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

2021 ◽  
Author(s):  
Olivia A Kim ◽  
Alexander D Forrence ◽  
Samuel D McDougle
Keyword(s):  
Sensory Feedback ◽  
Prediction Errors ◽  
Learning Networks ◽  
Model Framework ◽  
Forward Models ◽  
Implicit Motor Learning ◽  
Computer Mouse ◽  
Implicit Motor ◽  
Human Participants ◽  
Sensory Prediction

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.

scholarly journals Distinct Processing of Sensory Prediction Error and Task Error during Motor Learning

2021 ◽  
Author(s):  
Jonathan Tsay ◽  
Adrian Haith ◽  
Richard B Ivry ◽  
Hyosub E Kim
Keyword(s):  
Prediction Error ◽  
Sensory Feedback ◽  
Displacement Method ◽  
Visuomotor Learning ◽  
Primary Signal ◽  
Implicit Motor ◽  
Feedback Method ◽  
The Difference ◽  
Sensory Prediction ◽  
And Task

While sensory-prediction error (SPE), the difference between predicted and actual sensory feedback, is recognized as the primary signal that drives implicit motor recalibration, recent studies have shown that task error (TE), the difference between sensory feedback and the movement goal, also plays a modulatory role. To systematically examine how SPE and TE collectively shape implicit recalibration, we performed a series of visuomotor learning experiments, introducing perturbations that varied the size of TE using a popular target displacement method and the size of SPE using a clamped visual feedback method. In Experiments 1 & 2, we observed robust sign-dependent changes in hand angle in response to perturbations with both SPE and TE but failed to observe changes in hand angle in response to TE-only perturbations. Yet in Experiments 3 & 4, the magnitude of TE modulated implicit recalibration in the presence of a fixed SPE. Taken together, these results underscore that implicit recalibration is driven by both SPE and TE (Kim, Parvin, & Ivry, 2019), while specifying unappreciated interactions between these two error-based processes. First, TE only impacts implicit calibration when SPE is present. Second, transient changes occurring when the target is displaced to manipulate TE has an attenuating effect on implicit recalibration, perhaps due to attention being directed away from the sensory feedback.

scholarly journals Task errors contribute to implicit remapping in sensorimotor adaptation

2018 ◽  
Author(s):  
Li-Ann Leow ◽  
Welber Marinovic ◽  
Aymar de Rugy ◽  
Timothy J Carroll
Keyword(s):  
Sensory Feedback ◽  
Hand Position ◽  
Sensorimotor Adaptation ◽  
Prediction Errors ◽  
Reward Prediction ◽  
Strategic Processes ◽  
The Relationship ◽  
Sensory Prediction ◽  
Or Task

AbstractPerturbations of sensory feedback evoke sensory prediction errors (discrepancies between predicted and actual sensory outcomes of movements), and reward prediction errors (discrepancies between predicted rewards and actual rewards). Sensory prediction errors result in obligatory remapping of the relationship between motor commands and predicted sensory outcomes. The role of reward prediction errors in sensorimotor adaptation is less clear. When moving towards a target, we expect to obtain the reward of hitting the target, and so we experience a reward prediction error if the perturbation causes us to miss it. These discrepancies between desired task outcomes and actual task outcomes, or “task errors”, are thought to drive the use of strategic processes to restore success, although their role is not fully understood. Here, we investigated the role of task errors in sensorimotor adaptation: during target-reaching, we either removed task errors by moving the target mid-movement to align with cursor feedback of hand position, or enforced task error by moving the target away from the cursor feedback of hand position. Removing task errors not only reduced the rate and extent of adaptation during exposure to the perturbation, but also reduced the amount of post-adaptation implicit remapping. Hence, task errors contribute to implicit remapping resulting from sensory prediction errors. This suggests that the system which implicitly acquires new sensorimotor maps via exposure to sensory prediction errors is also sensitive to reward prediction errors.

scholarly journals Does somatosensory acuity influence the extent of internal model recalibration in young and older adults?

