  
Sudden Appearance

AbstractHumans are able to perform very sophisticated reaching movements in a myriad of contexts based on flexible control strategies influenced by the task goal and environmental constraints such as obstacles. However, it remains unknown whether these control strategies can be adjusted online. The objective of this study was to determine whether the factors which determine control strategies during planning also modify the execution of an ongoing movement following sudden changes in task demand. More precisely, we investigated whether, and at which latency, feedback responses to perturbation loads followed the change in the structure of the goal target or environment. We changed the target width (square or rectangle) to alter the task redundancy, or the presence of obstacles to induce different constraints on the reach path, and assessed based on surface recordings when the change in visual display altered the feedback response to mechanical perturbations. Task-related EMG responses were detected within 150 ms of a change in target shape. Considering visuomotor delays of ∼ 100 ms, these results suggest that it takes 50 ms to change control policy within a trial. An additional 30 ms delay was observed when the change in context involved sudden appearance or disappearance of obstacles. Overall, our results demonstrate that the control policy within a reaching movement is not static: contextual factors which influence movement planning also influence movement execution at surprisingly short latencies. Moreover, the additional 30 ms associated with obstacles suggest that these two types of changes may be mediated via distinct processes.New & NoteworthyThe present work demonstrates that the control strategies used to perform reaching movements are adjusted online when the structure of the target or the presence of obstacles are altered during movements. Thus, the properties of goal-directed reaching control are not simply selected during the planning stage of a movement prior to execution. Rather, they are dynamically and rapidly adjusted online, within ∼150ms, according to changes in environment.

scholarly journals Online modification of goal-directed control in human reaching movements

2021 ◽  
Author(s):  
Antoine De Comite ◽  
Frédéric Crevecoeur ◽  
Philippe Lefèvre
Keyword(s):  
Control Strategies ◽  
Control Policy ◽  
Visual Display ◽  
Surface Emg ◽  
Movement Planning ◽  
Reaching Movements ◽  
Reaching Movement ◽  
Flexible Control ◽  
Task Goal ◽  
Sudden Appearance

Humans are able to perform very sophisticated reaching movements in a myriad of contexts based on flexible control strategies influenced by the task goal and environmental constraints such as obstacles. However, it remains unknown whether these control strategies can be adjusted online. The objective of this study was to determine whether the factors which determine control strategies during planning also modify the execution of an ongoing movement following sudden changes in task demand. More precisely, we investigated whether, and at which latency, feedback responses to perturbation loads followed the change in the structure of the goal target or environment. We changed the target width (square or rectangle) to alter the task redundancy, or the presence of obstacles to induce different constraints on the reach path, and assessed based on surface EMG recordings when the change in visual display altered the feedback response to mechanical perturbations. Task-related EMG responses were detected within 150 ms of a change in target shape. Considering visuomotor delays of ~ 100 ms, these results suggest that it takes 50 ms to change control policy within a trial. An additional 30 ms delay was observed when the change in context involved sudden appearance or disappearance of obstacles. Overall, our results demonstrate that the control policy within a reaching movement is not static: contextual factors which influence movement planning also influence movement execution at surprisingly short latencies. Moreover, the additional 30 ms associated with obstacles suggest that these two types of changes may be mediated via distinct processes.

scholarly journals Reward-dependent selection of feedback gains impacts rapid motor decisions

2021 ◽  
Author(s):  
Antoine De Comite ◽  
Frederic Crevecoeur ◽  
Philippe Lefevre
Keyword(s):  
Muscle Activity ◽  
Control Strategies ◽  
Control Policy ◽  
Movement Planning ◽  
Baseline Activity ◽  
Planning Strategies ◽  
External Loads ◽  
Direction Opposite ◽  
Selection Of ◽  
Background Load

