Sensory prediction error drives subconscious motor learning outside of the laboratory.

Sensorimotor adaptation is supported by at least two parallel learning systems: an intentionally controlled explicit strategy and an involuntary implicit learning system. Past work focused on constrained reaches or finger movements in laboratory environments has shown subconscious learning systems to be driven in part by sensory prediction error (SPE), i.e., the mismatch between the realized and expected outcome of an action. We designed a ball rolling task to explore whether SPEs can drive implicit motor adaptation during complex whole body movements that impart physical motion on external objects. After applying a visual shift, participants rapidly adapted their rolling angles to reduce the error between the ball and the target. We removed all visual feedback and told participants to aim their throw directly toward the primary target, revealing an unintentional 5.06° implicit adjustment to reach angles that decayed over time. To determine whether this implicit adaptation was driven by SPE, we gave participants a second aiming target that would "solve" the visual shift, as in the study by Mazzoni and Krakauer (Mazzoni P, Krakauer JW. J Neurosci 26: 3642-3645, 2006). Remarkably, after rapidly reducing ball-rolling error to zero (due to enhancements in strategic aiming), the additional aiming target caused rolling angles to deviate beyond the primary target by 3.15°. This involuntary overcompensation, which worsened task performance, is a hallmark of SPE-driven implicit learning. These results show that SPE-driven implicit processes, previously observed within simplified finger or planar reaching movements, actively contribute to motor adaptation in more complex naturalistic skill-based tasks.NEW & NOTEWORTHY Implicit and explicit learning systems have been detected using simple, constrained movements inside the laboratory. How these systems impact movements during complex whole body, skill-based tasks has not been established. Here, we demonstrate that sensory prediction errors significantly impact how a person updates their movements, replicating findings from the laboratory in an unconstrained ball-rolling task. This real-world validation is an important step toward explaining how subconscious learning helps humans execute common motor skills in dynamic environments.

An analytical method reduces noise bias in motor adaptation analysis.

When a person makes a movement, a motor error is typically observed that then drives motor planning corrections on subsequent movements. This error correction, quantified as a trial-by-trial adaptation rate, provides insight into how the nervous system is operating, particularly regarding how much confidence a person places in different sources of information such as sensory feedback or motor command reproducibility. Traditional analysis has required carefully controlled laboratory conditions such as the application of perturbations or error clamping, limiting the usefulness of motor analysis in clinical and everyday environments. Here we focus on error adaptation during unperturbed and naturalistic movements. With increasing motor noise, we show that the conventional estimation of trial-by-trial adaptation increases, a counterintuitive finding that is the consequence of systematic bias in the estimate due to noise masking the learner's intention. We present an analytic solution relying on stochastic signal processing to reduce this effect of noise, producing an estimate of motor adaptation with reduced bias. The result is an improved estimate of trial-by-trial adaptation in a human learner compared to conventional methods. We demonstrate the effectiveness of the new method in analyzing simulated and empirical movement data under different noise conditions.

Validation of a constrained-time movement task for use in rehabilitation outcome measures.

Current motor assessment tools can provide numerical indicators of performance but do not provide actionable information to target further improvement in rehabilitation interventions. Psychophysics-based outcome measures show promise to provide more useful information in the laboratory environment but have been limited in clinical implementation. Here we present a constrained-time task to assess paced and non-rhythmic movements. The task's output metrics include trial-by-trial adaptation rate and the just noticeable difference of a perturbation. We show that the task's metrics are reliable (i.e. high test-retest reliability) and are responsive to changes in feedback type and experience. We also discuss the task's versatility to be used for other types of movements including grasping. The consistent, sensitive and flexible time-constrained movement task we present provides a foundation from which to develop advanced outcome measures for prosthesis users and for other rehabilitation contexts.

A third arm - Design of a bypass prosthesis enabling incorporation.

A variety of factors affect the performance of a person using a myoelectric prosthesis, including increased control noise, reduced sensory feedback, and muscle fatigue. Many studies use able-bodied subjects to control a myoelectric prosthesis using a bypass socket in order to make comparisons to movements made with intact limbs. Depending on the goals of the study, this approach can also allow for greater subject numbers and more statistical power in the analysis of the results. As we develop assessment tools and techniques to evaluate how peripheral nerve interfaces impact prosthesis incorporation, involving normally limbed subjects in the studies becomes challenging. We have designed a novel bypass prosthesis to allow for the assessment of prosthesis incorporation in able-bodied subjects. Incorporation of a prosthetic hand worn by a normally limbed subject requires that the prosthesis is a convincing, functional extension of their own body. We present the design and development of the bypass prosthesis with special attention to mounting position and angle of the prosthetic hand, the quality of the control system and the responsiveness of the feedback. The bypass prosthesis has been fitted with a myoelectrically-controlled hand that has been instrumented to measure the forces applied to the thumb, index, and middle fingers. The prosthetic hand was mounted on the bypass socket such that it is the same length as the subject's intact limb but at a medial rotation angle of 20° to prevent visual occlusion of the prosthetic hand. Force feedback is provided in the form of electrical stimulation, vibration, or force applied to the intact limb with milliseconds of delay. Preliminary data results from a cross-modal congruency task are included showing evidence of prosthesis incorporation in able-bodied subjects. This bypass will allow able-bodied subjects to participate in research studies that require the use of a prosthetic limb while also allowing the subjects to sense that the prosthesis is an extension of the body.