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We examined the extent to which intentionally underperforming a goal-directed reaching task impacts how memories of recent performance contribute to sensorimotor adaptation. Healthy human subjects performed computerized cognition testing and an assessment of sensorimotor adaptation, wherein they grasped the handle of a horizontal planar robot while making goal-directed out-and-back reaching movements. The robot exerted forces that resisted hand motion with a spring-like load that changed unpredictably between movements. The robotic test assessed how implicit and explicit memories of sensorimotor performance contribute to the compensation for the unpredictable changes in the hand-held load. After each movement, subjects were to recall and report how far the hand moved on the previous trial (peak extent of the out-and-back movement). Subjects performed the tests under two counter-balanced conditions: one where they performed with their best effort, and one where they intentionally sabotaged (i.e., suppressed) kinematic performance. Results from the computerized cognition tests confirmed that subjects understood and complied with task instructions. When suppressing performance during the robotic assessment, subjects demonstrated marked changes in reach precision, time to capture the target, and reaction time. We fit a set of limited memory models to the data to identify how subjects used implicit and explicit memories of recent performance to compensate for the changing loads. In both sessions, subjects used implicit, but not explicit, memories from the most recent trial to adapt reaches to unpredictable spring-like loads. Subjects did not "give up" on large errors, nor did they discount small errors deemed "good enough". Although subjects clearly suppressed kinematic performance (response timing, movement variability, and self-reporting of reach error), the relative contributions of sensorimotor memories to trial-by-trial variations in task performance did not differ significantly between the two testing conditions. We conclude that intentional performance suppression had minimal impact on how implicit sensorimotor memories contribute to adaptation of unpredictable mechanical loads applied to the hand. [ABSTRACT FROM AUTHOR]

Prior studies have shown that the accuracy and efficiency of reaching can be improved using novel sensory interfaces to apply task-specific vibrotactile feedback (VTF) during movement. However, those studies have typically evaluated performance after less than 1 h of training using VTF. Here, we tested the effects of extended training using a specific form of vibrotactile cues—supplemental kinesthetic VTF—on the accuracy and temporal efficiency of goal-directed reaching. Healthy young adults performed planar reaching with VTF encoding of the moving hand's instantaneous position, applied to the non-moving arm. We compared target capture errors and movement times before, during, and after approximately 10 h (20 sessions) of training on the VTF-guided reaching task. Initial performance of VTF-guided reaching showed that people were able to use supplemental VTF to improve reaching accuracy. Performance improvements were retained from one training session to the next. After 20 sessions of training, the accuracy and temporal efficiency of VTF-guided reaching were equivalent to or better than reaches performed with only proprioception. However, hand paths during VTF-guided reaching exhibited a persistent strategy where movements were decomposed into discrete sub-movements along the cardinal axes of the VTF display. We also used a dual-task condition to assess the extent to which performance gains in VTF-guided reaching resist dual-task interference. Dual-tasking capability improved over the 20 sessions, such that the primary VTF-guided reaching and a secondary choice reaction time task were performed with increasing concurrency. Thus, VTF-guided reaching is a learnable skill in young adults, who can achieve levels of accuracy and temporal efficiency equaling or exceeding those observed during movements guided only by proprioception. Future studies are warranted to explore learnability in older adults and patients with proprioceptive deficits, who might benefit from using wearable sensory augmentation technologies to enhance control of arm movements. [ABSTRACT FROM AUTHOR]

We examined a key aspect of sensorimotor skill: the capability to correct performance errors that arise mid-movement. Participants grasped the handle of a robot that imposed a nominal viscous resistance to hand movement. They watched a target move pseudo-randomly just above the horizontal plane of hand motion and initiated quick interception movements when cued. On some trials, the robot's viscosity or the target's speed changed without warning coincident with the GO cue. We fit a sum-of-Gaussians model to mechanical power measured at the handle to determine the number, magnitude, and relative timing of submovements occurring in each interception attempt. When a single submovement successfully intercepted the target, capture times averaged 410 ms. Sometimes, two or more submovements were required. Initial error corrections typically occurred before feedback could indicate the target had been captured or missed. Error corrections occurred sooner after movement onset in response to mechanical viscosity increases (at 154 ms) than to unprovoked errors on control trials (215 ms). Corrections occurred later (272 ms) in response to viscosity decreases. The latency of corrections for target speed changes did not differ from those in control trials. Remarkably, these early error corrections accommodated the altered testing conditions; speed/viscosity increases elicited more vigorous corrections than in control trials with unprovoked errors; speed/viscosity decreases elicited less vigorous corrections. These results suggest that the brain monitors and predicts the outcome of evolving movements, rapidly infers causes of mid-movement errors, and plans and executes corrections—all within 300 ms of movement onset. [ABSTRACT FROM AUTHOR]

