Mechanisms of Human Motor Learning Do Not Function Independently

Human motor learning is governed by a suite of interacting mechanisms each one of which modifies behavior in distinct ways and rely on different neural circuits. In recent years, much attention has been given to one type of motor learning, called motor adaptation. Here, the field has generally focused on the interactions of three mechanisms: sensory prediction error SPE-driven, explicit (strategy-based), and reinforcement learning. Studies of these mechanisms have largely treated them as modular, aiming to model how the outputs of each are combined in the production of overt behavior. However, when examined closely the results of some studies also suggest the existence of additional interactions between the sub-components of each learning mechanism. In this perspective, we propose that these sub-component interactions represent a critical means through which different motor learning mechanisms are combined to produce movement; understanding such interactions is critical to advancing our knowledge of how humans learn new behaviors. We review current literature studying interactions between SPE-driven, explicit, and reinforcement mechanisms of motor learning. We then present evidence of sub-component interactions between SPE-driven and reinforcement learning as well as between SPE-driven and explicit learning from studies of people with cerebellar degeneration. Finally, we discuss the implications of interactions between learning mechanism sub-components for future research in human motor learning.

Predication-Error-Based Intrinsically Motivated Saccade Learning

The quick, simultaneous movements of both eyes in the same direction is called a saccade, and the process of developing an internal model for the eyes’ movement-control based on visual stimuli is called saccade learning. All humans use this type of eye motion to bring salient objects to the foveal locations of the retina, even if the objects are located randomly in the surrounding environment. To begin with, infants are not able to perform this type of eye motion, but sensory information motivates them to start learning saccadic behavior. In this paper, a sensory prediction-error-based intrinsically motivated model is proposed for learning saccadic eye movements, and this approach is more consistent with biological systems for saccade learning. Predicted Coding/Biased Competition using Divisive Input Modulation (PC/BC-DIM) network is used for saccade learning using sensory prediction errors. The quantification of sensory prediction errors provides an intrinsic reward. A simulated humanoid agent, iCub, is used to assess and quantify the performance of the proposed model. The performance metrics used for this purpose are percentage mean post-saccadic distance and standard deviation. The mean post-saccadic distance for the proposed model was less than 1°, which is biologically plausible.

Pupil Drift Rate Indexes Groove Ratings

Groove, understood as a pleasurable compulsion to move to musical rhythms, typically varies along an inverted U-curve with increasing rhythmic complexity (e.g., syncopation, pickups). Predictive coding accounts posit that moderate complexity drives us to move to reduce sensory prediction errors and model the temporal structure. While musicologists generally distinguish the effects of pickups (anacruses) and syncopations, their difference remains unexplored in groove. We used pupillometry as an index to noradrenergic arousal while subjects listened to and rated drumbeats varying in rhythmic complexity. We replicated the inverted U-shaped relationship between rhythmic complexity and groove and showed this is modulated by musical ability, based on a psychoacoustic beat perception test. The pupil drift rates suggest that groovier rhythms hold attention longer than ones rated less groovy. Moreover, we found complementary effects of syncopations and pickups on groove ratings and pupil size, respectively, discovering a distinct predictive process related to pickups. We suggest that the brain deploys attention to pickups to sharpen subsequent strong beats, augmenting the predictive scaffolding’s focus on beats that reduce syncopations’ prediction errors. This interpretation is in accordance with groove envisioned as an embodied resolution of precision-weighted prediction error.

Sensory prediction errors increase coding efficiency in mouse visual cortex through gain amplification

The efficiency of sensory coding is affected both by past events (adaptation) and by expectation of future events (prediction). Here we employed a novel visual stimulus paradigm to determine whether expectation influences orientation selectivity in the primary visual cortex. We used two-photon calcium imaging (GCaMP6f) in awake mice viewing visual stimuli with different levels of predictability. The stimuli consisted of sequences of grating stimuli that randomly shifted in orientation or systematically rotated with occasionally unexpected rotations. At the single neuron and population level, there was significantly enhanced orientation-selective response to unexpected visual stimuli through a boost in gain, which was prominent in awake mice but also present to a lesser extent under anesthesia. We implemented a computational model to demonstrate how neuronal responses were best characterized when adaptation and expectation parameters were combined. Our results demonstrated that adaptation and prediction have unique signatures on activity of V1 neurons.

Sensory prediction errors increase coding efficiency in mouse visual cortex through gain amplification

The efficiency of sensory coding is affected both by past events (adaptation) and by expectation of future events (prediction). Here we employed a novel visual stimulus paradigm to determine whether expectation influences orientation selectivity in the primary visual cortex. We used two-photon calcium imaging (GCaMP6f) in awake mice viewing visual stimuli with different levels of predictability. The stimuli consisted of sequences of grating stimuli that randomly shifted in orientation or systematically rotated with occasionally unexpected rotations. At the single neuron and population level, there was significantly enhanced orientation-selective response to unexpected visual stimuli through a boost in gain, which was prominent in awake mice but also present to a lesser extent under anesthesia. We implemented a computational model to demonstrate how neuronal responses were best characterized when adaptation and expectation parameters were combined. Our results demonstrated that adaptation and prediction have unique signatures on activity of V1 neurons.