Expected reward is known to affect planning strategies through modulation of movement vigor. Strikingly, although current theories suggest that movement planning consists in selecting a goal-directed control policy, the influence of reward on feedback control strategies remains unknown. Here we investigated this question in three human reaching experiments. First, we varied the explicit reward associated with the goal target and found an overall increase in movement vigor for higher reward targets, highlighted by larger velocities, feedback responses to external loads, and background muscle activity. Then, assuming that larger feedback gains were used to reject perturbations, we sought to investigate whether this effect hindered online decisions to switch to a new target in the presence of multiple successful goals. We indeed observed idiosyncratic switching strategies dependent on both target rewards and movement vigor, such that the more vigorous movements were less likely to switch to a new goal following perturbations. To gain further insight into a causal influence of movement vigor on rapid motor decisions, we demonstrated that biasing the baseline activity and reflex gains by means of a background load evoked a larger proportion of target switches in the direction opposite to the background load associated with lower muscle activity. Our results highlight the competition between movement vigor and flexibility to switch target during movement.

Whole-body adaptation to novel dynamics does not transfer between effectors

2021 ◽  
Author(s):  
Alison Pienciak-Siewert ◽  
Alaa A Ahmed
Keyword(s):  
Postural Control ◽  
Arm Movement ◽  
Movement Planning ◽  
Reaching Movements ◽  
Whole Body ◽  
Postural Control System ◽  
Movement Dynamics ◽  
Gradual Introduction ◽  
Postural Movement ◽  
The Brain

How does the brain coordinate concurrent adaptation of arm movements and standing posture? From previous studies, the postural control system can use information about previously adapted arm movement dynamics to plan appropriate postural control; however, it is unclear whether postural control can be adapted and controlled independently of arm control. The present study addresses that question. Subjects practiced planar reaching movements while standing and grasping the handle of a robotic arm, which generated a force field to create novel perturbations. Subjects were divided into two groups, for which perturbations were introduced in either an abrupt or gradual manner. All subjects adapted to the perturbations while reaching with their dominant (right) arm, then switched to reaching with their non-dominant (left) arm. Previous studies of seated reaching movements showed that abrupt perturbation introduction led to transfer of learning between arms, but gradual introduction did not. Interestingly, in this study neither group showed evidence of transferring adapted control of arm or posture between arms. These results suggest primarily that adapted postural control cannot be transferred independently of arm control in this task paradigm. In other words, whole-body postural movement planning related to a concurrent arm task is dependent on information about arm dynamics. Finally, we found that subjects were able to adapt to the gradual perturbation while experiencing very small errors, suggesting that both error size and consistency play a role in driving motor adaptation.

scholarly journals Oral Tobaccco and Mortality in India

2016 ◽  
Vol 7 ◽  
pp. IJCM.S25889 ◽  
Author(s):  
Priya Mohan ◽  
Harry A. Lando
Keyword(s):  
Tobacco Control ◽  
Health Care Professionals ◽  
Large Scale ◽  
Control Strategies ◽  
Control Policy ◽  
Control Measures ◽  
Educational Institutions ◽  
Regional Studies ◽  
Gender And Education ◽  
Indian Context

This comprehensive review includes large-scale pan-India surveys and regional studies. Every aspect of smokeless tobacco, including variations in social, economic, demographic, gender, and education stratifiers, is presented. This evidence-based presentation thereby provides insight not only to assess the burden but can serve as a base, leading to the development and encouragement of research in closing the existing gaps in knowledge. It can also provide a track to formulate tobacco control strategies as well as to reinforce and potentially guide tobacco control policy aimed at addressing the tailored needs in the Indian context. The recommendations expand the tobacco control spectrum and are the first of their kind in the literature to focus on cessation programs as a paramedical subject to draw the attention of not only policymakers but also to integrate medical and dental educational institutions, health care professionals, and tobacco users to synergistically develop successful tobacco control measures.

