Proprioceptive Re-alignment drives Implicit Sensorimotor Adaptation

Multiple learning processes contribute to successful goal-directed actions in the face of changing physiological states, biomechanical constraints, and environmental contexts. Amongst these processes, implicit sensorimotor adaptation is of primary importance, ensuring that movements remain well-calibrated and accurate. A large body of work on reaching movements has emphasized how adaptation centers on an iterative process designed to minimize visual errors. The role of proprioception has been largely neglected, thought to play a passive role in which proprioception is affected by the visual error but does not directly contribute to adaptation. Here we present an alternative to this visuo-centric framework, arguing that that implicit adaptation can be understood as minimizing a proprioceptive error, the distance between the perceived hand position and its intended goal. We use this proprioceptive re-alignment model (PReMo) to re-examine many phenomena that have previously been interpreted in terms of learning from visual errors, as well as offer novel accounts for unexplained phenomena. We discuss potential challenges for this new perspective on implicit adaptation and outline a set of predictions for future experimentation.

Individual Differences in Sensorimotor Adaptation Are Conserved Over Time and Across Force-Field Tasks

Sensorimotor adaptation enables the nervous system to modify actions for different conditions and environments. Many studies have investigated factors that influence adaptation at the group level. There is growing recognition that individuals vary in their ability to adapt motor skills and that a better understanding of individual differences in adaptation may inform how motor skills are taught and rehabilitated. Here we examined individual differences in the adaptation of upper-limb reaching movements. We quantified the extent to which participants adapted their movements to a velocity-dependent force field during an initial session, at 24 h, and again 1-week later. Participants (n = 28) displayed savings, which was expressed as greater initial adaptation when re-exposed to the force field. Individual differences in adaptation across various stages of the experiment displayed weak-strong reliability, such that individuals who adapted to a greater extent in the initial session tended to do so when re-exposed to the force field. Our second experiment investigated if individual differences in adaptation are also present when participants adapt to different force fields or a force field and visuomotor rotation. Separate groups of participants adapted to position- and velocity-dependent force fields (Experiment 2a; n = 20) or a velocity-dependent force field and visuomotor rotation in a single session (Experiment 2b; n = 20). Participants who adapted to a greater extent to velocity-dependent forces tended to show a greater extent of adaptation when exposed to position-dependent forces. In contrast, correlations were weak between various stages of adaptation to the force-field and visuomotor rotation. Collectively, our study reveals individual differences in adaptation that are reliable across repeated exposure to the same force field and present when adapting to different force fields.

Impaired Sensorimotor Adaption in Schizophrenia in Comparison to Age-Matched and Elderly Controls

<b><i>Background:</i></b> The “cognitive dysmetria hypothesis” of schizophrenia proposes a disrupted communication between the cerebellum and cerebral cortex, resulting in sensorimotor and cognitive symptoms. Sensorimotor adaptation relies strongly on the function of the cerebellum. <b><i>Objectives:</i></b> This study investigated whether sensorimotor adaptation is reduced in schizophrenia compared with age-matched and elderly healthy controls. <b><i>Methods:</i></b> Twenty-nine stably treated patients with schizophrenia, 30 age-matched, and 30 elderly controls were tested in three motor adaptation tasks in which visual movement feedback was unexpectedly altered. In the “rotation adaptation task” the perturbation consisted of a rotation (30° clockwise), in the “gain adaptation task” the extent of the movement feedback was reduced (by a factor of 0.7) and in the “vertical reversal task,” up- and downward pen movements were reversed by 180°. <b><i>Results:</i></b> Patients with schizophrenia adapted to the perturbations, but their movement times and errors were substantially larger than controls. Unexpectedly, the magnitude of adaptation was significantly smaller in schizophrenia than elderly participants. The impairment already occurred during the first adaptation trials, pointing to a decline in explicit strategy use. Additionally, post-adaptation aftereffects provided strong evidence for impaired implicit adaptation learning. Both negative and positive schizophrenia symptom severities were correlated with indices of the amount of adaptation and its aftereffects. <b><i>Conclusions:</i></b> Both explicit and implicit components of sensorimotor adaptation learning were reduced in patients with schizophrenia, adding to the evidence for a role of the cerebellum in the pathophysiology of schizophrenia. Elderly individuals outperformed schizophrenia patients in the adaptation learning tasks.

The cost of correcting for error during sensorimotor adaptation

Learning from error is often a slow process. In machine learning, the learning rate depends on a loss function that specifies a cost for error. Here, we hypothesized that during motor learning, error carries an implicit cost for the brain because the act of correcting for error consumes time and energy. Thus, if this implicit cost could be increased, it may robustly alter how the brain learns from error. To vary the implicit cost of error, we designed a task that combined saccade adaptation with motion discrimination: movement errors resulted in corrective saccades, but those corrections took time away from acquiring information in the discrimination task. We then modulated error cost using coherence of the discrimination task and found that when error cost was large, pupil diameter increased and the brain learned more from error. However, when error cost was small, the pupil constricted and the brain learned less from the same error. Thus, during sensorimotor adaptation, the act of correcting for error carries an implicit cost for the brain. Modulating this cost affects how much the brain learns from error.

