Children with autism exhibit a host of motor disorders including poor coordination, poor tool use and delayed learning of complex motor skills like riding a tricycle. Theory suggests that one of the crucial steps in motor learning is the ability to form internal models: to predict the sensory consequences of motor commands and learn from errors to improve performance on the next attempt. The cerebellum appears to be an important site for acquisition of internal models, and indeed the development of the cerebellum is abnormal in autism. Here, we examined autistic children on a range of tasks that required a change in the motor output in response to a change in the environment. We first considered a prism adaptation task in which the visual map of the environment was shifted. The children were asked to throw balls to visual targets with and without the prism goggles. We next considered a reaching task that required moving the handle of a novel tool (a robotic arm). The tool either imposed forces on the hand or displaced the cursor associated with the handle position. In all tasks, the children with autism adapted their motor output by forming a predictive internal model, as exhibited through after-effects. Surprisingly, the rates of acquisition and washout were indistinguishable from normally developing children. Therefore, the mechanisms of acquisition and adaptation of internal models in self-generated movements appeared normal in autism. Sparing of adaptation suggests that alternative mechanisms contribute to impaired motor skill development in autism. Furthermore, the findings may have therapeutic implications, highlighting a reliable mechanism by which children with autism can most effectively alter their behaviour.
reach adaptation; prism adaptation; motor control; autism
When we use a novel tool, the motor commands may not produce the expected outcome. In healthy individuals, with practice the brain learns to alter the motor commands. This change depends critically on the cerebellum as damage to this structure impairs adaptation. However, it is unclear precisely what the cerebellum contributes to the process of adaptation in human motor learning. Is the cerebellum crucial for learning to associate motor commands with novel sensory consequences, called forward model, or is the cerebellum important for learning to associate sensory goals with novel motor commands, called inverse model? Here, we compared performance of cerebellar patients and healthy controls in a reaching task with a gradual perturbation schedule. This schedule allowed both groups to adapt their motor commands. Following training, we measured two kinds of behavior: in one case people were presented with reach targets near the direction in which they had trained. The resulting generalization patterns of patients and controls were similar, suggesting comparable inverse models. In another case, they reached without a target and reported the location of their hand. In controls the pattern of change in reported hand location was consistent with simulation results of a forward model that had learned to associate motor commands with new sensory consequences. In patients, this change was significantly smaller. Therefore, in our sample of patients we observed that while adaptation of motor commands can take place despite cerebellar damage, cerebellar integrity appears critical for learning to predict visual sensory consequences of motor commands.
Children with autism spectrum disorder (ASD) exhibit deficits in motor control, imitation, and social function. Does a dysfunction in the neural basis of representing internal models of action contribute to these problems? We measured patterns of generalization as children learned to control a novel tool and found that the autistic brain built a stronger than normal association between self generated motor commands and proprioceptive feedback; furthermore, the greater the reliance on proprioception, the greater the child’s impairments in social function and imitation.
Motor deficits are commonly reported in autism, with one of the most consistent findings being impaired execution of skilled movements and gestures. Given the developmental nature of autism, it is possible that deficits in motor/procedural learning contribute to impaired acquisition of motor skills. Thus, careful examination of mechanisms underlying learning and memory may be critical to understanding the neural basis of autism. A previous study reported impaired motor learning in children with high-functioning autism (HFA); however, it is unclear whether the observed deficits in motor learning are due, in part, to impaired motor execution and whether these deficits are specific to autism. In order to examine these questions, 153 children (52 with HFA, 39 with attention-deficit/hyperactivity disorder (ADHD) and 62 typically developing (TD) children) participated in two independent experiments using a Rotary Pursuit task, with change in performance across blocks as a measure of learning. For both tasks, children with HFA demonstrated significantly less change in performance than did TD children, even when differences in motor execution were minimized. Differences in learning were not seen between ADHD and TD groups on either experiment. Analyses of the pattern of findings revealed that compared with both ADHD and TD children, children with HFA showed a similar degree of improvement in performance; however, they showed significantly less decrement in performance when presented with an alternate (“interference”) pattern. The findings suggest that mechanisms underlying acquisition of novel movement patterns may differ in children with autism. These findings may help explain impaired skill development in children with autism and help to guide approaches for helping children learn novel motor, social and communicative skills.
