Dissociating the Influence of Limb Posture and Visual Feedback Shifts on the Adaptation to Novel Movement Dynamics.

Accurate movements of the upper limb require the integration of various forms of sensory feedback (e.g., visual and postural information). The influence of these different sensory modalities on reaching movements has been largely studied by assessing endpoint errors after selectively perturbing sensory estimates of hand location. These studies have demonstrated that both vision and proprioception make key contributions in determining the reach endpoint. However, their influence on motor output throughout movement remains unclear. Here we used separate perturbations of posture and visual information to dissociate their effects on reaching dynamics and temporal force profiles during point-to-point reaching movements. We tested human subjects (N = 32) and found that vision and posture modulate select aspects of reaching dynamics. Specifically, altering arm posture influences the relationship between temporal force patterns and the motion-state variables of hand position and acceleration, whereas dissociating visual feedback influences the relationship between force patterns and the motion-state variables of velocity and acceleration. Next, we examined the extent these baseline motion-state relationships influence motor adaptation based on perturbations of movement dynamics. We trained subjects using a velocity-dependent force-field to probe the extent arm posture-dependent influences persisted after exposure to a motion-state dependent perturbation. Changes in the temporal force profiles due to variations in arm posture were not reduced by adaptation to novel movement dynamics, but persisted throughout learning. These results suggest that vision and posture differentially influence the internal estimation of limb state throughout movement and play distinct roles in forming the response to external perturbations during movement.

Understanding the capacity of children with congenital unilateral below-elbow deficiency to actuate their affected muscles.

In recent years, commercially available dexterous upper limb prostheses for children have begun to emerge. These devices derive control signals from surface electromyography (measure of affected muscle electrical activity, sEMG) to drive a variety of grasping motions. However, the ability for children with congenital upper limb deficiency to actuate their affected muscles to achieve naturalistic prosthetic control is not well understood, as compared to adults or children with acquired hand loss. To address this gap, we collected sEMG data from 9 congenital one-handed participants ages 8-20 years as they envisioned and attempted to perform 10 different movements with their missing hands. Seven sEMG electrodes were adhered circumferentially around the participant's affected and unaffected limbs and participants mirrored the attempted missing hand motions with their intact side. To analyze the collected sEMG data, we used time and frequency domain analyses. We found that for the majority of participants, attempted hand movements produced detectable and consistent muscle activity, and the capacity to achieve this was not dissimilar across the affected and unaffected sides. These data suggest that children with congenital hand absence retain a degree of control over their affected muscles, which has important implications for translating and refining advanced prosthetic control technologies for children.

Multimodal processing of noisy cues in bumblebees.

Multimodal cues can improve behavioral responses by enhancing the detection and localization of sensory cues and reducing response times. Across species, studies have shown that multisensory integration of visual and olfactory cues can improve response accuracy. However, in real-world settings, sensory cues are often noisy; visual and olfactory cues can be deteriorated, masked, or mixed, making the target cue less clear to the receiver. In this study, we use an associative learning paradigm (Free Moving Proboscis Extension Reflex, FMPER) to show that having multimodal cues may improve the accuracy of bees' responses to noisy cues. Adding a noisy visual cue improves the accuracy of response to a noisy olfactory cue, despite neither the clear nor noisy visual cue being sufficient when paired with a novel olfactory cue. This may provide insight into the neural mechanisms underlying multimodal processing and the effects of environmental change on pollination services.

Motion state-dependent motor learning based on explicit visual feedback has limited spatiotemporal properties compared with adaptation to physical perturbations.