We examined how implicit and explicit memories contribute to sensorimotor adaptation of movement extent during goal-directed reaching. Twenty subjects grasped the handle of a horizontal planar robot that rendered spring-like resistance to movement. Subjects made rapid "out-and-back" reaches to capture a remembered visual target at the point of maximal reach extent. The robot's resistance changed unpredictably between reaches, inducing target capture errors that subjects attempted to correct from one trial to the next. Each subject performed over 400 goal-directed reaching trials. Some trials were performed without concurrent visual cursor feedback of hand motion. Some trials required self-assessment of performance between trials, whereby subjects reported peak reach extent on the most recent trial. This was done by either moving a cursor on a horizontal display (visual self-assessment), or by moving the robot's handle back to the recalled location (proprioceptive self-assessment). Control condition trials performed either without or with concurrent visual cursor feedback of hand motion did not require self-assessments. We used step-wise linear regression analyses to quantify the extent to which prior reach errors and explicit memories of reach extent contribute to subsequent reach performance. Consistent with prior reports, providing concurrent visual feedback of hand motion increased reach accuracy and reduced the impact of past performance errors on future performance, relative to the corresponding no-vision control condition. By contrast, we found no impact of interposed self-assessment on subsequent reach performance or on how prior target capture errors influence subsequent reach performance. Self-assessments were biased toward the remembered target location and they spanned a compressed range of values relative to actual reach extents, demonstrating that declarative memories of reach performance systematically differed from actual performances. We found that multilinear regression could best account for observed data variability when the regression model included only implicit memories of prior reach performance; including explicit memories (self-assessments) in the model did not improve its predictive accuracy. We conclude therefore that explicit memories of prior reach performance do not contribute to implicit sensorimotor adaptation of movement extent during goal-directed reaching under conditions of environmental uncertainty. [ABSTRACT FROM AUTHOR]

Body–machine interfaces (BMIs) provide a non-invasive way to control devices. Vibrotactile stimulation has been used by BMIs to provide performance feedback to the user, thereby reducing visual demands. To advance the goal of developing a compact, multivariate vibrotactile display for BMIs, we performed two psychophysical experiments to determine the acuity of vibrotactile perception across the arm. The first experiment assessed vibration intensity discrimination of sequentially presented stimuli within four dermatomes of the arm (C5, C7, C8, and T1) and on the ulnar head. The second experiment compared vibration intensity discrimination when pairs of vibrotactile stimuli were presented simultaneously vs. sequentially within and across dermatomes. The first experiment found a small but statistically significant difference between dermatomes C7 and T1, but discrimination thresholds at the other three locations did not differ. Thus, while all tested dermatomes of the arm and hand could serve as viable sites of vibrotactile stimulation for a practical BMI, ideal implementations should account for small differences in perceptual acuity across dermatomes. The second experiment found that sequential delivery of vibrotactile stimuli resulted in better intensity discrimination than simultaneous delivery, independent of whether the pairs were located within the same dermatome or across dermatomes. Taken together, our results suggest that the arm may be a viable site to transfer multivariate information via vibrotactile feedback for body–machine interfaces. However, user training may be needed to overcome the perceptual disadvantage of simultaneous vs. sequentially presented stimuli. [ABSTRACT FROM AUTHOR]

The present study examined the effects of a visual-based biofeedback training on improving balance challenges in autism spectrum disorder (ASD). Twenty-nine youth with ASD (7-17 years) completed an intensive 6-week biofeedback-based videogame balance training. Participants exhibited training-related balance improvements that significantly accounted for postural-sway improvements outside of training. Participants perceived the training as beneficial and enjoyable. Significant moderators of training included milder stereotyped and ritualistic behaviors and better starting balance. Neither IQ nor BMI moderated training. These results suggest that biofeedback-based balance training is associated with balance improvements in youth with ASD, most robustly in those with less severe repetitive behaviors and better starting balance. The training was perceived as motivating, further suggesting its efficacy and likelihood of use. [ABSTRACT FROM AUTHOR]

