The Origins of Anterograde Interference in Visuomotor Adaptation

Repeated context-specific actions disrupt feedforward adjustments in motor commands in younger and older adults

The flexibility of the motor system to adjust a planned action before or during the execution of the movement in response to sensory information is critical for preventing errors in motor control. As individuals age, this function declines, leading to an increased incidence of motor errors. Although sensory processing and cognitive decline are known contributors to this impairment, here, we test the hypothesis that repetition of context-specific planned actions interferes with the adjustment of feedforward motor commands. Younger and older participants were instructed to grasp and lift a T-shaped object with a concealed, off-sided center of mass and minimize its roll through anticipatory force control, relying predominantly on predictive model-driven planning (i.e., sensorimotor memories) developed through repeated lifts. We selectively manipulate the number of trial repeats with the center of mass on one side before switching it to the other side of the T-shaped object. The results showed that increasing the number of repetitions improved performance in manipulating an object with a given center of mass but led to increased errors when the object's center of mass was switched. This deleterious effect of repetition on feedforward motor adjustment was observed in younger and older adults. Critically, we show these effects on an internal model-driven motor planning task that relies predominantly on sensorimotor memory, with no differences in sensory inputs from the repetition manipulation. The findings indicate that feedforward motor adjustments are hampered by repetitive stereotyped planning and execution of motor behavior.NEW & NOTEWORTHY Adjusting planned actions in response to sensory stimuli degrades with age contributing to increased incidence of errors ranging from clumsy spills to catastrophic falls. Multiple factors likely contribute to age-related motor inflexibility, including sensory- and cognition-supporting system declines. Here, we present compelling evidence for repetition to disrupt feedforward adjusting of motor commands in younger and older adults, which suggests increases in stereotypy as a deleterious potentiator of motor control errors.

A cerebellar population coding model for sensorimotor learning

The cerebellum is crucial for sensorimotor adaptation, using error information to keep the sensorimotor system well-calibrated. Here we introduce a population-coding model to explain how cerebellar-dependent learning is modulated by contextual variation. The model consists of a two-layer network, designed to capture activity in both the cerebellar cortex and deep cerebellar nuclei. A core feature of the model is that within each layer, the processing units are tuned to both movement direction and the direction of movement error. The model captures a large range of contextual effects including interference from prior learning and the influence of error uncertainty and volatility. While these effects have traditionally been taken to indicate meta learning or context-dependent memory within the adaptation system, our results show that they are emergent properties that arise from the population dynamics within the cerebellum. Our results provide a novel framework to understand how the nervous system responds to variable environments.

A software tool for at-home measurement of sensorimotor adaptation

Sensorimotor adaptation is traditionally studied in well-controlled laboratory settings with specialized equipment. However, recent public health concerns such as the COVID-19 pandemic, as well as a desire to recruit a more diverse study population, have led the motor control community to consider at-home study designs. At-home motor control experiments are still rare because of the requirement to write software that can be easily used by anyone on any platform. To this end, we developed software that runs locally on a personal computer. The software provides audiovisual instructions and measures the ability of the subject to control the cursor in the context of visuomotor perturbations. We tested the software on a group of at-home participants and asked whether the adaptation principles inferred from in-lab measurements were reproducible in the at-home setting. For example, we manipulated the perturbations to test whether there were changes in adaptation rates (savings and interference), whether adaptation was associated with multiple timescales of memory (spontaneous recovery), and whether we could selectively suppress subconscious learning (delayed feedback, perturbation variability) or explicit strategies (limited reaction time). We found remarkable similarity between in-lab and at-home behaviors across these experimental conditions. Thus, we developed a software tool that can be used by research teams with little or no programming experience to study mechanisms of adaptation in an at-home setting.

