Analysis of Human Control Ability for Isometric Force

A common problem in motor control concerns how to generate patterns of muscle activity when there are redundant solutions to attain a behavioral goal. Optimal feedback control is a theory that has guided many behavioral studies exploring how the motor system incorporates task redundancy. This theory predicts that kinematic errors that deviate the limb should not be corrected if one can still attain the behavioral goal. Studies in humans demonstrate that the motor system can flexibly integrate visual and proprioceptive feedback of the limb with goal redundancy within 90 ms and 70 ms, respectively. Here, we show monkeys (Macaca mulatta) demonstrate similar abilities to exploit goal redundancy. We trained four male monkeys to reach for a goal that was either a narrow square or a wide, spatially redundant rectangle. Monkeys exhibited greater trial-by-trial variability when reaching to the wide goal consistent with exploiting goal redundancy. On random trials we jumped the visual feedback of the hand and found monkeys corrected for the jump when reaching to the narrow goal and largely ignored the jump when reaching for the wide goal. In a separate set of experiments, we applied mechanical loads to the arm of the monkey and found similar corrective responses based on goal shape. Muscle activity reflecting these different corrective responses were detected for the visual and mechanical perturbations starting at ∼90 and ∼70 ms, respectively. Thus, rapid motor responses in macaques can exploit goal redundancy similar to humans, creating a paradigm to study the neural basis of goal-directed motor action and motor redundancy.SIGNIFICANCE STATEMENT Moving in the world requires selecting from an infinite set of possible motor commands. Theories predict that motor commands are selected that exploit redundancies. Corrective responses in humans to either visual or proprioceptive disturbances of the limb can rapidly exploit redundant trajectories to a goal in <100 ms after a disturbance. However, uncovering the neural correlates generating these rapid motor corrections has been hampered by the absence of an animal model. We developed a behavioral paradigm in monkeys that incorporates redundancy in the form of the shape of the goal. Critically, monkeys exhibit corrective responses and timings similar to humans performing the same task. Our paradigm provides a model for investigating the neural correlates of sophisticated rapid motor corrections.

In addition to defining impairments in social communication skills, individuals with autism spectrum disorder (ASD) also show impairments in more basic sensory and motor skills. Development of new skills involves integrating information from multiple sensory modalities. This input is then used to form internal models of action that can be accessed when both performing skilled movements, as well as understanding those actions performed by others. Learning skilled gestures is particularly reliant on integration of visual and proprioceptive input. We used a modified serial reaction time task (SRTT) to decompose proprioceptive and visual components and examine whether patterns of implicit motor skill learning differ in ASD participants as compared with healthy controls. While both groups learned the implicit motor sequence during training, healthy controls showed robust generalization whereas ASD participants demonstrated little generalization when visual input was constant. In contrast, no group differences in generalization were observed when proprioceptive input was constant, with both groups showing limited degrees of generalization. The findings suggest, when learning a motor sequence, individuals with ASD tend to rely less on visual feedback than do healthy controls. Visuomotor representations are considered to underlie imitative learning and action understanding and are thereby crucial to social skill and cognitive development. Thus, anomalous patterns of implicit motor learning, with a tendency to discount visual feedback, may be an important contributor in core social communication deficits that characterize ASD. Autism Res 2016, 9: 563-569. © 2015 International Society for Autism Research, Wiley Periodicals, Inc.

Changes in corticospinal excitability during motor imagery by physical practice of a force production task: Effect of the rate of force development during practice

Speed/accuracy trade-off is a ubiquitous phenomenon in motor behaviour, which has been ascribed to the presence of signal-dependent noise (SDN) in motor commands. Although this explanation can provide a quantitative account of many aspects of motor variability, including Fitts' law, the fact that this law is frequently violated, e.g. during the acquisition of new motor skills, remains unexplained. Here, we describe a principled approach to the influence of noise on motor behaviour, in which motor variability results from the interplay between sensory and motor execution noises in an optimal feedback-controlled system. In this framework, we first show that Fitts' law arises due to signal-dependent motor noise (SDN(m)) when sensory (proprioceptive) noise is low, e.g. under visual feedback. Then we show that the terminal variability of non-visually guided movement can be explained by the presence of signal-dependent proprioceptive noise. Finally, we show that movement accuracy can be controlled by opposite changes in signal-dependent sensory (SDN(s)) and SDN(m), a phenomenon that could be ascribed to muscular co-contraction. As the model also explains kinematics, kinetics, muscular and neural characteristics of reaching movements, it provides a unified framework to address motor variability.