Drifting pitch awareness after exposure to altered auditory feedback

Various studies have claimed that the sense of agency is based on a comparison between an internal estimate of an action’s outcome and sensory feedback. With respect to speech, this presumes that speakers have a stable pre-articulatory representation of their own speech. However, recent research suggests that the sense of agency is flexible and thus in some contexts we may feel like we produced speech that was not actually produced by us. The current study tested whether the estimated pitch of one’s articulation (termed ‘pitch awareness’) is affected by manipulated auditory feedback. In four experiments, fifty-six participants produced isolated vowels while being exposed to pitch-shifted auditory feedback. After every vocalization, participants indicated whether they thought the feedback was higher or lower than their actual production. After exposure to a block of high-pitched auditory feedback (+500 cents pitch shift), participants were more likely to label subsequent auditory feedback as “lower than my actual production”, suggesting that prolonged exposure to high-pitched auditory feedback led to a drift in participants’ pitch awareness. The opposite pattern was found after exposure to a constant -500 cents pitch shift. This suggests that pitch awareness is not solely based on a pre-articulatory representation of intended speech or on a sensory prediction, but also on sensory feedback. We propose that this drift in pitch awareness could be indicative of a sense of agency over the pitch-shifted auditory feedback in the exposure block. If so, this suggests that the sense of agency over vocal output is flexible.

Autistic-like traits and Positive Schizotypy as Diametric Specializations of the Predictive Mind

The predictive processing (PP) framework suggests that the mind works by making and testing predictions. According to PP, only prediction errors (rather than all sensory inputs) are processed by an organism’s perceptual system. Prediction errors can be weighted such that some errors (usually those deemed more reliable) will be more influential in updating prior beliefs. It has recently been argued that autism spectrum disorders (ASD) result from an underlying predictive processing mechanism. The weight given to sensory prediction errors is thought to be inflexibly high in ASD, meaning that the perceptual system utilizes even relatively small prediction errors to update prior beliefs. Deficits in executive functioning, theory of mind, and central coherence are all argued to flow naturally from this core underlying mechanism. The diametric model of autism and psychosis suggests that these disorders result from opposite cognitive tendencies. Building on the diametric model, others have argued that autistic-like traits and positive schizotypy represent diametric cognitive-perceptual and behavioral traits that exist on a continuum in normal, non-clinical populations. In this paper I argue that positive schizotypy (which consists of magical thinking, unusual experiences, and ideas of reference) can be explained by the opposite mechanism to that of autism, namely an inflexibly low weight given to sensory prediction errors. This mechanism can potentially explain such disparate features of positive schizotypy as increased exploratory behavior, hyper-theory of mind, attentional differences, idiosyncratic worldviews, and a hyper-active imagination.

Sound omission related brain responses in children

Action is an important way for children to learn about the world. Recent theories suggest that action is inherently accompanied by the sensory prediction of its effects. Such predictions can be revealed by rarely omitting the expected sensory consequence of the action, resulting in an omission response that is observable in the EEG. Although prediction errors play an important role in models of learning and development, little is known about omission-related brain responses in children.This study used a motor-auditory omission paradigm, testing a group of 6–8-year-old children and an adult group (N=62). In an identity-specific condition, the sound coupled to the motor action was predictable, while in an identity unspecific condition the sound was unpredictable. Results of a temporal principal component analysis revealed that sound-related brain responses underlying the N1-complex differed considerably between age groups. Despite these developmental differences, omission responses (oN1) were similar between age groups. Two subcomponents of the oN1 were differently affected by specific and unspecific predictions. Results demonstrate that children, independent from the maturation of sound processing mechanisms, can implement specific and unspecific predictions as flexibly as adults. This supports theories that regard action and prediction error as important drivers of cognitive development.

Learning from the path not taken: Sensory prediction errors are sufficient for implicit adaptation of withheld movements

Current theories of motor control emphasize forward models as a critical component of the brain's motor execution and learning networks. These internal models are thought to predict the consequences of movement before sensory feedback from these movements can reach the brain, allowing for smooth, continuous online motor performance and for the computation of prediction errors that drive implicit motor learning. Taking this framework to its logical extreme, we tested the hypothesis that movements are not necessary for the generation of predictions, the computation of prediction errors, and implicit motor adaptation. Human participants were cued to move a computer mouse to a visually displayed target and were subsequently cued to withhold those movements on a subset of trials. Visual errors displayed on both trials with and without movements to the target induced single-trial learning. Furthermore, learning on trials without movements persisted when accompanying movement trials were never paired with errors and when movement and sensory feedback trajectories were decoupled. These data provide compelling evidence supporting an internal model framework in which forward models generate sensory predictions independent of the generation of movements.

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.