procedural memory; declarative memory; cerebellum; visuomotor learning
The aim of this study was to quantify the frequently observed problems in motor control in Neurofibromatosis type 1 (NF1) using three tasks on motor performance and motor learning. A group of 70 children with NF1 was compared to age-matched controls. As expected, NF1 children showed substantial problems in visuo-motor integration (Beery VMI). Prism-induced hand movement adaptation seemed to be mildly affected. However, no significant impairments in the accuracy of simple eye or hand movements were observed. Also, saccadic eye movement adaptation, a cerebellum dependent task, appeared normal. These results suggest that the motor problems of children with NF1 in daily life are unlikely to originate solely from impairments in motor learning. Our findings, therefore, do not support a general dysfunction of the cerebellum in children with NF1.
Neurofibromatosis type 1; Children; Motor deficits; Motor control; Eye movements; Hand movements
Neural plasticity is a key topic in the study of behavioral neuroscience, yet it can be a difficult concept to demonstrate in a classroom setting. In this report, we describe an interactive technique that can be used to demonstrate and quantify in a laboratory setting the plasticity of motor coordination to altered visual input, i.e. visuo-motor plasticity. Visual input can be easily altered by horizontally-displacing prism goggles. Open-loop motor coordination immediately after putting on these goggles is inaccurate. However, after performing a number of visuo-motor tasks wearing these goggles, coordination adapts and improves. Immediately after removing the goggles, a robust negative aftereffect resulting from adaptation to the goggles is consistently demonstrated. This negative aftereffect can be used to quantify the amount of adaptation that has taken place. We document how to create the prism goggles, how to quantify accuracy of motor coordination, what kinds of visuo-motor tasks consistently lead to significant adaptation, and the importance of active over passive adaptation conditions.
neural plasticity; sensory and motor systems; prism adaptation; negative aftereffects
In everyday life, humans interact with a dynamic environment often requiring rapid adaptation of visual perception and motor control. In particular, new visuo–motor mappings must be learned while old skills have to be kept, such that after adaptation, subjects may be able to quickly change between two different modes of generating movements (‘dual–adaptation’). A fundamental question is how the adaptation schedule determines the acquisition speed of new skills. Given a fixed number of movements in two different environments, will dual–adaptation be faster if switches (‘phase changes’) between the environments occur more frequently? We investigated the dynamics of dual–adaptation under different training schedules in a virtual pointing experiment. Surprisingly, we found that acquisition speed of dual visuo–motor mappings in a pointing task is largely independent of the number of phase changes. Next, we studied the neuronal mechanisms underlying this result and other key phenomena of dual–adaptation by relating model simulations to experimental data. We propose a simple and yet biologically plausible neural model consisting of a spatial mapping from an input layer to a pointing angle which is subjected to a global gain modulation. Adaptation is performed by reinforcement learning on the model parameters. Despite its simplicity, the model provides a unifying account for a broad range of experimental data: It quantitatively reproduced the learning rates in dual–adaptation experiments for both direct effect, i.e. adaptation to prisms, and aftereffect, i.e. behavior after removal of prisms, and their independence on the number of phase changes. Several other phenomena, e.g. initial pointing errors that are far smaller than the induced optical shift, were also captured. Moreover, the underlying mechanisms, a local adaptation of a spatial mapping and a global adaptation of a gain factor, explained asymmetric spatial transfer and generalization of prism adaptation, as observed in other experiments.
To investigate the functional integrity of cerebellar and frontal system in autism using oculomotor paradigms.