Fitts’ law models the relationship between amplitude, precision, and speed of rapid movements. It is widely used to quantify performance in pointing tasks, study human-computer interaction, and generally to understand perceptual-motor information processes, including research to model performance in isometric force production tasks. Applying Fitts’ law to an isometric grip force task would allow for quantifying grasp performance in rehabilitative medicine and may aid research on prosthetic control and design. We examined whether Fitts’ law would hold when participants attempted to accurately produce their intended force output while grasping a manipulandum when presented with images of various everyday objects (we termed this the implicit task). Although our main interest was the implicit task, to benchmark it and establish validity, we examined performance against a more standard visual feedback condition via a digital force-feedback meter on a video monitor (explicit task). Next, we progressed from visual force feedback with force meter targets to the same targets without visual force feedback (operating largely on feedforward control with tactile feedback). This provided an opportunity to see if Fitts’ law would hold without vision, and allowed us to progress toward the more naturalistic implicit task (which does not include visual feedback). Finally, we changed the nature of the targets from requiring explicit force values presented as arrows on a force-feedback meter (explicit targets) to the more naturalistic and intuitive target forces implied by images of objects (implicit targets). With visual force feedback the relation between task difficulty and the time to produce the target grip force was predicted by Fitts’ law (average r2 = 0.82). Without vision, average grip force scaled accurately although force variability was insensitive to the target presented. In contrast, images of everyday objects generated more reliable grip forces without the visualized force meter. In sum, population means were well-described by Fitts’ law for explicit targets with vision (r2 = 0.96) and implicit targets (r2 = 0.89), but not as well-described for explicit targets without vision (r2 = 0.54). Implicit targets should provide a realistic see-object-squeeze-object test using Fitts’ law to quantify the relative speed-accuracy relationship of any given grasper.

Influence of aging and visual feedback on the stability of hand grip control in elderly adults.

Virtual environments are often used in pre-wearing training and assessment of prosthetic control abilities. Here, we developed a virtual prosthetic hand training platform for evaluation of closed-loop control of grasp force. Biorealistic controllers emulated a pair of antagonistic muscles that actuated the thumb and index fingers of the hand. Surface electromyographic (sEMG) signals from a pair of antagonistic residual muscles drove the biorealistic controllers. Tactile forces from fingertip sensors were conveyed to amputees through evoked tactile sensations (ETS) elicited at the projected finger map (PFM) areas of the stump. A forearm amputee subject participated in force tracking or holding tasks using the virtual hand with residual muscle EMGs, or the contralateral intact hand. Root-mean-square error (RMSE) was used as outcome measure of motor performance. Results in this subject showed that the biorealistic controller enabled the virtual hand to track and maintain grasping forces. The best performance in both tasks was achieved by the contralateral intact hand with visual feedback. The roles of visual or tactile feedback in force tracking or maintaining were also assessed with the virtual hand. For force holding task, hybrid tactile and visual feedback with biorealistic control had a better performance than single visual or tactile feedback in terms of RMSE, success rate, and force variability. While in the force pursuing task, tactile feedback did not seem to add visual feedback in following the target force. The study suggests that training may be required for a novel virtual hand user to perceive and integrate multiple modalities of feedback information, so as to optimize the closed-loop control ability.

Females of many species choose mates using multiple sensory modalities. Multimodal noise may arise, however, in dense aggregations of animals communicating via multiple sensory modalities. Some evidence suggests multimodal signals may not always improve receiver decision-making performance. When sensory systems process input from multimodal signal sources, multimodal noise may arise and potentially complicate decision-making due to the demands on cognitive integration tasks. We tested female túngara frog, Physalaemus (=Engystomops) pustulosus, responses to male mating signals in noise from multiple sensory modalities (acoustic and visual). Noise treatments were partitioned into three categories: acoustic, visual, and multimodal. We used natural calls from conspecifics and heterospecifics for acoustic noise. Robotic frogs were employed as either visual signal components (synchronous vocal sac inflation with call) or visual noise (asynchronous vocal sac inflation with call). Females expressed a preference for the typically more attractive call in the presence of unimodal noise. However, during multimodal signal and noise treatments (robofrogs employed with background noise), females failed to express a preference for the typically attractive call in the presence of conspecific chorus noise. We found that social context and temporal synchrony of multimodal signaling components are important for multimodal communication. Our results demonstrate that multimodal signals have the potential to increase the complexity of the sensory scene and reduce the efficacy of female decision making.

Social interactions rely on the interpretation of semantic and emotional information, often from multiple sensory modalities. Nonhuman primates send and receive auditory and visual communicative signals. However, the neural mechanisms underlying the association of visual and auditory information based on their common social meaning are unknown. Using heart rate estimates and functional neuroimaging, we show that in the lateral and superior temporal sulcus of the macaque monkey, neural responses are enhanced in response to species-specific vocalisations paired with a matching visual context, or when vocalisations follow, in time, visual information, but inhibited when vocalisation are incongruent with the visual context. For example, responses to affiliative vocalisations are enhanced when paired with affiliative contexts but inhibited when paired with aggressive or escape contexts. Overall, we propose that the identified neural network represents social meaning irrespective of sensory modality.