Combining BIM, GIS, and IoT to Foster Energy Management and Simulation in Smart Cities

2021 ◽  
pp. 425-447
Author(s):  
Edoardo Patti ◽  
Francesco G. Brundu ◽  
Andrea Bellagarda ◽  
Lorenzo Bottaccioli ◽  
Niccolò Rapetti ◽  
...  
Keyword(s):  
Energy Management ◽  
Smart Cities ◽  
Control Strategies ◽  
Control Policy ◽  
Information Model ◽  
Environmental Data ◽  
Software Infrastructure ◽  
Heterogeneous Information ◽  
Building Information ◽  
Iot Devices

This chapter presents a novel distributed software infrastructure to enable energy management and simulation of novel control strategies in smart cities. In this context, the following heterogeneous information, describing the different entities in a city, needs to be taken into account to form a unified district information model: internet-of-things (IoT) devices, building information model, system information model, and georeferenced information system. IoT devices are crucial to monitor in (near-) real-time both building energy trends and environmental data. Thus, the proposed solution fulfills the integration and interoperability of such data sources providing also a correlation among them. Such correlation is the key feature to unlock management and simulation of novel energy policies aimed at optimizing the energy usage accounting also for its impact on building comfort. The platform has been deployed in a real-world district and a novel control policy for the heating distribution network has been developed and tested. Finally, experimental results are presented and discussed.

Behavioral Reference Frames for Planning Human Reaching Movements

2006 ◽  
Vol 96 (1) ◽  
pp. 352-362 ◽  
Author(s):  
Sabine M. Beurze ◽  
Stan Van Pelt ◽  
W. Pieter Medendorp
Keyword(s):  
Reference Frame ◽  
Visual Information ◽  
Reference Frames ◽  
Target Position ◽  
Movement Planning ◽  
Reaching Movements ◽  
Hand Position ◽  
Pointing Error ◽  
Movement Vector ◽  
Common Reference

At some stage in the process of a sensorimotor transformation for a reaching movement, information about the current position of the hand and information about the location of the target must be encoded in the same frame of reference to compute the hand-to-target difference vector. Two main hypotheses have been proposed regarding this reference frame: an eye-centered and a body-centered frame. Here we evaluated these hypotheses using the pointing errors that subjects made when planning and executing arm movements to memorized targets starting from various initial hand positions while keeping gaze fixed in various directions. One group of subjects ( n = 10) was tested without visual information about hand position during movement planning (unseen-hand condition); another group ( n = 8) was tested with hand and target position simultaneously visible before movement onset (seen-hand condition). We found that both initial hand position and gaze fixation direction had a significant effect on the magnitude and direction of the pointing error. Errors were significantly smaller in the seen-hand condition. For both conditions, though, a reference frame analysis showed that the errors arose at an eye- or hand-centered stage or both, but not at a body-centered stage. As a common reference frame is required to specify a movement vector, these results suggest that an eye-centered mechanism is involved in integrating target and hand position in programming reaching movements. We discuss how simple gain elements modulating the eye-centered target and hand-position signals can account for these results.

Opposed optimal strategies of weighting somatosensory inputs for planning reaching movements toward visual and proprioceptive targets

2014 ◽  
Vol 112 (9) ◽  
pp. 2290-2301 ◽  
Author(s):  
Jean Blouin ◽  
Anahid H. Saradjian ◽  
Nicolas Lebar ◽  
Alain Guillaume ◽  
Laurence Mouchnino
Keyword(s):  
Visual Feedback ◽  
Sensory Modality ◽  
Optimal Strategies ◽  
Neural Correlates ◽  
Movement Planning ◽  
Reaching Movements ◽  
Behavioral Studies ◽  
Somatosensory Input ◽  
Visual Targets ◽  
The Brain