Cerebellar and neocortical systems models of autism have been proposed. Courchesne and colleagues have argued that cognitive deficits such as shifting attention disturbances result from dysfunction of vermal lobules VI and VII. Such a vermal deficit should be associated with dysmetric saccadic eye movements because of the major role these areas play in guiding the motor precision of saccades. In contrast, neocortical models of autism predict intact saccade metrics, but impairments on tasks requiring the higher cognitive control of saccades.
A total of 26 rigorously diagnosed nonmentally retarded autistic subjects and 26 matched healthy control subjects were assessed with a visually guided saccade task and two volitional saccade tasks, the oculomotor delayed-response task and the antisaccade task.
Metrics and dynamic of the visually guided saccades were normal in autistic subjects, documenting the absence of disturbances in cerebellar vermal lobules VI and VII and in automatic shifts of visual attention. Deficits were demonstrated on both volitional saccade tasks, indicating dysfunction in the circuitry of prefrontal cortex and its connections with the parietal cortex, and associated cognitive impairments in spatial working memory and in the ability to voluntarily suppress context-inappropriate responses.
These findings demonstrate intrinsic neocortical, not cerebellar, dysfunction in autism, and parallel deficits in higher order cognitive mechanisms and not in elementary attentional and sensorimotor systems in autism.
Children with autism spectrum disorder (ASD) show deficits in development of motor skills, in addition to core deficits in social skill development. In a previous study (Haswell et al., 2009) we found that children with autism show a key difference in how they learn motor actions, with a bias for relying on joint position rather than visual feedback; further, this pattern of motor learning predicted impaired motor, imitation and social abilities. We were interested in finding out whether this altered motor learning pattern was specific to autism. To do so, we examined children with Attention Deficit Hyperactivity Disorder (ADHD), who also show deficits in motor control. Children learned a novel movement and we measured rates of motor learning, generalization patterns of motor learning, and variability of motor speed during learning. We found children with ASD show a slower rate of learning and, consistent with previous findings, an altered pattern of generalization that was predictive of impaired motor, imitation, and social impairment. In contrast, children with ADHD showed a normal rate of learning and a normal pattern of generalization; instead, they (and they alone), showed excessive variability in movement speed. The findings suggest that there is a specific pattern of altered motor learning associated with autism.
The brain builds an association between action and sensory feedback to predict the sensory consequence of self-generated motor commands. This internal model of action is central to our ability to adapt movements, and may also play a role in our ability to learn from observing others. Recently we reported that the spatial generalization patterns that accompany adaptation of reaching movements were distinct in children with Autism Spectrum Disorder (ASD) as compared to typically developing (TD) children. To test whether the generalization patterns are specific to ASD, here we compared the patterns of adaptation to those in children with Attention Deficit Hyperactivity Disorder (ADHD). Consistent with our previous observations, we found that in ASD the motor memory showed greater than normal generalization in proprioceptive coordinates compared with both TD children and children with ADHD; children with ASD also showed slower rates of adaptation compared with both control groups. Children with ADHD did not show this excessive generalization to the proprioceptive target, but did show excessive variability in the speed of movements with an increase in the exponential distribution of responses (τ) as compared with both TD children and children with ASD. The results suggest that slower rate of adaptation and anomalous bias towards proprioceptive feedback during motor learning is characteristic of autism; whereas increased variability in execution is characteristic of ADHD.
The cerebellum is thought to mediate sensorimotor adaptation through the acquisition of internal models of the body-environment interaction. These representations can be of two types, identified as forward and inverse models. The first predicts the sensory consequences of actions, while the second provides the correct commands to achieve desired state transitions. In this paper, we propose a composite architecture consisting of multiple cerebellar internal models to account for the adaptation performance of humans during sensorimotor learning. The proposed model takes inspiration from the cerebellar microcomplex circuit, and employs spiking neurons to process information. We investigate the intrinsic properties of the cerebellar circuitry subserving efficient adaptation properties, and we assess the complementary contributions of internal representations by simulating our model in a procedural adaptation task. Our simulation results suggest that the coupling of internal models enhances learning performance significantly (compared with independent forward and inverse models), and it allows for the reproduction of human adaptation capabilities. Furthermore, we provide a computational explanation for the performance improvement observed after one night of sleep in a wide range of sensorimotor tasks. We predict that internal model coupling is a necessary condition for the offline consolidation of procedural memories.