The influence of learning history on anterograde interference

Classically interpreted as a competition between opposite memories (A vs B), anterograde interference (AI) also emerges in the absence of competing memories (A vs A), suggesting that mechanisms other than those involved in memory competition contribute to AI. To investigate this, we tested the hypothesis that extending motor practice would enhance a first memory, but come at the cost of reduced learning capabilities when subsequently exposed to a second learning session of the same task. Based on converging biological evidence, AI was expected to depend upon the degree of extended practice of the initial exposure. During a first Session, four conditions were carried out where participants (n = 24) adapted to a gradually introduced -20° visual deviation while the extent of the initial exposure was manipulated by varying the duration or type of the performance asymptote. Specifically, the performance asymptote at -20° was either Short (40 trials), Moderate (160 trials), Long (320 trials), or absent due to continuously changing perturbations around the mean of -20° (Jagged; 160 trials). After a 2-min interval, participants re-adapted to the same (-20°) visual deviation, which was meant to probe the effect of extended practice in the first Session on the learning capabilities of a second identical memory (A vs A). The results first confirmed that the duration of exposure in the first Session enhanced immediate aftereffects in the Moderate, Long, and Jagged conditions as compared to the Short condition, suggesting that extended practice enhanced retention of the first memory. When comparing the second Session to the first one, results revealed a different pattern of re-adaptation depending on the duration of initial exposure: in the Short condition, there was evidence for facilitated re-adaptation and similar aftereffects. However, in the Moderate, Long and Jagged conditions, re-adaptation was similar and aftereffects were impaired, suggestive of AI. This suggests that extended practice initially enhances memory formation, but comes at the cost of reduced subsequent learning capabilities. One possibility is that AI occurs because extended practice induces the emergence of network-specific homeostatic constraints, which limit subsequent neuroplastic and learning capabilities in the same neural network.

The effects of prior exposure to prism lenses on de novo motor skill learning

Motor learning involves plasticity in a network of brain areas across the cortex and cerebellum. Such traces of learning have the potential to affect subsequent learning of other tasks. In some cases, prior learning can interfere with subsequent learning, but it may be possible to potentiate learning of one task with a prior task if they are sufficiently different. Because prism adaptation involves extensive neuroplasticity, we reasoned that the elevated excitability of neurons could increase their readiness to undergo structural changes, and in turn, create an optimal state for learning a subsequent task. We tested this idea, selecting two different forms of learning tasks, asking whether exposure to a sensorimotor adaptation task can improve subsequent de novo motor skill learning. Participants first learned a new visuomotor mapping induced by prism glasses in which prism strength varied trial-to-trial. Immediately after and the next day, we tested participants on a mirror tracing task, a form of de novo skill learning. Prism-trained and control participants both learned the mirror tracing task, with similar reductions in error and increases in distance traced. Both groups also showed evidence of offline performance gains between the end of day 1 and the start of day 2. However, we did not detect differences between groups. Overall, our results do not support the idea that prism adaptation learning can potentiate subsequent de novo learning. We discuss factors that may have contributed to this result.

Evidence that anterograde learning interference depends on the stage of learning of the interferer: blocked versus interleaved training

Training on one task (task A) can disrupt learning on a subsequently trained task (task B), illustrating anterograde learning interference. We asked whether the induction of anterograde learning interference depends on the learning stage that task A has reached when the training on task B begins. To do so, we drew on previous observations in perceptual learning in which completing all training on one task before beginning training on another task (blocked training) yielded markedly different learning outcomes than alternating training between the same two tasks for the same total number of trials (interleaved training). Those blocked versus interleaved contrasts suggest that there is a transition between two differentially vulnerable learning stages that is related to the number of consecutive training trials on each task, with interleaved training presumably tapping acquisition, and blocked training tapping consolidation. Here, we used the blocked versus interleaved paradigm in auditory perceptual learning in a case in which blocked training generated anterograde-but not its converse, retrograde-learning interference (A→B, not B←A). We report that anterograde learning interference of training on task A (interaural time difference discrimination) on learning on task B (interaural level difference discrimination) occurred with blocked training and diminished with interleaved training, with faster rates of interleaving leading to less interference. This pattern held for across-day, within-session, and offline learning. Thus, anterograde learning interference only occurred when the number of consecutive training trials on task A surpassed some critical value, consistent with other recent evidence that anterograde learning interference only arises when learning on task A has entered the consolidation stage.

Low Vision Impairs Implicit Sensorimotor Adaptation in Response to Small Errors, But Not Large Errors

Successful goal-directed actions require constant fine-tuning of the motor system. This fine-tuning is thought to rely on an implicit adaptation process that is driven by sensory prediction errors (e.g., where you see your hand after reaching vs. where you expected it to be). Individuals with low vision experience challenges with visuomotor control, but whether low vision disrupts motor adaptation is unknown. To explore this question, we assessed individuals with low vision and matched controls with normal vision on a visuomotor task designed to isolate implicit adaptation. We found that low vision was associated with attenuated implicit adaptation only for small visual errors, but not for large visual errors. This result highlights important constraints underlying how low-fidelity visual information is processed by the sensorimotor system to enable successful implicit adaptation.