We explored processes that take place in the uncontrolled manifold (UCM) for the task of two-hand accurate force production. Based on previous studies of structured motor variability, we hypothesized that these processes would represent a superposition of a random walk within a shallow potential field and a slow drift of the potential field. Young healthy participants performed accurate force production over 60 s with visual feedback on the force magnitude, starting from different initial sharing of the total force between the hands. No feedback on force sharing was available after the first 5 s. Trajectories within the UCM demonstrated a random walk with the characteristic step time of 50–80 ms and a slow drift, primarily toward the 50:50 sharing pattern, although drifts away from 50:50 and with reversals were also observed. The Hurst exponent of the diffusion plots showed a trend toward persistent fluctuations at times under 0.2 s and anti-persistent fluctuations at times over 0.5 s. The characteristic drift times were between 5 and 15 s. The drift magnitudes were large for the initial sharing, different from 50:50, and small for the 50:50 sharing. The Hurst exponent for longer times correlated significantly with the peak-to-peak drift magnitude. We conclude that natural processes within the UCM represent a superposition of random walk and slow drift and can cause drifts in performance variables reported earlier. Spinal circuitry is a likely major contributor to the random walk. These results suggest direct application to clinical studies of impaired movement stability.

Human computer interface (HCI) is often regarded as the intersection of computer science, behavioral sciences, design and several other fields of study. In order to improve the usability of HCI, investigation of the interaction between human and computers is an important issue. In present study, we use a pointing movement experimental device with visual feedback control function which developed in our companion research to investigate the human movement characteristics. Fitts' law is a successful model of human movement that predicts the time required to rapidly move to a target. According to Fitts' law, the relationship between the movement time (MT) and the index of difficulty (ID) can be demonstrated as a linear function. Here, we designed a series of rectangle boxes as using in Fitts' study as pointing stimuli. Ten subjects were asked to do pointing movement with different visual feedback conditions. The findings of present study suggest that the pointing performance was not only depending on the size of targets but also the quantity of visual feedback information. Therefore, both visual feedback and target size need to considered for HCI design.

Three experiments were conducted to determine how variables other than movement time influence the speed of visual feedback utilization in a target-pointing task. In Experiment 1, subjects moved a stylus to a target 20 cm away with movement times of approximately 225 msec. Visual feedback was manipulated by leaving the room lights on over the whole course of the movement or extinguishing the lights upon movement initiation, while prior knowledge about feedback availability was manipulated by blocking or randomizing feedback. Subjects exhibited less radial error in the lights-on/blocked condition than in the other three conditions. In Experiment 2, when subjects were forced to use vision by a laterally displacing prism, it was found that they benefited from the presence of visual feedback regardless of feedback uncertainty even when moving very rapidly (e.g. less than 190 msec). In Experiment 3, subjects pointed with and without a prism over a wide variety of movement times. Subjects benefited from vision much earlier in the prism condition. Subjects seem able to use vision rapidly to modify aiming movements but may do so only when the visual information is predictably available and/or yields an error large enough to detect early enough to correct.

The central role of the temporo-parietal junction and the superior longitudinal fasciculus in supporting multi-item competition: Evidence from lesion-symptom mapping of extinction

Neural Correlates of State Estimation in Visually Guided Movements: an Event-Related FMRI Study

This paper addresses a fundamental question of how motor commands specify target torque levels. Human subjects produced fast and accurate changes in torque with the isometric elbow joint. Visual stimuli were used to indicate target torque levels as well as to cue subjects to initiate their responses. During rapid changes in torque from one steady-state level to another, target torque was achieved through a sequence of approximations. During the first 200-250 msec of responses produced in the presence of visual feedback, 3 distinct control mechanisms were recruited to guide torque to the target level. The timing and accuracy of each control mechanism were evaluated. The first control mechanism was triggered by the visual stimulus and produced the initial rise in torque. Target torque predictability was found to strongly influence the accuracy of this control mechanism. The second control mechanism produced a corrective adjustment in torque within roughly the first 100 msec of responses. This mechanism incorporated target torque information provided by the stimulus into the response. The third control mechanism began 200-250 msec after response onset and produced corrective adjustments based on visual feedback of torque errors. The stability of the visual feedback mechanism was evaluated because of a long loop delay. Two strategies were used to control stability: low gain and information transfer between the visual feedback mechanism and the preceding (second) control mechanism.