cerebellar microcomplex; sensorimotor adaptation; inverse and forward internal models; procedural adaptation task; motor control
Offspring of rats exposed to valproic acid (VPA) on Gestational Day (GD) 12 have been advocated as a rodent model of autism because they show neuron loss in brainstem nuclei and the cerebellum resembling that seen in human autistic cases [20, 37]. Studies of autistic children have reported alterations in acquisition of classical eyeblink conditioning  and in reversal of instrumental discrimination learning . Acquisition of discriminative eyeblink conditioning depends on known brainstem-cerebellar circuitry whereas reversal depends on interactions of this circuitry with the hippocampus and prefrontal cortex. In order to explore behavioral parallels of the VPA rodent model with human autism, the present study exposed pregnant Long-Evans rats to 600 mg/kg VPA on GD12 [cf. 37] and tested their offspring from PND26-31 on discriminative eyeblink conditioning and reversal. VPA rats showed faster eyeblink conditioning, consistent with studies in autistic children . This suggests that previously reported parallels between human autism and the VPA rodent model with respect to injury to brainstem-cerebellar circuitry  are accompanied by behavioral parallels when a conditioning task engaging this circuitry is used. VPA rats also showed impaired reversal learning, but this likely reflected “carry-over” of enhanced conditioning during acquisition rather than a reversal learning deficit like that seen in human autism. Further studies of eyeblink conditioning in human autism and in various animal models may help to identify the etiology of this developmental disorder.
Eyeblink Conditioning; Gestational Valproate Exposure; Discrimination Reversal; Cerebellum; Hippocampus; Development
Humans skillfully manipulate objects and tools despite the inherent instability. In order to succeed at these tasks, the sensorimotor control system must build an internal representation of both the force and mechanical impedance. As it is not practical to either learn or store motor commands for every possible future action, the sensorimotor control system generalizes a control strategy for a range of movements based on learning performed over a set of movements. Here, we introduce a computational model for this learning and generalization, which specifies how to learn feedforward muscle activity in a function of the state space. Specifically, by incorporating co-activation as a function of error into the feedback command, we are able to derive an algorithm from a gradient descent minimization of motion error and effort, subject to maintaining a stability margin. This algorithm can be used to learn to coordinate any of a variety of motor primitives such as force fields, muscle synergies, physical models or artificial neural networks. This model for human learning and generalization is able to adapt to both stable and unstable dynamics, and provides a controller for generating efficient adaptive motor behavior in robots. Simulation results exhibit predictions consistent with all experiments on learning of novel dynamics requiring adaptation of force and impedance, and enable us to re-examine some of the previous interpretations of experiments on generalization.
Predictable sensorimotor perturbations can lead to cerebellum-dependent adaptation—i.e., recalibration of the relationship between sensory input and motor output. Here we asked if the cerebellum is also needed to recalibrate the relationship between two sensory modalities, vision and proprioception. We studied how people with and without cerebellar damage use visual and proprioceptive signals to estimate their hand’s position when the sensory estimates disagree. Theoretically, the brain may resolve the discrepancy by recalibrating the relationship between estimates (sensory realignment). Alternatively, the misalignment may be dealt with by relying less on one sensory estimate and more on the other (a weighting strategy). To address this question, we studied subjects with cerebellar damage and healthy controls as they performed a series of tasks. The first was a prism adaptation task that involves motor adaptation to compensate for a visual perturbation and is known to require the cerebellum. As expected, people with cerebellar damage were impaired relative to controls. The same subjects then performed two experiments in which they reached to visual and proprioceptive targets while a visuoproprioceptive misalignment was gradually imposed. Surprisingly, cerebellar patients performed as well as controls when the task invoked only sensory realignment, but were impaired relative to controls when motor adaptation was also possible. Additionally, individuals with cerebellar damage were able to use a weighting strategy similarly to controls. These results demonstrate that, unlike motor adaptation, sensory realignment and weighting are not cerebellum-dependent.