We recently showed that subjects can learn motion state-dependent changes to motor output (temporal force patterns) based on explicit visual feedback of the equivalent force field (i.e., without the physical perturbation). Here, we examined the spatiotemporal properties of this learning compared with learning based on physical perturbations. There were two human subject groups and two experimental paradigms. One group (n = 40) experienced physical perturbations (i.e., a velocity-dependent force field, vFF), whereas the second (n = 40) was given explicit visual feedback (EVF) of the force-velocity relationship. In the latter, subjects moved in force channels and we provided visual feedback of the lateral force exerted during the movement, as well as the required force pattern based on movement velocity. In the first paradigm (spatial generalization), following vFF or EVF training, generalization of learning was tested by requiring subjects to move to 14 untrained target locations (0° to ±135° around the trained location). In the second paradigm (temporal stability), following training, we examined the decay of learning over eight delay periods (0 to 90 s). Results showed that learning based on EVF did not generalize to untrained directions, whereas the generalization for the vFF was significant for targets ≤ 45° away. In addition, the decay of learning for the EVF group was significantly faster than the FF group (a time constant of 2.72 ± 1.74 s vs. 12.53 ± 11.83 s). Collectively, our results suggest that recalibrating motor output based on explicit motion state information, in contrast to physical disturbances, uses learning mechanisms with limited spatiotemporal properties.NEW & NOTEWORTHY Adjustment of motor output based on limb motion state information can be achieved based on explicit information or from physical perturbations. Here, we investigated the spatiotemporal characteristics of short-term motor learning to determine the properties of the respective learning mechanisms. Our results suggest that adjustments based on physical perturbations are more temporally stable and applied over a greater spatial range than the learning based on explicit visual feedback, suggesting largely separate learning mechanisms.

Moving a missing hand: children born with below elbow deficiency can enact hand grasp patterns with their residual muscles.

Children with a unilateral congenital below elbow deficiency (UCBED) have one typical upper limb and one that lacks a hand, ending below the elbow at the proximal/mid forearm. UCBED is an isolated condition, and affected children otherwise develop normal sensorimotor control. Unlike adults with upper limb absence, the majority of whom have an acquired loss, children with UCBED never developed a hand, so their residual muscles have never actuated an intact limb. Their ability to purposefully modulate affected muscle activity is often assumed to be limited, and this assumption has influenced prosthetic design and prescription practices for this population as many modern devices derive control signals from affected muscle activity. To better understand the motor capabilities of the affected muscles, we used ultrasound imaging to study 6 children with UCBED. We examined the extent to which subjects activate their affected muscles when performing mirrored movements with their typical and missing hands. We demonstrate that all subjects could intentionally and consistently enact at least five distinct muscle patterns when attempting different missing hand movements (e.g., power grasp) and found similar performance across affected and typically developed limbs. These results suggest that although participants had never actuated the missing hand they could distinctively and consistently activate the residual muscle patterns associated with actions on the unaffected side. These findings indicate that motor control still develops in the absence of the normal effector, and can serve as a guide for developing prostheses that leverage the full extent of these children's motor control capabilities.

Neural Underpinnings of Learning in Dementia Populations: A Review of Motor Learning Studies Combined with Neuroimaging.

The intent of this review article is to serve as an overview of current research regarding the neural characteristics of motor learning in Alzheimer disease (AD) as well as prodromal phases of AD: at-risk populations, and mild cognitive impairment. This review seeks to provide a cognitive framework to compare various motor tasks. We will highlight the neural characteristics related to cognitive domains that, through imaging, display functional or structural changes because of AD progression. In turn, this motivates the use of motor learning paradigms as possible screening techniques for AD and will build upon our current understanding of learning abilities in AD populations.

Review and critique of current testing protocols for upper-limb prostheses: a call for standardization amidst rapid technological advancements.