The smooth pursuit eye movement system appears to be importantly engaged during the planning and execution of interceptive hand movements. The present study sought to probe the interaction between eye and hand control systems by examining their responses during an interception task that included target speed perturbations. On 2/3 of trials, the target increased or decreased speed at various times, ranging from about 300 ms before to 150 ms after the onset of a finger movement directed to intercept the target and was triggered by a GO signal. Additionally, the same 2D sum-of-sines target trajectories were followed with the eyes without interception. The smooth pursuit system responded more quickly if the target speed perturbation occurred earlier during the reaction time (i.e., near the time of the GO signal). Similarly, the finger movement began more quickly if target speed was increased earlier during the reaction time. For early perturbation conditions, the initial direction of the finger movement matched the predicted target intercept using the new target speed. For perturbations occurring after finger movement, onset initial direction of finger movement did not match target interception such that the finger path began to curve toward the perturbed target after about 150-200 ms. The results support the idea of an active process of visual target path extrapolation simultaneously used to guide both the eye and hand. [ABSTRACT FROM AUTHOR]

When a tracked target is occluded transiently, extraretinal signals are known to maintain smooth pursuit, albeit with a reduced gain. The extent to which extraretinal signals incorporate predictions of time-varying behavior, such as gradual changes in target direction, is not known. Three experiments were conducted to examine this question. In the experiments, subjects tracked a target that initially moved along a straight path, then (briefly) followed the arc of a circle, before it disappeared behind a visible occlusion. In the first experiment, the target did not emerge from the occlusion and subjects were asked to point to the location where they thought the target would have emerged. Gaze and pointing behaviors demonstrated that most of the subjects predicted that the target would follow a linear path through the occlusion. The direction of this extrapolated path was the same as the final visible target direction. In the second set of experiments, the target did emerge after following a curvilinear path through the occlusion, and subjects were asked to track the target with their eyes. Gaze behaviors indicated that, in this experimental condition, the subjects predicted curvilinear target motion while the target was occluded. Saccades were directed to the unseen curvilinear path and pursuit continued to follow this same path at a reduced speed in the occlusion. Importantly, the direction of smooth pursuit continued to change throughout the occlusion. Smooth pursuit angular velocity was maintained for approximately 200 ms following target disappearance. The results of the experiments indicate that extraretinal signals indeed incorporate cognitive expectations about the time-varying behavior of target motion. [ABSTRACT FROM AUTHOR]

Smooth pursuit tracking of targets moving linearly (in one dimension) is well characterized by a model where retinal image motion drives eye acceleration. However, previous findings suggest that this model cannot be simply extended to two-dimensional (2D) tracking. To examine 2D pursuit, in the present study, human subjects tracked a target that moved linearly and then followed the arc of a circle. The subjects’ gaze angular velocity accurately matched target angular velocity, but the direction of smooth pursuit always lagged behind the current target direction. Pursuit speed slowly declined after the onset of the curve (for about 500 ms), even though the target speed was constant. In a second experiment, brief perturbations were presented immediately prior to the beginning of the change in direction. The subjects’ responses to these perturbations consisted of two components: (1) a response specific to the parameters of the perturbation and (2) a nonspecific response that always consisted of a transient decrease in gaze velocity. With the exception of this nonspecific response, pursuit behavior in response to the gradual changes in direction and to the perturbations could be explained by using retinal slip (image velocity) as the input signal. The retinal slip was parallel and perpendicular to the instantaneous direction of pursuit ultimately resulted in changes in gaze velocity (via gaze acceleration). Perhaps due to the subjects’ expectations that the target will curve, the sensitivity to the image motion in the direction of pursuit was not as strong as the sensitivity to image motion perpendicular to gaze velocity. [ABSTRACT FROM AUTHOR]