Behavioral studies have suggested that the brain uses a visual estimate of the hand to plan reaching movements toward visual targets and somatosensory inputs in the case of somatosensory targets. However, neural correlates for distinct coding of the hand according to the sensory modality of the target have not yet been identified. Here we tested the twofold hypothesis that the somatosensory input from the reaching hand is facilitated and inhibited, respectively, when planning movements toward somatosensory (unseen fingers) or visual targets. The weight of the somatosensory inputs was assessed by measuring the amplitude of the somatosensory evoked potential (SEP) resulting from vibration of the reaching finger during movement planning. The target sensory modality had no significant effect on SEP amplitude. However, Spearman's analyses showed significant correlations between the SEPs and reaching errors. When planning movements toward proprioceptive targets without visual feedback of the reaching hand, participants showing the greater SEPs were those who produced the smaller directional errors. Inversely, participants showing the smaller SEPs when planning movements toward visual targets with visual feedback of the reaching hand were those who produced the smaller directional errors. No significant correlation was found between the SEPs and radial or amplitude errors. Our results indicate that the sensory strategy for planning movements is highly flexible among individuals and also for a given sensory context. Most importantly, they provide neural bases for the suggestion that optimization of movement planning requires the target and the reaching hand to both be represented in the same sensory modality.

Hand-held tools with complex kinematics are efficiently incorporated into movement planning and online control

2012 ◽  
Vol 108 (7) ◽  
pp. 1954-1964 ◽  
Author(s):  
Lee A. Baugh ◽  
Erica Hoe ◽  
J. Randall Flanagan
Keyword(s):  
Online Control ◽  
Movement Planning ◽  
Control Mechanisms ◽  
Movement Initiation ◽  
Reaching Movement ◽  
Hand Motion ◽  
Reversal Condition ◽  
End Point ◽  
Point Motion ◽  
Time Required

Certain hand-held tools alter the mapping between hand motion and motion of the tool end point that must be controlled in order to perform a task. For example, when using a pool cue, the motion of the cue tip is reversed relative to the hand. Previous studies have shown that the time required to initiate a reaching movement (Fernandez-Ruiz J, Wong W, Armstrong IT, Flanagan JR. Behav Brain Res 219: 8–14, 2011), or correct an ongoing reaching movement (Gritsenko V, Kalaska JF. J Neurophysiol 104: 3084–3104, 2010), is prolonged when the mapping between hand motion and motion of a cursor controlled by the hand is reversed. Here we show that these time costs can be significantly reduced when the reversal is instantiated by a virtual hand-held tool. Participants grasped the near end of a virtual tool, consisting of a rod connecting two circles, and moved the end point to displayed targets. In the reversal condition, the rod translated through, and rotated about, a pivot point such that there was a left-right reversal between hand and end point motion. In the nonreversal control, the tool translated with the hand. As expected, when only the two circles were presented, movement initiation and correction times were much longer in the reversal condition. However, when full vision of the tool was provided, the reaction time cost was almost eliminated. These results indicate that tools with complex kinematics can be efficiently incorporated into sensorimotor control mechanisms used in movement planning and online control.

scholarly journals The duration of reaching movement is longer than predicted by minimum variance

2016 ◽  
Vol 116 (5) ◽  
pp. 2342-2345 ◽  
Author(s):  
Chunji Wang ◽  
Yupeng Xiao ◽  
Etienne Burdet ◽  
James Gordon ◽  
Nicolas Schweighofer
Keyword(s):  
Minimum Variance ◽  
Reaching Movements ◽  
Movement Duration ◽  
Slow Movement ◽  
Reaching Movement ◽  
End Point ◽  
Parsimonious Explanation ◽  
Arm Reaching ◽  
The Central Nervous System ◽  
Duration Condition

Whether the central nervous system minimizes variability or effort in planning arm movements can be tested by measuring the preferred movement duration and end-point variability. Here we conducted an experiment in which subjects performed arm reaching movements without visual feedback in fast-, medium-, slow-, and preferred-duration conditions. Results show that 1) total end-point variance was smallest in the medium-duration condition and 2) subjects preferred to carry out movements that were slower than this medium-duration condition. A parsimonious explanation for the overall pattern of end-point errors across fast, medium, preferred, and slow movement durations is that movements are planned to minimize effort as well as end-point error due to both signal-dependent and constant noise.

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