motor adaptation; sensory adaptation; sensorimotor integration; reaching; cerebellum
Spina bifida meningomyelocele (SBM), a congenital neurodevelopmental disorder, involves dysmorphology of the cerebellum, and its most obvious manifestations are motor deficits. This paper reviews cerebellar neuropathology and motor function across several motor systems well studied in SBM in relation to current models of cerebellar motor and timing function. Children and adults with SBM have widespread motor deficits in trunk, upper limbs, eyes, and speech articulators that are broadly congruent with those observed in adults with cerebellar lesions. The structure and function of the cerebellum are correlated with a range of motor functions. While motor learning is generally preserved in SBM, those motor functions requiring predictive signals and precise calibration of the temporal features of movement are impaired, resulting in deficits in smooth movement coordination as well as in the classical cerebellar triad of dysmetria, ataxia, and dysarthria. That motor function in individuals with SBM is disordered in a manner phenotypically similar to that in adult cerebellar lesions, and appears to involve similar deficits in predictive cerebellar motor control, suggests that age-based cerebellar motor plasticity is limited in individuals with this neurodevelopmental disorder.
Cerebellum; Motor function; Motor learning; Spina bifida; Chiari II
In every motor task, our brain must handle external forces acting on the body. For example, riding a bike on cobblestones or skating on irregular surface requires us to appropriately respond to external perturbations. In these situations, motor predictions cannot help anticipate the motion of the body induced by external factors, and direct use of delayed sensory feedback will tend to generate instability. Here, we show that to solve this problem the motor system uses a rapid sensory prediction to correct the estimated state of the limb. We used a postural task with mechanical perturbations to address whether sensory predictions were engaged in upper-limb corrective movements. Subjects altered their initial motor response in ∼60 ms, depending on the expected perturbation profile, suggesting the use of an internal model, or prior, in this corrective process. Further, we found trial-to-trial changes in corrective responses indicating a rapid update of these perturbation priors. We used a computational model based on Kalman filtering to show that the response modulation was compatible with a rapid correction of the estimated state engaged in the feedback response. Such a process may allow us to handle external disturbances encountered in virtually every physical activity, which is likely an important feature of skilled motor behaviour.
It is commonly assumed that the brain uses internal estimates of the state of the body to adjust motor commands and perform successful movements. A problem arises when external disturbances deviate the limb from the ongoing task. In such cases, the estimated state of the body must be corrected based on sensory feedback. Because neural transmission delays can destabilize feedback control, an important challenge for motor systems is to correct the estimated state as quickly as possible. In this paper, we tested whether such a rapid correction is performed following mechanical loads applied to the upper limb. Our results indicate that long latency responses (∼50–100 ms) exhibit knowledge of the relationship between the delayed sensed joint displacement and the current state of the limb at the onset of the motor response. Importantly, this knowledge can be adjusted from one perturbation response to the next, should a distinct perturbation profile be experienced. These results suggest that a correction of state estimation is performed within the limb rapid-feedback pathways, allowing fast and stable feedback control.
In this paper we discuss a new perspective on how the central nervous system (CNS) represents and solves some of the most fundamental computational problems of motor control. In particular, we consider the task of transforming a planned limb movement into an adequate set of motor commands. To carry out this task the CNS must solve a complex inverse dynamic problem. This problem involves the transformation from a desired motion to the forces that are needed to drive the limb. The inverse dynamic problem is a hard computational challenge because of the need to coordinate multiple limb segments and because of the continuous changes in the mechanical properties of the limbs and of the environment with which they come in contact. A number of studies of motor learning have provided support for the idea that the CNS creates, updates and exploits internal representations of limb dynamics in order to deal with the complexity of inverse dynamics. Here we discuss how such internal representations are likely to be built by combining the modular primitives in the spinal cord as well as other building blocks found in higher brain structures. Experimental studies on spinalized frogs and rats have led to the conclusion that the premotor circuits within the spinal cord are organized into a set of discrete modules. Each module, when activated, induces a specific force field and the simultaneous activation of multiple modules leads to the vectorial combination of the corresponding fields. We regard these force fields as computational primitives that are used by the CNS for generating a rich grammar of motor behaviours.