This article provides a comprehensive narrative review of physical task-based assessments used to evaluate the multi-grasp dexterity and functional impact of varying control systems in pediatric and adult upper-limb prostheses. Our search returned 1,442 research articles from online databases, of which 25 tests-selected for their scientific rigor, evaluation metrics, and psychometric properties-met our review criteria. We observed that despite significant advancements in the mechatronics of upper-limb prostheses, these 25 assessments are the only validated evaluation methods that have emerged since the first measure in 1948. This not only underscores the lack of a consistently updated, standardized assessment protocol for new innovations, but also reveals an unsettling trend: as technology outpaces standardized evaluation measures, developers will often support their novel devices through custom, study-specific tests. These boutique assessments can potentially introduce bias and jeopardize validity. Furthermore, our analysis revealed that current validated evaluation methods often overlook the influence of competing interests on test success. Clinical settings and research laboratories differ in their time constraints, access to specialized equipment, and testing objectives, all of which significantly influence assessment selection and consistent use. Therefore, we propose a dual testing approach to address the varied demands of these distinct environments. Additionally, we found that almost all existing task-based assessments lack an integrated mechanism for collecting patient feedback, which we assert is essential for a holistic evaluation of upper-limb prostheses. Our review underscores the pressing need for a standardized evaluation protocol capable of objectively assessing the rapidly advancing prosthetic technologies across all testing domains.

Using principles of motor control to analyze performance of human machine interfaces.

There have been significant advances in biosignal extraction techniques to drive external biomechatronic devices or to use as inputs to sophisticated human machine interfaces. The control signals are typically derived from biological signals such as myoelectric measurements made either from the surface of the skin or subcutaneously. Other biosignal sensing modalities are emerging. With improvements in sensing modalities and control algorithms, it is becoming possible to robustly control the target position of an end-effector. It remains largely unknown to what extent these improvements can lead to naturalistic human-like movement. In this paper, we sought to answer this question. We utilized a sensing paradigm called sonomyography based on continuous ultrasound imaging of forearm muscles. Unlike myoelectric control strategies which measure electrical activation and use the extracted signals to determine the velocity of an end-effector; sonomyography measures muscle deformation directly with ultrasound and uses the extracted signals to proportionally control the position of an end-effector. Previously, we showed that users were able to accurately and precisely perform a virtual target acquisition task using sonomyography. In this work, we investigate the time course of the control trajectories derived from sonomyography. We show that the time course of the sonomyography-derived trajectories that users take to reach virtual targets reflect the trajectories shown to be typical for kinematic characteristics observed in biological limbs. Specifically, during a target acquisition task, the velocity profiles followed a minimum jerk trajectory shown for point-to-point arm reaching movements, with similar time to target. In addition, the trajectories based on ultrasound imaging result in a systematic delay and scaling of peak movement velocity as the movement distance increased. We believe this is the first evaluation of similarities in control policies in coordinated movements in jointed limbs, and those based on position control signals extracted at the individual muscle level. These results have strong implications for the future development of control paradigms for assistive technologies.

Using Principles of Motor Control to Analyze Performance of Human Machine Interfaces.

There have been significant advances in biosignal extraction techniques to drive external biomechatronic devices or to use as inputs to sophisticated human machine interfaces. The control signals are typically derived from biological signals such as myoelectric measurements made either from the surface of the skin or subcutaneously. Other biosignal sensing modalities are emerging. With improvements in sensing modalities and control algorithms, it is becoming possible to robustly control the target position of a end effector. It remains largely unknown to what extent these improvements can lead to naturalistic human-like movement. In this paper, we sought to answer this question. We utilized a sensing paradigm called sonomyography based on continuous ultrasound imaging of forearm muscles. Unlike myoelectric control strategies which measure electrical activation and use the extracted signals to determine the velocity of an end-effector; sonomyography measures muscle deformation directly with ultrasound and uses the extracted signals to proportionally control the position of an end-effector. Previously, we showed that users were able to accurately and precisely perform a virtual target acquisition task using sonomyography. In this work, we investigate the time course of the control trajectories derived from sonomyography. We show that the time course of the sonomyography-derived trajectories that users take to reach virtual targets reflect the trajectories shown to be typical for kinematic characteristics observed in biological limbs. Specifically, during a target acquisition task, the velocity profiles followed a minimum jerk trajectory shown for point-to-point arm reaching movements, with similar time to target. In addition, the trajectories based on ultrasound imaging result in a systematic delay and scaling of peak movement velocity as the movement distance increased. We believe this is the first evaluation of similarities in control policies in coordinated movements in jointed limbs, and those based on position control signals extracted at the individual muscle level. These results have strong implications for the future development of control paradigms for assistive technologies.