Interactions between sensory prediction error and task error during implicit motor learning

Implicit motor recalibration allows us to flexibly move in novel and changing environments. Conventionally, implicit recalibration is thought to be driven by errors in predicting the sensory outcome of movement (i.e., sensory prediction errors). However, recent studies have shown that implicit recalibration is also influenced by errors in achieving the movement goal (i.e., task errors). Exactly how sensory prediction errors and task errors interact to drive implicit recalibration and, in particular, whether task errors alone might be sufficient to drive implicit recalibration remain unknown. To test this, we induced task errors in the absence of sensory prediction errors by displacing the target mid-movement. We found that task errors alone failed to induce implicit recalibration. In additional experiments, we simultaneously varied the size of sensory prediction errors and task errors. We found that implicit recalibration driven by sensory prediction errors could be continuously modulated by task errors, revealing an unappreciated dependency between these two sources of error. Moreover, implicit recalibration was attenuated when the target was simply flickered in its original location, even though this manipulation did not affect task error - an effect likely attributed to attention being directed away from the feedback cursor. Taken as a whole, the results were accounted for by a computational model in which sensory prediction errors and task errors, modulated by attention, interact to determine the extent of implicit recalibration.

Competition between parallel sensorimotor learning systems

Sensorimotor learning is supported by at least two parallel systems: a strategic process that benefits from explicit knowledge and an implicit process that adapts subconsciously. How do these systems interact? Does one system's contributions suppress the other, or do they operate independently? Here, we illustrate that during reaching, implicit and explicit systems both learn from visual target errors. This shared error leads to competition such that an increase in the explicit system's response siphons away resources that are needed for implicit adaptation, thus reducing its learning. As a result, steady-state implicit learning can vary across experimental conditions, due to changes in strategy. Furthermore, strategies can mask changes in implicit learning properties, such as its error sensitivity. These ideas, however, become more complex in conditions where subjects adapt using multiple visual landmarks, a situation which introduces learning from sensory prediction errors in addition to target errors. These two types of implicit errors can oppose each other, leading to another type of competition. Thus, during sensorimotor adaptation, implicit and explicit learning systems compete for a common resource: error.

Anterograde interference emerges along a gradient as a function of task similarity: A behavioural study

Anterograde interference emerges when two opposite (B → A) or identical tasks (A → A) are learned in close temporal succession, suggesting that interference cannot be fully accounted for by competing memories. Informed by neurobiological evidence, this work tested the hypothesis that interference depends upon the degree of overlap between the neural networks involved in the learning of two tasks. In a fully within‐subject and counterbalanced design, participants (n = 24) took part in two learning sessions where the putative overlap between learning‐specific neural networks was behaviourally manipulated across four conditions by modifying reach direction and the effector used during gradual visuomotor adaptation. The results showed that anterograde interference emerged regardless of memory competition—that is, to a similar extent in the B → A and A → A conditions—and along a gradient as a function of the tasks' similarity. Specifically, learning under similar reaching conditions generated more anterograde interference than learning under dissimilar reaching conditions, suggesting that putatively overlapping neural networks are required to generate interference. Overall, these results indicate that competing memories are not the sole contributor to anterograde interference and suggest that overlapping neural networks between two learning sessions are required to trigger interference. One discussed possibility is that initial learning modifies the properties of its neural networks to constrain further plasticity induction and learning capabilities, therefore causing anterograde interference in a network‐dependent manner. One implication is that learning‐specific neural networks must be maximally dissociated to minimize the interfering influences of previous learning on subsequent learning.

Composition and decomposition of visuomotor maps during manual tracking

Adapting hand movements to changes in our body or the environment is essential for skilled motor behavior, as is the ability to flexibly combine experience gathered in separate contexts. However, it has been shown that when adapting hand movements to two different visuomotor perturbations in succession, interference effects can occur. Here, we investigate whether these interference effects compromise our ability to adapt to the superposition of the two perturbations. Participants tracked with a joystick, a visual target that followed a smooth but an unpredictable trajectory. Four separate groups of participants (total n = 83) completed one block of 50 trials under each of three mappings: one in which the cursor was rotated by 90° (ROTATION), one in which the cursor mimicked the behavior of a mass-spring system (SPRING), and one in which the SPRING and ROTATION mappings were superimposed (SPROT). The order of the blocks differed across groups. Although interference effects were found when switching between SPRING and ROTATION, participants who performed these blocks first performed better in SPROT than participants who had no prior experience with SPRING and ROTATION (i.e., composition). Moreover, participants who started with SPROT exhibited better performance under SPRING and ROTATION than participants who had no prior experience with each of these mappings (i.e., decomposition). Additional analyses confirmed that these effects resulted from components of learning that were specific to the rotational and spring perturbations. These results show that interference effects do not preclude the ability to compose/decompose various forms of visuomotor adaptation.NEW & NOTEWORTHY The ability to compose/decompose task representations is critical for both cognitive and behavioral flexibility. Here, we show that this ability extends to two forms of visuomotor adaptation in which humans have to perform visually guided hand movements. Despite the presence of interference effects when switching between visuomotor maps, we show that participants are able to flexibly compose or decompose knowledge acquired in previous sessions. These results further demonstrate the flexibility of sensorimotor adaptation in humans.