The cerebellum has a well-established role in maintaining motor coordination and studies of cerebellar learning suggest that it does this by recognizing neural patterns, which it uses to predict optimal movements. Serious damage to the cerebellum impairs this learning and results in a set of motor disturbances called ataxia. However, recent work implicates the cerebellum in cognition and emotion, and it has been argued that cerebellar dysfunction contributes to non-motor conditions such as autism spectrum disorders (ASD). Based on human and animal model studies, two major questions arise. Does the cerebellum contribute to non-motor as well as motor diseases, and if so, how does altering its function contribute to such diverse symptoms? The architecture and connectivity of cerebellar circuits may hold the answers to these questions. An emerging view is that cerebellar defects can trigger motor and non-motor neurological conditions by globally influencing brain function. Furthermore, during development cerebellar circuits may play a role in wiring events necessary for higher cognitive functions such as social behavior and language. We discuss genetic, electrophysiological, and behavioral evidence that implicates Purkinje cell dysfunction as a major culprit in several diseases and offer a hypothesis as to how canonical cerebellar functions might be at fault in non-motor as well as motor diseases.
neurological disorders; genetics; circuitry; neural activity; brain behavior
Although autistic people have shown impairments in various learning and memory tasks, recent studies have reported mixed findings concerning implicit learning in ASD. Implicit skill learning, with its unconscious and statistical properties, underlies not only motor but also cognitive and social skills, and it therefore plays an important role from infancy to old age.
We investigated probabilistic implicit sequence learning and its consolidation in Autism Spectrum Disorder (ASD). Three groups of children participated: thirteen with high-functioning ASD, 14 age-matched controls, and 13 IQ-matched controls. All were tested on the Alternating Serial Reaction Time Task (ASRT), making it possible to separate general skill learning from sequence-specific learning. The ASRT task was repeated after 16 hours. We found that control and ASD children showed similar sequence-specific and general skill learning in the learning phase. Consolidation of skill learning and sequence-specific learning were also intact in the ASD compared to the control groups.
These results suggest that autistic children can use the effects/results of implicit learning not only for a short period, but also for a longer stretch of time. Using these findings, therapists can design more effective educational and rehabilitation programs.
Gender differences have been shown across many domains, and motor skills are no exception. One of the most robust findings is a significant sex difference in throwing accuracy, which reflects the advantage of men in targeting abilities. However, little is known about the basis of this difference. To try to dissect possible mechanisms involved in this difference, here we tested for gender variations in a prism adaptation throwing task. We tested 154 subjects in a visuomotor prism adaptation task that discriminates between motor performance, visuomotor adaptation and negative aftereffects. Our results corroborate men's significant better throwing accuracy, although there were no adaptation differences between genders. In contrast, women showed significant larger negative aftereffects, which could be explained by a larger contribution of spatial alignment. These results suggest that different learning mechanisms, like strategic calibration and spatial alignment, may have different contributions in men and women.