A multiarticulate pediatric prosthetic hand for clinical and research applications.

Although beginning to emerge, multiarticulate upper limb prostheses for children remain sparse despite the continued advancement of mechatronic technologies that have benefited adults with upper limb amputations. Upper limb prosthesis research is primarily focused on adults, even though rates of pediatric prosthetic abandonment far surpass those seen in adults. The implicit goal of a prosthesis is to provide effective functionality while promoting healthy social interaction. Yet most current pediatric devices offer a single degree of freedom open/close grasping function, a stark departure from the multiple grasp configurations provided in advanced adult devices. Although comparable child-sized devices are on the clinical horizon, understanding how to effectively translate these technologies to the pediatric population is vital. This includes exploring grasping movements that may provide the most functional benefits and techniques to control the newly available dexterity. Currently, no dexterous pediatric research platforms exist that offer open access to hardware and programming to facilitate the investigation and provision of multi-grasp function. Our objective was to deliver a child-sized multi-grasp prosthesis that may serve as a robust research platform. In anticipation of an open-source release, we performed a comprehensive set of benchtop and functional tests with common household objects to quantify the performance of our device. This work discusses and evaluates our pediatric-sized multiarticulate prosthetic hand that provides 6 degrees of actuation, weighs 177 g and was designed specifically for ease of implementation in a research or clinical-research setting. Through the benchtop and validated functional tests, the pediatric hand produced grasping forces ranging from 0.424-7.216 N and was found to be comparable to the functional capabilities of similar adult devices. As mechatronic technologies advance and multiarticulate prostheses continue to evolve, translating many of these emerging technologies may help provide children with more useful and functional prosthesis options. Effective translation will inevitably require a solid scientific foundation to inform how best to prescribe advanced prosthetic devices and control systems for children. This work begins addressing these current gaps by providing a much-needed research platform with supporting data to facilitate its use in laboratory and clinical research settings.

Characterizing Pediatric Hand Grasps During Activities of Daily Living to Inform Robotic Rehabilitation and Assistive Technologies.

Hand function plays a critical role in how we interact with our physical environment. Hand motor impairments in children can compromise many facets of their daily life including physical independence and social interactions. For adults, there has been an emergence of mechatronic rehabilitation systems to improve hand mobility, strength, and dexterity; assistive technologies such as exoskeletons to drive impaired digits; and highly dexterous upper limb prostheses. Although similar devices are on the clinical horizon for children, childhood play, motor development, and daily activities mean they use their hands in fundamentally different ways than adults. It is imperative that devices for this population facilitate their unique needs; yet it is not completely known which hand movements may be of the highest priority during daily tasks or rehabilitation to best foster functional independence. Here, we evaluated and categorized the hand activity of two children in their home environments. Small wearable video cameras were attached to the children as they performed daily tasks and the video footage was analyzed to obtain the frequency and duration of their hand grasp movements. It was found that 7 common grasps accounted for 90% or greater of the children's hand activity in duration and frequency. This suggests, that like adults, a repertoire of common hand grasps may be prioritized by rehabilitative or assistive devices to ensure effective outcomes in performing daily activities.

Sonomyography shows feasibility as a tool to quantify joint movement at the muscle level.