Arm and hand movements are generally controlled using a combination of sensory-based and memory-based guidance mechanisms. This study examined similarities and differences in visually-guided and memory-guided arm movements, and sought to determine as to what extent certain control principles apply to each type of movement. In particular, the 2/3 power law is a principle that appears to govern the formation of complex, curved hand trajectories; it specifies that the tangential velocity should be proportional to the radius of curvature raised to an exponent of 1/3. A virtual reality system was used to project complex target paths in three-dimensional (3D) space. Human subjects first tracked (with the tip of a handheld pen) a single target moving along an unseen path. The entire target path then became visible and the subject traced the shape. Finally, the target shape disappeared and the subject was to draw it, in the same 3D space, from memory. Most aspects of the movements (speed, path size, shape and arm postures) were very similar across the three conditions. However, subjects adhered to the 2/3 power law most closely in the tracing condition, when the entire target path was visible. Also, only within the tracing condition, there were significant differences in the value of the exponent depending on the size and the spatial orientation of the trajectory. In the tracking and drawing conditions, the exponent was greater than 1/3, indicating that subjects spent more time in areas of tight curvature. This may represent a strategy for learning and remembering the complex shape. [ABSTRACT FROM AUTHOR]

Little is known about the manual tracking of targets that move in three dimensions. In the present study, human subjects followed, with the tip of a hand-held pen, a virtual target moving four times (period 5 s) around a novel, unseen path. Two basic types of target paths were used: a peanut-shaped Cassini ellipse and a quasi-spherical shape where four connected semicircles lay in orthogonal planes. The quasi-spherical shape was presented in three different sizes, and the Cassini shape was varied in spatial orientation and by folding it along one of the three bend axes. During the first cycle of Cassini shapes, the hand lagged behind the target by about 150 ms on average, which decreased to 100 ms during the last three cycles. Tracking performance gradually improved during the first 3 s of the first cycle and then stabilized. Tracking was especially good during the smooth, planar sections of the shapes, and time lag was significantly shorter when the tracking of a low-frequency component was compared to performance at a higher frequency (−88 ms at 0.2 Hz vs. −101 ms at 0.6 Hz). Even after the appropriate adjustment of the virtual target path to a virtual shape tracing condition, tracking in depth was poor compared to tracking in the frontal plane, resulting in a flattening of the hand path. In contrast to previous studies where target trajectories were linear or sinusoidal, these complex trajectories may have involved estimation of the overall shape, as well as prediction of target velocity. [ABSTRACT FROM AUTHOR]

The directional control of smooth pursuit eye movements was studied by presenting human subjects with targets that moved in a straight line at a constant speed and then changed direction abruptly and unpredictably. To minimize the probability of saccadic responses in the interval following the target’s change in direction, target position was offset so as to eliminate position error after the reaction time. Smooth pursuit speed declined at a latency of 90 ms, whereas the direction of smooth pursuit began to change later (130 ms). The amplitude of the offset in target position did not affect the subsequent smooth pursuit response. In other experiments, the target’s speed or acceleration was changed abruptly at the time of the change in direction. Step changes in speed elicited short-latency responses in smooth pursuit tracking but step changes in acceleration did not. In all instances, the earliest component of the response did not depend on the parameters of the stimulus. The data were fit with a model in which smooth pursuit resulted from the vector addition of two components, one representing a response to the arrest of the initial target motion and the other the response to the onset of target motion in the new direction. This model gave an excellent fit but further analysis revealed nonlinear interactions between the two vector components. These interactions represented directional anisotropies both in terms of the initial tracking direction (which was either vertical or 45°) and in terms of the cardinal directions (vertical and horizontal). [ABSTRACT FROM AUTHOR]

There are time delays in visuomanual and oculomotor pathways, and some of these time delays may be due to the finite time required to process visual motion signals and to extract accurate information about the speed and direction of the motion. The present experiments were designed to ascertain the time required to obtain a reliable estimate of the direction of target motion. Subjects were asked to indicate the final direction of a moving target, which abruptly changed direction and shortly thereafter disappeared, by pointing to its expected emergence at the boundary of an occlusion. Subjects made small but consistent errors that overestimated the target’s change in direction. These errors depended little on the amount of time the target was visible (ranging from 50 to 400 ms) after it changed direction. Pointing direction was strongly correlated with gaze, which was dominated by a saccade initiated shortly after the target changed direction. The pointing errors were explained by the fact that the saccade always intercepted the (occluded) target, but then continued in the same direction toward the boundary of the occlusion. The analysis reveals that target direction was estimated accurately even at the shortest viewing time. [ABSTRACT FROM AUTHOR]