Prism adaptation improves a wide range of manifestations of left spatial neglect in right-brain-damaged patients. The typical paradigm consists in repeated pointing movements to visual targets, while patients wear prism goggles that displace the visual scene rightwards. Recently, we demonstrated the efficacy of a novel adaptation procedure, involving a variety of every-day visuo-motor activities. This “ecological” procedure proved to be as effective as the repetitive pointing adaptation task in ameliorating symptoms of spatial neglect, and was better tolerated by patients. However, the absence of adaptation and aftereffects measures for the ecological treatment did not allow for a full comparison of the two procedures. This is important in the light of recent findings showing that the magnitude of prism-induced aftereffects may predict recovery from spatial neglect. Here, we investigated prism-induced adaptation and aftereffects after ecological and pointing adaptation procedures. Forty-eight neurologically healthy participants (young and aged groups) were exposed to rightward shifting prisms while they performed the ecological or the pointing procedures, in separate days. Before and after prism exposure, participants performed proprioceptive, visual, and visual-proprioceptive tasks to assess prism-induced aftereffects. Participants adapted to the prisms during both procedures. Importantly, the ecological procedure induced greater aftereffects in the proprioceptive task (for both the young and the aged groups) and in the visual-proprioceptive task (young group). A similar trend was found for the visual task in both groups. Finally, participants rated the ecological procedure as more pleasant, less monotonous, and more sustainable than the pointing procedure. These results qualify ecological visuo-motor activities as an effective prism-adaptation procedure, suitable for the rehabilitation of spatial neglect.
prism adaptation; aftereffects; spatial neglect; right brain damage; rehabilitation; ecological; pointing
The Ts65Dn mouse is partly trisomic at chromosome 16 and is considered to be a valid mouse model of human Down syndrome. Prior research using an incremental repeated acquisition (IRA) schedule of reinforcement has revealed that there is a significant learning deficit in young, adult Ts65Dn mice compared to littermate controls. The purpose of this study was to examine whether this deficit changes during the life-span of these mice. In order to determine if changes in the deficit were caused by motoric or motivational deficiencies, a second group of mice was trained to respond under a performance version of the task (IRA-P). The IRA-P task required the same motor responses to produce the reinforcer, but no learning or acquisition was required. Data collected under the IRA task demonstrated that there was a significant learning impairment that persisted up to 24-months of age in the Ts65Dn mice compared to littermate controls. There was a significant decrease in the rate of responding and the number of milk presentations earned by the Ts65Dn mice after 19-months of age. However, during this time, response accuracy, which is independent of mobility and possibly motivation, did not decrease. Under the IRA-P schedule, there was no decrease observed in the number of milk presentations of either line as they aged, but the trend in the rate of responding of the Ts65Dn mice was similarly declining as the rate of responding observed in the Ts65Dn mice under the IRA task. These data indicate that the ability to learn in Ts65Dn mice does not decline with age as measured by the IRA task and suggests that perhaps Ts65Dn mice do not exhibit the same early-onset Alzheimer’s disease phenotype that is typically seen in human patients.
Control of our movements is apparently facilitated by an adaptive internal model in the cerebellum. It was long thought that this internal model implemented an adaptive inverse model and generated motor commands, but recently many reject that idea in favor of a forward model hypothesis. In theory, the forward model predicts upcoming state during reaching movements so the motor cortex can generate appropriate motor commands. Recent computational models of this process rely on the optimal feedback control (OFC) framework of control theory. OFC is a powerful tool for describing motor control, it does not describe adaptation. Some assume that adaptation of the forward model alone could explain motor adaptation, but this is widely understood to be overly simplistic. However, an adaptive optimal controller is difficult to implement. A reasonable alternative is to allow forward model adaptation to ‘re-tune’ the controller. Our simulations show that, as expected, forward model adaptation alone does not produce optimal trajectories during reaching movements perturbed by force fields. However, they also show that re-optimizing the controller from the forward model can be sub-optimal. This is because, in a system with state correlations or redundancies, accurate prediction requires different information than optimal control. We find that adding noise to the movements that matches noise found in human data is enough to overcome this problem. However, since the state space for control of real movements is far more complex than in our simple simulations, the effects of correlations on re-adaptation of the controller from the forward model cannot be overlooked.
Electronic supplementary material
The online version of this article (doi:10.1007/s10827-011-0350-z) contains supplementary material, which is available to authorized users.