Motor Learning Promotes the Coupling between Fast Spindles and Slow Oscillations Locally over the Contralateral Motor Network

Recent studies from us and others suggest that traditionally declarative structures mediate some aspects of the encoding and consolidation of procedural memories. This evidence points to the existence of converging physiological pathways across memory systems. Here, we examined whether the coupling between slow oscillations (SO) and spindles, a mechanism well established in the consolidation of declarative memories, is relevant for the stabilization of human motor memories. To this aim, we conducted an electroencephalography study in which we quantified various parameters of these oscillations during a night of sleep that took place immediately after learning a visuomotor adaptation (VMA) task. We found that VMA increased the overall density of fast (≥12 Hz), but not slow (<12 Hz), spindles during nonrapid eye movement sleep, stage 3 (NREM3). This modulation occurred rather locally over the hemisphere contralateral to the trained hand. Although adaptation learning did not affect the density of SOs, it substantially enhanced the number of fast spindles locked to the active phase of SOs. The fact that only coupled spindles predicted overnight memory retention points to the relevance of this association in motor memory consolidation. Our work provides evidence in favor of a common mechanism at the basis of the stabilization of declarative and motor memories.

Training at asymptote stabilizes motor memories by reducing intracortical excitation

Learning similar motor skills in close succession is limited by interference, a phenomenon that takes place early after acquisition when motor memories are unstable. Interference can be bidirectional, as the first memory can be disrupted by the second (retrograde interference), or the second memory can be disrupted by the first (anterograde interference). The heightened plastic state of primary motor cortex after learning is thought to underlie interference, as unstable motor memories compete for neural resources. While time-dependent consolidation processes reduce interference, the passage of time (~6 h) required for memory stabilization limits our capacity to learn multiple motor skills at once. Here, we demonstrate in humans that prolonged training at asymptote of an initial motor skill reduces both retrograde and anterograde interference when a second motor skill is acquired in close succession. Neurophysiological assessments via transcranial magnetic stimulation reflect this online stabilization process. Specifically, excitatory neurotransmission in primary motor cortex increased after short training and decreased after prolonged training at performance asymptote. Of note, this reduction in intracortical excitation after prolonged training was proportional to better skill retention the following day. Importantly, these neurophysiological effects were not observed after motor practice without learning or after a temporal delay. Together, these findings indicate that prolonged training at asymptote improves the capacity to learn multiple motor skills in close succession, and that downregulation of excitatory neurotransmission in primary motor cortex may be a marker of online motor memory stabilization.

Acoustic stimulation increases implicit adaptation in sensorimotor adaptation

Sensorimotor adaptation is an important part of our ability to perform novel motor tasks (i.e., learning of motor skills). Efforts to improve adaptation in healthy and clinical patients using non-invasive brain stimulation methods have been hindered by inter-individual and intra-individual variability in brain susceptibility to stimulation. Here, we explore unpredictable loud acoustic stimulation as an alternative method of modulating brain excitability to improve sensorimotor adaptation. In two experiments, participants moved a cursor towards targets, and adapted to a 30º rotation of cursor feedback, either with or without unpredictable acoustic stimulation. Acoustic stimulation improved initial adaptation to sensory prediction errors in Study 1, and improved overnight retention of adaptation in Study 2. Unpredictable loud acoustic stimulation might thus be a potent method of modulating sensorimotor adaptation in healthy adults.