Several methods have been used to quantify human movement at different levels, from coordinated multi joint movements to those taking place at the single muscle level. These methods are developed either in order to allow us to interact with computers and machines, or to use such technologies for aiding rehabilitation among those with mobility impairments or movement disorders. Human machine interfaces typically rely on some existing human movement ability and measure it using motion tracking or inertial measurement units, while the rehabilitation applications may require us to measure human motor intent. Surface or implanted electrodes, electromyography, electroencephalography, and brain computer interfaces are beneficial in this regard, but have their own shortcomings. We have previously shown feasibility of using ultrasound imaging (Sonomyography) to infer human motor intent and allow users to control external biomechatronic devices such as prosthetics. Here, we asked users to freely move their hand in three different movement patterns, measuring their actual joint angles and passively computing their Sonomyographic output signal. We found a high correlation between these two signals, demonstrating that the Sonomyography signal is not only user-controlled and stable, but it is closely linked with the user's actual movement level. These results could help design wearable rehabilitation or human computer interaction devices based on Sonomyography to decode human motor intent.

Motion state-dependent motor learning based on explicit visual feedback is quickly recalled, but is less stable than adaptation to physical perturbations.

Recent studies have shown that adaptation to visual feedback perturbations during arm reaching movements involves implicit and explicit learning components. Evidence also suggests that explicit, intentional learning mechanisms are largely responsible for savings-a faster recalibration compared with initial training. However, the extent explicit learning mechanisms facilitate learning and early savings (i.e., the rapid recall of previous performance) for motion state-dependent learning is generally unknown. To address this question, we compared the early savings/recall achieved by two groups of human subjects. One experienced physical perturbations (a velocity-dependent force-field, vFF) to promote adaptation that is thought to be a largely implicit process. The second was only given visual feedback of the required force-velocity relationship; subjects moved in force channels and we provided visual feedback of the lateral force exerted during the movement, as well as the required force pattern based on the movement velocity. Thus, subjects were shown explicit information on the extent the applied temporal pattern of force matched the required velocity-dependent force profile if the force-field perturbation had been applied. After training, both groups experienced a decay and washout period, which was followed by a reexposure block to assess early savings/recall. Although decay was faster for the explicit visual feedback group, the single-trial recall was similar to the physical perturbation group. Thus, compared with visual feedback perturbations, conscious modification of motor output based on motion state-dependent feedback demonstrates rapid recall, but this adjustment is less stable than adaptation based on experiencing the multisensory errors that accompany physical perturbations.NEW & NOTEWORTHY The extent explicit feedback facilitates motion state-dependent changes to motor output is largely unknown. Here, we examined motor adaptation for subjects that experienced physical perturbations and another that made adjustments based on explicit visual feedback information of the required force-velocity relationship. Our results suggest that adjustment of motor output can be based on explicit motion state-dependent information and demonstrates rapid recall, but this learning is less stable than adaptation based on physical perturbations to movement.

A review of upper limb pediatric prostheses and perspectives on future advancements.

Many complex factors affect whether a child with a congenital upper limb deficiency will wear a prosthetic limb. Ultimately, for a child to wear and use their prosthesis, it must facilitate the effective performance of daily tasks and promote healthy social interactions. Although numerous pediatric devices are available, most provide a single open-close grasp (if a grasping function is available at all) and often offer nonanthropomorphic appearances, falling short of meeting these criteria. In this narrative review, we provide a critical assessment of the state of upper limb prostheses for children. We summarize literature using quality of life measures and categorize driving factors affecting prosthesis use into two main groupings: psychosocial and physical functioning. We define psychosocial functioning as factors related to social inclusion/exclusion, emotional function, independence, and school functioning. Physical functioning is defined as factors associated with the physical use of a prosthesis. The reviewed literature suggests that psychosocial domains of quality of life may be influenced by a congenital limb deficiency, and currently available prostheses provide little benefit in the physical functioning domains. Finally, we discuss technological advancements in adult prostheses that have yet to be leveraged for pediatric devices, including describing recently developed adult electric hands that may improve physical functioning through multiple grasping configurations and provide more hand-like cosmesis. We outline actions necessary to translate similar technologies for children and discuss further strategies to begin removing barriers to pediatric device adoption.

Quantifying the kinematic features of dexterous finger movements in nonhuman primates with markerless tracking.

