120 research outputs found
Characterization of Neural Tuning: Visual Lead-in Movements Generalize in Speed and Distance
Prior work has shown that independent motor memories of opposing dynamics can be learned when the movements are preceded by unique lead-in movements, each associated with a different direction of dynamics. Here we examine generalization effects using visual lead-in movements. Specifically, we test how variations in lead-in kinematics, in terms of duration, speed and distance, effect the expression of the learned motor memory. We show that the motor system is more strongly affected by changes in the duration of the movement, whereas longer movement distances have no effect
Flow-based dissimilarity measures for reservoir models: a spatial-temporal tensor approach
Proprioceptive loss and the perception, control and learning of arm movements in humans: evidence from sensory neuronopathy
Š 2018 The Author(s) It is uncertain how vision and proprioception contribute to adaptation of voluntary arm movements. In normal participants, adaptation to imposed forces is possible with or without vision, suggesting that proprioception is sufficient; in participants with proprioceptive loss (PL), adaptation is possible with visual feedback, suggesting that proprioception is unnecessary. In experiment 1 adaptation to, and retention of, perturbing forces were evaluated in three chronically deafferented participants. They made rapid reaching movements to move a cursor toward a visual target, and a planar robot arm applied orthogonal velocity-dependent forces. Trial-by-trial error correction was observed in all participants. Such adaptation has been characterized with a dual-rate model: a fast process that learns quickly, but retains poorly and a slow process that learns slowly and retains well. Experiment 2 showed that the PL participants had large individual differences in learning and retention rates compared to normal controls. Experiment 3 tested participantsâ perception of applied forces. With visual feedback, the PL participants could report the perturbationâs direction as well as controls; without visual feedback, thresholds were elevated. Experiment 4 showed, in healthy participants, that force direction could be estimated from head motion, at levels close to the no-vision threshold for the PL participants. Our results show that proprioceptive loss influences perception, motor control and adaptation but that proprioception from the moving limb is not essential for adaptation to, or detection of, force fields. The differences in learning and retention seen between the three deafferented participants suggest that they achieve these tasks in idiosyncratic ways after proprioceptive loss, possibly integrating visual and vestibular information with individual cognitive strategies
Estimating the Relevance of World Disturbances to Explain Savings, Interference and Long-Term Motor Adaptation Effects
Recent studies suggest that motor adaptation is the result of multiple, perhaps linear processes each with distinct time scales. While these models are consistent with some motor phenomena, they can neither explain the relatively fast re-adaptation after a long washout period, nor savings on a subsequent day. Here we examined if these effects can be explained if we assume that the CNS stores and retrieves movement parameters based on their possible relevance. We formalize this idea with a model that infers not only the sources of potential motor errors, but also their relevance to the current motor circumstances. In our model adaptation is the process of re-estimating parameters that represent the body and the world. The likelihood of a world parameter being relevant is then based on the mismatch between an observed movement and that predicted when not compensating for the estimated world disturbance. As such, adapting to large motor errors in a laboratory setting should alert subjects that disturbances are being imposed on them, even after motor performance has returned to baseline. Estimates of this external disturbance should be relevant both now and in future laboratory settings. Estimated properties of our bodies on the other hand should always be relevant. Our model demonstrates savings, interference, spontaneous rebound and differences between adaptation to sudden and gradual disturbances. We suggest that many issues concerning savings and interference can be understood when adaptation is conditioned on the relevance of parameters
Potential of a suite of robot/computer-assisted motivating systems for personalized, home-based, stroke rehabilitation
BACKGROUND: There is a need to improve semi-autonomous stroke therapy in home environments often characterized by low supervision of clinical experts and low extrinsic motivation. Our distributed device approach to this problem consists of an integrated suite of low-cost robotic/computer-assistive technologies driven by a novel universal access software framework called UniTherapy. Our design strategy for personalizing the therapy, providing extrinsic motivation and outcome assessment is presented and evaluated. METHODS: Three studies were conducted to evaluate the potential of the suite. A conventional force-reflecting joystick, a modified joystick therapy platform (TheraJoy), and a steering wheel platform (TheraDrive) were tested separately with the UniTherapy software. Stroke subjects with hemiparesis and able-bodied subjects completed tracking activities with the devices in different positions. We quantify motor performance across subject groups and across device platforms and muscle activation across devices at two positions in the arm workspace. RESULTS: Trends in the assessment metrics were consistent across devices with able-bodied and high functioning strokes subjects being significantly more accurate and quicker in their motor performance than low functioning subjects. Muscle activation patterns were different for shoulder and elbow across different devices and locations. CONCLUSION: The Robot/CAMR suite has potential for stroke rehabilitation. By manipulating hardware and software variables, we can create personalized therapy environments that engage patients, address their therapy need, and track their progress. A larger longitudinal study is still needed to evaluate these systems in under-supervised environments such as the home
Stroke Rehabilitation Reaches a Threshold