Optimal control; Motor adaptation; Forward model; Reaching movements
Computational theory of motor control suggests that the brain continuously monitors motor commands, to predict their sensory consequences before actual sensory feedback becomes available. Such prediction error is a driving force of motor learning, and therefore appropriate associations between motor commands and delayed sensory feedback signals are crucial. Indeed, artificially introduced delays in visual feedback have been reported to degrade motor learning. However, considering our perceptual ability to causally bind our own actions with sensory feedback, demonstrated by the decrease in the perceived time delay following repeated exposure to an artificial delay, we hypothesized that such perceptual binding might alleviate deficits of motor learning associated with delayed visual feedback. Here, we evaluated this hypothesis by investigating the ability of human participants to adapt their reaching movements in response to a novel visuomotor environment with 3 visual feedback conditions—no-delay, sudden-delay, and adapted-delay. To introduce novelty into the trials, the cursor position, which originally indicated the hand position in baseline trials, was rotated around the starting position. In contrast to the no-delay condition, a 200-ms delay was artificially introduced between the cursor and hand positions during the presence of visual rotation (sudden-delay condition), or before the application of visual rotation (adapted-delay condition). We compared the learning rate (representing how the movement error modifies the movement direction in the subsequent trial) between the 3 conditions. In comparison with the no-delay condition, the learning rate was significantly degraded for the sudden-delay condition. However, this degradation was significantly alleviated by prior exposure to the delay (adapted-delay condition). Our data indicate the importance of appropriate temporal associations between motor commands and sensory feedback in visuomotor learning. Moreover, they suggest that the brain is able to account for such temporal associations in a flexible manner.
Adaptive control of reaching depends on internal models that associate states in which the limb experienced a force perturbation with motor commands that can compensate for it. Limb state can be sensed via both vision and proprioception. However, adaptation of reaching in novel dynamics results in generalization in the intrinsic coordinates of the limb, suggesting that the proprioceptive states in which the limb was perturbed dominate representation of limb state. To test this hypothesis, we considered a task where position of the hand during a reach was correlated with patterns of force perturbation. This correlation could be sensed via vision, proprioception, or both. As predicted, when the correlations could be sensed only via proprioception, learning was significantly better as compared to when the correlations could only be sensed through vision. We found that learning with visual correlations resulted in subjects who could verbally describe the patterns of perturbations but this awareness was never observed in subjects who learned the task with only proprioceptive correlations. We manipulated the relative values of the visual and proprioceptive parameters and found that the probability of becoming aware strongly depended on the correlations that subjects could visually observe. In all conditions, aware subjects demonstrated a small but significant advantage in their ability to adapt their motor commands. Proprioceptive correlations produced an internal model that strongly influenced reaching performance yet did not lead to awareness. Visual correlations strongly increased the probability of becoming aware, yet had a much smaller but still significant effect on reaching performance. Therefore, practice resulted in acquisition of both implicit and explicit internal models.
reaching; arm movements; awareness; adaptation; force fields; vision; proprioception; computational models; motor control; motor learning
When learning to perform a novel sensorimotor task, humans integrate multi-modal sensory feedback such as vision and proprioception in order to make the appropriate adjustments to successfully complete the task. Sensory feedback is used both during movement to control and correct the current movement, and to update the feed-forward motor command for subsequent movements. Previous work has shown that adaptation to stable dynamics is possible without visual feedback. However, it is not clear to what degree visual information during movement contributes to this learning or whether it is essential to the development of an internal model or impedance controller.
We examined the effects of the removal of visual feedback during movement on the learning of both stable and unstable dynamics in comparison with the case when both vision and proprioception are available. Subjects were able to learn to make smooth movements in both types of novel dynamics after learning with or without visual feedback. By examining the endpoint stiffness and force after learning it could be shown that subjects adapted to both types of dynamics in the same way whether they were provided with visual feedback of their trajectory or not. The main effects of visual feedback were to increase the success rate of movements, slightly straighten the path, and significantly reduce variability near the end of the movement.
These findings suggest that visual feedback of the hand during movement is not necessary for the adaptation to either stable or unstable novel dynamics. Instead vision appears to be used to fine-tune corrections of hand trajectory at the end of reaching movements.