Research using nonhuman primate models for human disease frequently requires behavioral observational techniques to quantify functional outcomes. The ability to assess reaching and grasping patterns is of particular interest in clinical conditions that affect the motor system (e.g., spinal cord injury, SCI). Here we explored the use of DeepLabCut, an open-source deep learning toolset, in combination with a standard behavioral task (Brinkman Board) to quantify nonhuman primate performance in precision grasping. We examined one male rhesus macaque (Macaca mulatta) in the task which involved retrieving rewards from variously-oriented shallow wells. Simultaneous recordings were made using GoPro Hero7 Black cameras (resolution 1920 x 1080 at 120 fps) from two different angles (from the side and top of the hand motion). The task/device design necessitates use of the right hand to complete the task. Two neural networks (corresponding to the top and side view cameras) were trained using 400 manually annotated images, tracking 19 unique landmarks each. Based on previous reports, this produced sufficient tracking (Side: trained pixel error of 2.15, test pixel error of 11.25; Top: trained pixel error of 2.06, test pixel error of 30.31) so that landmarks could be tracked on the remaining frames. Landmarks included in the tracking were the spatial location of the knuckles and the fingernails of each digit, and three different behavioral measures were quantified for assessment of hand movement (finger separation, middle digit extension and preshaping distance). Together, our preliminary results suggest that this markerless approach is a possible method to examine specific kinematic features of dexterous function.Clinical Relevance- The methodology presented below allows for the markerless tracking of kinematic features of dexterous finger movement by non-human primates. This method could allow for direct comparisons between human patients and non-human primate models of clinical conditions (e.g., spinal cord injury). This would provide objective quantitative metrics and crucial information for assessing movement impairments across populations and the potential translation of treatments, interventions and their outcomes.

Normal Aging Affects the Short-Term Temporal Stability of Implicit, But Not Explicit, Motor Learning following Visuomotor Adaptation.

Normal aging is associated with a decline in memory and motor learning ability. However, the exact form of these impairments (e.g., the short-term temporal stability and affected learning mechanisms) is largely unknown. Here, we used a sensorimotor adaptation task to examine changes in the temporal stability of two forms of learning (explicit and implicit) because of normal aging. Healthy young subjects (age range, 19-28 years; 20 individuals) and older human subjects (age range, 63-85 years; 19 individuals) made reaching movements in response to altered visual feedback. On each trial, subjects turned a rotation dial to select an explicit aiming direction. Once selected, the display was removed and subjects moved the cursor from the start position to the target. After initial training with the rotational feedback perturbation, subjects completed a series of probe trials at different delay periods to systematically assess the short-term retention of learning. For both groups, the explicit aiming showed no significant decrease over 1.5 min. However, this was not the case for implicit learning; the decay pattern was markedly different between groups. Older subjects showed a linear decrease of the implicit component of adaptation over time, while young subjects showed an exponential decay over the same period (time constant, 25.61 s). Although older subjects adapted at a similar rate, these results suggest natural aging selectively impacts the short-term (seconds to minutes) temporal stability of implicit motor learning mechanisms. This understanding may provide a means to dissociate natural aging memory impairments from deficits caused by brain disorders that progress with aging.

Transsaccadic visual perception of foveal compared to peripheral environmental changes.

The maintenance of stable visual perception across eye movements is hypothesized to be aided by extraretinal information (e.g., corollary discharge [CD]). Previous studies have focused on the benefits of this information for perception at the fovea. However, there is little information on the extent that CD benefits peripheral visual perception. Here we systematically examined the extent that CD supports the ability to perceive transsaccadic changes at the fovea compared to peripheral changes. Human subjects made saccades to targets positioned at different amplitudes (4° or 8°) and directions (rightward or upward). On each trial there was a reference point located either at (fovea) or 4° away (periphery) from the target. During the saccade the target and reference disappeared and, after a blank period, the reference reappeared at a shifted location. Subjects reported the perceived shift direction, and we determined the perceptual threshold for detection and estimate of the reference location. We also simulated the detection and location if subjects solely relied on the visual error of the shifted reference experienced after the saccade. The comparison of the reference location under these two conditions showed that overall the perceptual estimate was approximately 53% more accurate and 30% less variable than estimates based solely on visual information at the fovea. These values for peripheral shifts were consistently lower than that at the fovea: 34% more accurate and 9% less variable. Overall, the results suggest that CD information does support stable visual perception in the periphery, but is consistently less beneficial compared to the fovea.