Learning the same motor task twice impairs its retention in a time- and dose-dependent manner

Anterograde interference emerges when two differing tasks are learned in close temporal proximity, an effect repeatedly attributed to a competition between differing task memories. However, recent development alternatively suggests that initial learning may trigger a refractory period that occludes neuroplasticity and impairs subsequent learning, consequently mediating interference independently of memory competition. Accordingly, this study tested the hypothesis that interference can emerge when the same motor task is being learned twice, that is when competition between memories is prevented. In a first experiment, the inter-session interval (ISI) between two identical motor learning sessions was manipulated to be 2 min, 1 h or 24 h. Results revealed that retention of the second session was impaired as compared to the first one when the ISI was 2 min but not when it was 1 h or 24 h, indicating a time-dependent process. Results from a second experiment replicated those of the first one and revealed that adding a third motor learning session with a 2 min ISI further impaired retention, indicating a dose-dependent process. Results from a third experiment revealed that the retention impairments did not take place when a learning session was preceded by simple rehearsal of the motor task without concurrent learning, thus ruling out fatigue and confirming that retention is impaired specifically when preceded by a learning session. Altogether, the present results suggest that competing memories is not the sole mechanism mediating anterograde interference and introduce the possibility that a time- and dose-dependent refractory period-independent of fatigue-also contributes to its emergence. One possibility is that learning transiently perturbs the homeostasis of learning-related neuronal substrates. Introducing additional learning when homeostasis is still perturbed may not only impair performance improvements, but also memory formation.

Timescales of motor memory formation in dual-adaptation

The timescales of adaptation to novel dynamics are well explained by a dual-rate model with slow and fast states. This model can predict interference, savings and spontaneous recovery, but cannot account for adaptation to multiple tasks, as each new task drives unlearning of the previously learned task. Nevertheless, in the presence of appropriate contextual cues, humans are able to adapt simultaneously to opposing dynamics. Consequently this model was expanded, suggesting that dual-adaptation occurs through a single fast process and multiple slow processes. However, such a model does not predict spontaneous recovery within dual-adaptation. Here we assess the existence of multiple fast processes by examining the presence of spontaneous recovery in two experimental variations of an adaptation-de-adaptation-error-clamp paradigm within dual-task adaptation in humans. In both experiments, evidence for spontaneous recovery towards the initially learned dynamics (A) was found in the error-clamp phase, invalidating the one-fast-two-slow dual-rate model. However, as adaptation is not only constrained to two timescales, we fit twelve multi-rate models to the experimental data. BIC model comparison again supported the existence of two fast processes, but extended the timescales to include a third rate: the ultraslow process. Even within our single day experiment, we found little evidence for decay of the learned memory over several hundred error-clamp trials. Overall, we show that dual-adaptation can be best explained by a two-fast-triple-rate model over the timescales of adaptation studied here. Longer term learning may require even slower timescales, explaining why we never forget how to ride a bicycle.

Retaining motor skills is crucial to perform basic daily life tasks. However we still have limited understanding of the computational structure of these motor memories, an understanding that is critical for designing rehabilitation. Here we demonstrate that learning any task involves adaptation of independent fast, slow and ultraslow processes to build a motor memory. The selection of the appropriate motor memory is gated through a contextual cue. Together this work extends our understanding of the architecture of motor memories, by merging disparate computational theories to propose a new model.

Characterization of the Adaptation to Visuomotor Rotations in the Muscle Synergies Space

The adaptation to visuomotor rotations is one of the most studied paradigms of motor learning. Previous literature has presented evidence of a dependency between the process of adaptation to visuomotor rotations and the constrains dictated by the workspace of the biological actuators, the muscles, and their co-activation strategies, modeled using muscle synergies analysis. To better understand this relationship, we asked a sample of healthy individuals (N = 7) to perform two experiments aiming at characterizing the adaptation to visuomotor rotations in terms of rotations of the activation space of the muscle synergies during isometric reaching tasks. In both experiments, subjects were asked to adapt to visual rotations altering the position mapping between the force exerted on a fixed manipulandum and the movement of a cursor on a screen. In the first experiment subjects adapted to three different visuomotor rotation angles (30°, 40°, and 50° clockwise) applied to the whole experimental workspace. In the second experiment subjects adapted to a single visuomotor rotation angle (45° clockwise) applied to eight different sub-spaces of the whole workspace, while also performing movements in the rest of the unperturbed workspace. The results from the first experiment confirmed the hypothesis that visuomotor rotations induce rotations in the synergies activation workspace that are proportional to the visuomotor rotation angle. The results from the second experiment showed that rotations affecting limited sub-spaces of the whole workspace are adapted for by rotating only the synergies involved in the movement, with an angle proportional to the distance between the preferred angle of the synergy and the sub-space covered by the rotation. Moreover, we show that the activation of a synergy is only rotated when the sub-space covered by the visual perturbation is applied at the boundaries of the workspace of the synergy. We found these results to be consistent across subjects, synergies and sub-spaces. Moreover, we found a correlation between synergies and muscle rotations further confirming that the adaptation process can be well described, at the neuromuscular level, using the muscle synergies model. These results provide information on how visuomotor rotations can be used to induce a desired neuromuscular response.