The acute effects of aerobic exercise on sensorimotor adaptation in chronic stroke

Background: Sensorimotor adaptation, or the capacity to adapt movement to changes in the moving body or environment, is a form of motor learning that is important for functional independence (e.g., regaining stability after slips or trips). Aerobic exercise can acutely improve many forms of motor learning in healthy adults. It is not known, however, whether acute aerobic exercise has similar positive effects on sensorimotor adaptation in stroke survivors as it does in healthy individuals. Objective: The aim of this study was to determine whether acute aerobic exercise promotes sensorimotor adaptation in people post stroke. Methods: A single-blinded crossover study. Participants attended two separate sessions, completing an aerobic exercise intervention in one session and a resting control condition in the other session. Sensorimotor adaptation was assessed before and after each session, as was brain derived neurotrophic factor. Twenty participants with chronic stroke completed treadmill exercise at mod-high intensity for 30 minutes. Results: Acute aerobic exercise in chronic stroke survivors significantly increased sensorimotor adaptation from pre to post treadmill intervention. The 30-minute treadmill intervention resulted in an averaged 2.99 ng/ml increase in BDNF levels (BDNF pre-treadmill = 22.31 + /–2.85 ng/ml, post-treadmill was = 25.31 + /–2.46 pg/ml; t(16) = 2.146, p = 0.048, cohen’s d = 0.521, moderate effect size). Conclusions: These results indicate a potential role for aerobic exercise to promote the recovery of sensorimotor function in chronic stroke survivors.

Does proprioceptive acuity influence the extent of implicit sensorimotor adaptation in young and older adults?

The ability to adjust movements to changes in the environment declines with aging. This age-related decline is caused by the decline of explicit adjustments. However, implicit adaptation remains intact and might even be increased with aging. Since proprioceptive information has been linked to implicit adaptation, it might well be that an age-related decline in proprioceptive acuity might be linked to the performance of older adults in implicit adaptation tasks. Indeed, age-related proprioceptive deficits could lead to altered sensory integration with an increased weighting of the visual sensory-prediction error. Another possibility is that reduced proprioceptive acuity results in an increased reliance on predicted sensory consequences of the movement. Both these explanations led to our preregistered hypothesis: we expected a relation between the decline of proprioception and the amount of implicit adaptation across ages. However, we failed to support this hypothesis. Our results question the existence of reliability-based integration of visual and proprioceptive signals during motor adaptation.

A single exposure to altered auditory feedback causes observable sensorimotor adaptation in speech

Sensory errors caused by perturbations to movement-related feedback induce two types of behavioral changes that oppose the perturbation: rapid compensation within a movement, as well as longer-term adaptation of subsequent movements. Although adaptation is hypothesized to occur whenever a sensory error is perceived (including after a single exposure to altered feedback), adaptation of articulatory movements in speech has only been observed after repetitive exposure to auditory perturbations, questioning both current theories of speech sensorimotor adaptation as well as the universality of more general theories of adaptation. Thus, positive evidence for the hypothesized single-exposure or 'one-shot' learning would provide critical support for current theories of speech sensorimotor learning and control and align adaptation in speech more closely with other motor domains. We measured one-shot learning in a large dataset in which participants were exposed to intermittent, unpredictable auditory perturbations to their vowel formants (the resonant frequencies of the vocal tract that distinguish between different vowels). On each trial, participants spoke a word out loud while their first formant was shifted up, shifted down, or remained unshifted. We examined whether the perturbation on a given trial affected speech on the subsequent, unperturbed trial. We found that participants adjusted their first formant in the opposite direction of the preceding shift, demonstrating that learning occurs even after a single auditory perturbation as predicted by current theories of sensorimotor adaptation. While adaptation and the preceding compensation responses were correlated, this was largely due to differences across individuals rather than within-participant variation from trial to trial. These findings are more consistent with theories that hypothesize adaptation is driven directly by updates to internal control models than those that suggest adaptation results from incorporation of feedback responses from previous productions.

Reproducing Human Motor Adaptation in Spiking Neural Simulation and known Synaptic Learning Rules

Sensorimotor adaptation enables us to adjust our goal-oriented movements in response to external perturbations. These phenomena have been studied experimentally and computationally at the level of human and animals reaching movements, and have clear links to the cerebellum as evidenced by cerebellar lesions and neurodegeneration. Yet, despite our macroscopic understanding of the high-level computational mechanisms it is unclear how these are mapped and are implemented in the neural substrates of the cerebellum at a cellular-computational level. We present here a novel spiking neural circuit model of the sensorimotor system including a cerebellum which control physiological muscle models to reproduce behaviour experiments. Our cerebellar model is composed of spiking neuron populations reflecting cells in the cerebellar cortex and deep cerebellar nuclei, which generate motor correction to change behaviour in response to perturbations. The model proposes two learning mechanisms for adaptation: predictive learning and memory formation, which are implemented with synaptic updating rules. Our model is tested in a force-field sensorimotor adaptation task and successfully reproduce several phenomena arising from human adaptation, including well-known learning curves, aftereffects, savings and other multi-rate learning effects. This reveals the capability of our model to learn from perturbations and generate motor corrections while providing a bottom-up view for the neural basis of adaptation. Thus, it also shows the potential to predict how patients with specific types of cerebellar damage will perform in behavioural experiments. We explore this by in silico experiments where we selectively incapacitate selected cerebellar circuits of the model which generate and reproduce defined motor learning deficits.