Slowing the body slows down time perception.

Interval timing is a fundamental component of action and is susceptible to motor-related temporal distortions. Previous studies have shown that concurrent movement biases temporal estimates, but have primarily considered self-modulated movement only. However, real-world encounters often include situations in which movement is restricted or perturbed by environmental factors. In the following experiments, we introduced viscous movement environments to externally modulate movement and investigated the resulting effects on temporal perception. In two separate tasks, participants timed auditory intervals while moving a robotic arm that randomly applied four levels of viscosity. Results demonstrated that higher viscosity led to shorter perceived durations. Using a drift-diffusion model and a Bayesian observer model, we confirmed these biasing effects arose from perceptual mechanisms, instead of biases in decision making. These findings suggest that environmental perturbations are an important factor in movement-related temporal distortions, and enhance the current understanding of the interactions of motor activity and cognitive processes.

Sonomyography Combined with Vibrotactile Feedback Enables Precise Target Acquisition Without Visual Feedback.

Upper limb prosthesis users currently lack haptic feedback from their terminal devices, which significantly limits their ability to meaningfully interact with their environment. Users therefore rely heavily on visual feedback when using terminal devices. Previously, it has been shown that force-related feedback from an end-effector or virtual environment can help the user minimize errors and improve performance. Currently, myoelectric control systems enable the user to control the velocity of terminal devices. We have developed a novel control method using ultrasound sensing, called sonomyography, that enables position control based on mechanical deformation of muscles. In this paper, we investigated whether the proprioceptive feedback from muscle deformation combined with vibrotactile haptic feedback can minimize the need for visual feedback. Able bodied subjects used sonomyography to control a virtual cursor, and performed a target acquisition task. The effect of visual and haptic feedback on performance of a target acquisition task was systematically tested. We found that subjects made large errors when they tried to reacquire a target without visual feedback, but in the presence of real-time haptic feedback, the precision of the target position improved, and were similar to when visual feedback was used for target acquisition. This result has implications for improving the performance of prosthetic control systems.

Dissociating effects of error size, training duration, and amount of adaptation on the ability to retain motor memories.

Extensive computational and neurobiological work has focused on how the training schedule, i.e., the duration and rate at which an environmental disturbance is presented, shapes the formation of motor memories. If long-lasting benefits are to be derived from motor training, however, retention of the performance improvements gained during practice is essential. Thus a better understanding of mechanisms that promote retention could lead to the design of more effective training procedures. The few studies that have investigated how retention depends on the training schedule have suggested that the gradual exposure of a perturbation leads to improved retention of motor memory compared with an abrupt exposure. However, several of these previous studies showed small effects, and although some controlled the training duration and others the level of learning, none have controlled both. In the present study we disambiguated both of these effects from exposure rate by systematically varying the duration of training, type of trained dynamics, and exposure rate for these dynamics in human force-field adaptation. After controlling for both training duration and the amount of learning, we found essentially identical retention when comparing gradual and abrupt training for two different types of force-field dynamics. By contrast, we found that retention was markedly higher for long-duration compared with short-duration training for both types of dynamics. These results demonstrate that the duration of training has a far greater effect on the retention of motor memory than the exposure rate during training. We show that a multirate learning model provides a computational mechanism for these findings.NEW & NOTEWORTHY Previous studies have suggested that a gradual, incremental introduction of a novel environment is helpful for improving retention. However, we used experimental and computational approaches to demonstrate that previously reported improvements in retention associated with gradual introductions fail to persist when other factors, including the duration of training and the degree of initial learning, are accounted for.