Motor adaptation to a novel dynamic environment is primarily thought of as a process in which the nervous system learns to anticipate the environmental forces to eliminate kinematic error. Here we show that motor adaptation can more generally be modeled as a process in which the motor system greedily minimizes a cost function that is the weighted sum of kinematic error and effort. The learning dynamics predicted by this minimization process are a linear, auto-regressive equation with only one state, which has been identified previously as providing a good fit to data from force-field-type experiments. Thus we provide a new theoretical result that shows how these previously identified learning dynamics can be viewed as arising from an optimization of error and effort. We also show that the coefficients of the learning dynamics must fall within a specific range for the optimization model to be valid and verify with experimental data from walking in a force field that they indeed fall in this range. Finally, we attempted to falsify the model by performing experiments in two conditions (repeated exposure to a force field, exposure to force fields of different strengths) for which the single-state, auto-regressive equation might be expected to not fit the data well. We found however that the equation adequately captured the pattern of errors and thus conclude that motor adaptation to a force field can be approximated as an optimization of effort and error for a range of experimental conditions.

Background: A prevailing paradigm of physical rehabilitation following neurologic injury is to "assist-as-needed" in completing desired movements. Several research groups are attempting to automate this principle with robotic movement training devices and patient cooperative algorithms that encourage voluntary participation. These attempts are currently not based on computational models of motor learning. Methods: Here we assume that motor recovery from a neurologic injury can be modelled as a process of learning a novel sensory motor transformation, which allows us to study a simplified experimental protocol amenable to mathematical description. Specifically, we use a robotic force field paradigm to impose a virtual impairment on the left leg of unimpaired subjects walking on a treadmill. We then derive an "assist-as-needed" robotic training algorithm to help subjects overcome the virtual impairment and walk normally. The problem is posed as an optimization of performance error and robotic assistance. The optimal robotic movement trainer becomes an error-based controller with a forgetting factor that bounds kinematic errors while systematically reducing its assistance when those errors are small. As humans have a natural range of movement variability, we introduce an error weighting function that causes the robotic trainer to disregard this variability. Results: We experimentally validated the controller with ten unimpaired subjects by demonstrating how it helped the subjects learn the novel sensory motor transformation necessary to counteract the virtual impairment, while also preventing them from experiencing large kinematic errors. The addition of the error weighting function allowed the robot assistance to fade to zero even though the subjects' movements were variable. We also show that in order to assist-as-needed, the robot must relax its assistance at a rate faster than that of the learning human. Conclusion: The assist-as-needed algorithm proposed here can limit error during the learning of a dynamic motor task. The algorithm encourages learning by decreasing its assistance as a function of the ongoing progression of movement error. This type of algorithm is well suited for helping people learn dynamic tasks for which large kinematic errors are dangerous or discouraging, and thus may prove useful for robot-assisted movement training of walking or reaching following neurologic injury.

Clinical and basic studies shed light on the mechanism, diagnosis, and treatment of cardiac ryanodine receptor Ca ²⁺ release deficiency syndrome.

The modern multi-channel cochlear implant is widely considered to be the most successful neural prosthesis owing to its ability to restore partial hearing to post-lingually deafened adults and to allow essentially normal language development in pre-lingually deafened children. However, the implant performance varies greatly in individuals and is still limited in background noise, tonal language understanding, and music perception. One main cause for the individual variability and the limited performance in cochlear implants is spatial channel interaction from the stimulating electrodes to the auditory nerve and brain. Here we systematically examined spatial channel interactions at the physical, physiological, and perceptual levels in the same five modern cochlear implant subjects. The physical interaction was examined using an electric field imaging technique, which measured the voltage distribution as a function of the electrode position in the cochlea in response to the stimulation of a single electrode. The physiological interaction was examined by recording electrically evoked compound action potentials as a function of the electrode position in response to the stimulation of the same single electrode position. The perceptual interactions were characterized by changes in detection threshold as well as loudness summation in response to in-phase or out-of-phase dual-electrode stimulation. To minimize potentially confounding effects of temporal factors on spatial channel interactions, stimulus rates were limited to 100 Hz or less in all measurements. Several quantitative channel interaction indexes were developed to define and compare the width, slope and symmetry of the spatial excitation patterns derived from these physical, physiological and perceptual measures. The electric field imaging data revealed a broad but uniformly asymmetrical intracochlear electric field pattern, with the apical side producing a wider half-width and shallower slope than the basal side. In contrast, the evoked compound action potential and perceptual channel interaction data showed much greater individual variability. It is likely that actual reduction in neural and higher level interactions, instead of simple sharpening of the electric current field, would be the key to predicting and hopefully improving the variable cochlear implant performance. The present results are obtained with auditory prostheses but can be applied to other neural prostheses, in which independent spatial channels, rather than a high stimulation rate, are critical to their performance.

Rationale : Phospholamban (PLN) is an inhibitor of cardiac sarco(endo)plasmic reticulum Ca ²⁺ ATPase. PLN knockout (PLN-KO) enhances sarcoplasmic reticulum Ca ²⁺ load and Ca ²⁺ leak. Conversely, PLN-KO accelerates Ca ²⁺ sequestration and aborts arrhythmogenic spontaneous Ca ²⁺ waves (SCWs). An important question is whether these seemingly paradoxical effects of PLN-KO exacerbate or protect against Ca ²⁺ -triggered arrhythmias. Objective : We investigate the impact of PLN-KO on SCWs, triggered activities, and stress-induced ventricular tachyarrhythmias (VTs) in a mouse model of cardiac ryanodine-receptor (RyR2)-linked catecholaminergic polymorphic VT. Methods and Results : We generated a PLN-deficient, RyR2-mutant mouse model (PLN ^−/− /RyR2-R4496C ^+/− ) by crossbreeding PLN-KO mice with catecholaminergic polymorphic VT–associated RyR2-R4496C mutant mice. Ca ²⁺ imaging and patch-clamp recording revealed cell-wide propagating SCWs and triggered activities in RyR2-R4496C ^+/− ventricular myocytes during sarcoplasmic reticulum Ca ²⁺ overload. PLN-KO fragmented these cell-wide SCWs into mini-waves and Ca ²⁺ sparks and suppressed the triggered activities evoked by sarcoplasmic reticulum Ca ²⁺ overload. Importantly, these effects of PLN-KO were reverted by partially inhibiting sarco(endo)plasmic reticulum Ca ²⁺ ATPase with 2,5-di-tert-butylhydroquinone. However, Bay K, caffeine, or Li ⁺ failed to convert mini-waves to cell-wide SCWs in PLN ^−/− /RyR2-R4496C ^+/− ventricular myocytes. Furthermore, ECG analysis showed that PLN-KO mice are not susceptible to stress-induced VTs. On the contrary, PLN-KO protected RyR2-R4496C mutant mice from stress-induced VTs. Conclusions : Our results demonstrate that despite severe sarcoplasmic reticulum Ca ²⁺ leak, PLN-KO suppresses triggered activities and stress-induced VTs in a mouse model of catecholaminergic polymorphic VT. These data suggest that breaking up cell-wide propagating SCWs by enhancing Ca ²⁺ sequestration represents an effective approach for suppressing Ca ²⁺ -triggered arrhythmias.