Motor training with the upper limb affected by stroke partially reverses the loss of cortical representation after lesion and has been proposed to increase spontaneous arm use. Moreover, repeated attempts to use the affected hand in daily activities create a form of practice that can potentially lead to further improvement in motor performance. We thus hypothesized that if motor retraining after stroke increases spontaneous arm use sufficiently, then the patient will enter a virtuous circle in which spontaneous arm use and motor performance reinforce each other. In contrast, if the dose of therapy is not sufficient to bring spontaneous use above threshold, then performance will not increase and the patient will further develop compensatory strategies with the less affected hand. To refine this hypothesis, we developed a computational model of bilateral hand use in arm reaching to study the interactions between adaptive decision making and motor relearning after motor cortex lesion. The model contains a left and a right motor cortex, each controlling the opposite arm, and a single action choice module. The action choice module learns, via reinforcement learning, the value of using each arm for reaching in specific directions. Each motor cortex uses a neural population code to specify the initial direction along which the contralateral hand moves towards a target. The motor cortex learns to minimize directional errors and to maximize neuronal activity for each movement. The derived learning rule accounts for the reversal of the loss of cortical representation after rehabilitation and the increase of this loss after stroke with insufficient rehabilitation. Further, our model exhibits nonlinear and bistable behavior: if natural recovery, motor training, or both, brings performance above a certain threshold, then training can be stopped, as the repeated spontaneous arm use provides a form of motor learning that further bootstraps performance and spontaneous use. Below this threshold, motor training is âin vainâ: there is little spontaneous arm use after training, the model exhibits learned nonuse, and compensatory movements with the less affected hand are reinforced. By exploring the nonlinear dynamics of stroke recovery using a biologically plausible neural model that accounts for reversal of the loss of motor cortex representation following rehabilitation or the lack thereof, respectively, we can explain previously hard to reconcile data on spontaneous arm use in stroke recovery. Further, our threshold prediction could be tested with an adaptive trainâwaitâtrain paradigm: if spontaneous arm use has increased in the âwaitâ period, then the threshold has been reached, and rehabilitation can be stopped. If spontaneous arm use is still low or has decreased, then another bout of rehabilitation is to be provided
Robotic neurorehabilitation: a computational motor learning perspective
Conventional neurorehabilitation appears to have little impact on impairment over and above that of spontaneous biological recovery. Robotic neurorehabilitation has the potential for a greater impact on impairment due to easy deployment, its applicability across of a wide range of motor impairment, its high measurement reliability, and the capacity to deliver high dosage and high intensity training protocols
Adaptive robot training for the treatment of incoordination in Multiple Sclerosis
<p>Abstract</p> <p>Background</p> <p>Cerebellar symptoms are extremely disabling and are common in Multiple Sclerosis (MS) subjects. In this feasibility study, we developed and tested a robot therapy protocol, aimed at the rehabilitation of incoordination in MS subjects.</p> <p>Methods</p> <p>Eight subjects with clinically defined MS performed planar reaching movements while grasping the handle of a robotic manipulandum, which generated forces that either reduced (error-reducing, ER) or enhanced (error-enhancing, EE) the curvature of their movements, assessed at the beginning of each session. The protocol was designed to adapt to the individual subjects' impairments, as well as to improvements between sessions (if any). Each subject went through a total of eight training sessions. To compare the effect of the two variants of the training protocol (ER and EE), we used a cross-over design consisting of two blocks of sessions (four ER and four EE; 2 sessions/week), separated by a 2-weeks rest period. The order of application of ER and EE exercises was randomized across subjects. The primary outcome measure was the modification of the Nine Hole Peg Test (NHPT) score. Other clinical scales and movement kinematics were taken as secondary outcomes.</p> <p>Results</p> <p>Most subjects revealed a preserved ability to adapt to the robot-generated forces. No significant differences were observed in EE and ER training. However over sessions, subjects exhibited an average 24% decrease in their NHPT score. The other clinical scales showed small improvements for at least some of the subjects. After training, movements became smoother, and their curvature decreased significantly over sessions.</p> <p>Conclusions</p> <p>The results point to an improved coordination over sessions and suggest a potential benefit of a short-term, customized, and adaptive robot therapy for MS subjects.</p
Modifiable risk factors associated with bone deficits in childhood cancer survivors
<p>Abstract</p> <p>Background</p> <p>To determine the prevalence and severity of bone deficits in a cohort of childhood cancer survivors (CCS) compared to a healthy sibling control group, and the modifiable factors associated with bone deficits in CCS.</p> <p>Methods</p> <p>Cross-sectional study of bone health in 319 CCS and 208 healthy sibling controls. Bone mineral density (BMD) was measured by dual-energy x-ray absorptiometry (DXA). Generalized estimating equations were used to compare measures between CCS and controls. Among CCS, multivariable logistic regression was used to evaluate odds ratios for BMD Z-score ⤠-1.</p> <p>Results</p> <p>All subjects were younger than 18 years of age. Average time since treatment was 10.1 years (range 4.3 - 17.8 years). CCS were 3.3 times more likely to have whole body BMD Z-score ⤠-1 than controls (95% CI: 1.4-7.8; p = 0.007) and 1.7 times more likely to have lumbar spine BMD Z-score ⤠-1 than controls (95% CI: 1.0-2.7; p = 0.03). Among CCS, hypogonadism, lower lean body mass, higher daily television/computer screen time, lower physical activity, and higher inflammatory marker IL-6, increased the odds of having a BMD Z-score ⤠-1.</p> <p>Conclusions</p> <p>CCS, less than 18 years of age, have bone deficits compared to a healthy control group. Sedentary lifestyle and inflammation may play a role in bone deficits in CCS. Counseling CCS and their caretakers on decreasing television/computer screen time and increasing activity may improve bone health.</p
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