2020 ◽  
Author(s):  
Koenraad Vandevoorde ◽  
Jean-Jacques Orban de Xivry
Keyword(s):  
Older Adults ◽  
Sensory Integration ◽  
Prediction Error ◽  
Internal Model ◽  
Sensory Feedback ◽  
Motor Adaptation ◽  
Age Related ◽  
Somatosensory Information ◽  
Implicit Motor ◽  
Sensory Prediction

AbstractThe 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, automatic adjustment of movement, or internal model recalibration, remains intact and might even be increased with aging. Since somatosensory information appears to be required for internal model recalibration, it might well be that an age-related decline in somatosensory acuity is linked to the increase of internal model recalibration. One possible explanation for an increased internal model recalibration is that age-related somatosensory deficits could lead to altered sensory integration with an increased weighting of the visual sensory-prediction error. Another possibility is that reduced somatosensory acuity results in an increased reliance on predicted sensory feedback. Both these explanations led to our preregistered hypothesis: we expect a relation between the decline of somatosensation and the increased internal model recalibration with aging. However, we failed to support this hypothesis. Our results question the existence of reliability-based integration of visual and somatosensory signals during motor adaptation.New & NoteworthyIs somatosensory acuity linked to implicit motor adaptation? The latter is larger in old compared to younger people? In light of reliability-based sensory integration, we hypothesized that this larger implicit adaptation was linked to an age-related lower reliability of somatosensation. Over two experiments and 130 participants, we failed to find any evidence for this. We discuss alternative explanations for the increase in implicit adaptation with age and the validity of our somatosensory assessment.

scholarly journals Task errors drive memories that improve sensorimotor adaptation

2019 ◽  
Author(s):  
Li-Ann Leow ◽  
Welber Marinovic ◽  
Aymar de Rugy ◽  
Timothy J Carroll
Keyword(s):  
Sensory Feedback ◽  
Target Location ◽  
Adaptive Behaviour ◽  
Hand Position ◽  
Sensorimotor Adaptation ◽  
Prediction Errors ◽  
Preparation Time ◽  
Position Feedback ◽  
History Of ◽  
Sensory Prediction

AbstractTraditional views on how humans adapt movements to perturbations of sensory feedback emphasize a fundamental role for automatic, implicit correction of sensory prediction errors. However, it is now clear that adaptive behaviour also involves deliberate, strategic movement corrections. Such strategic processes have recently been argued to underlie the latent retention of sensorimotor adaptation, evident in improved adaptation to previously encountered perturbations; a phenomenon termed “savings”. It remains unclear, however, whether savings results from prior experience of sensory prediction errors, task errors, or both. Here, we used perturbations of target locations and hand position feedback during reaching to dissociate the contributions of task and sensory prediction errors to latent sensorimotor memory. We show that prior learning to correct for task errors is required to improve adaptation to rotated hand position feedback, whereas a history of sensory prediction errors is neither sufficient nor obligatory for savings. A history of correcting for task errors, induced by experimentally perturbing the target location instead of perturbing sensory feedback of movement, improved adaptation to visuomotor perturbations that were never before encountered. Limiting movement preparation time further showed that this learning consists of two distinct components: 1) a strategic component that is flexible enough to facilitate corrective responses in the opposite direction, but that requires substantial preparation time, and 2) a set of inflexible, cached, stimulus-response associations between targets and reach directions, that can be expressed under time-pressure when similar task conditions are experienced. The results emphasise that adaptive responses to sensorimotor perturbations take multiple forms.

scholarly journals Implicit motor learning in primary school children: A systematic review

2021 ◽  
pp. 1-19
Author(s):  
Femke van Abswoude ◽  
Remo Mombarg ◽  
Wouter de Groot ◽  
Gwennyth Eileen Spruijtenburg ◽  
Bert Steenbergen
Keyword(s):  
Systematic Review ◽  
Motor Learning ◽  
Primary School ◽  
School Children ◽  
Primary School Children ◽  
Implicit Motor Learning ◽  
Implicit Motor

scholarly journals Implicit motor learning within three trials

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jennifer E. Ruttle ◽  
Bernard Marius ’t Hart ◽  
Denise Y. P. Henriques
Keyword(s):  
Motor Learning ◽  
Implicit Learning ◽  
Time Course ◽  
Skills Training ◽  
Implicit Processes ◽  
Training Performance ◽  
Slow Development ◽  
Implicit Motor Learning ◽  
Implicit Motor ◽  
And Shifts

AbstractIn motor learning, the slow development of implicit learning is traditionally taken for granted. While much is known about training performance during adaptation to a perturbation in reaches, saccades and locomotion, little is known about the time course of the underlying implicit processes during normal motor adaptation. Implicit learning is characterized by both changes in internal models and state estimates of limb position. Here, we measure both as reach aftereffects and shifts in hand localization in our participants, after every training trial. The observed implicit changes were near asymptote after only one to three perturbed training trials and were not predicted by a two-rate model’s slow process that is supposed to capture implicit learning. Hence, we show that implicit learning is much faster than conventionally believed, which has implications for rehabilitation and skills training.

Transcranial static magnetic stimulation over the primary motor cortex alters sequential implicit motor learning

2019 ◽  
Vol 696 ◽  
pp. 33-37 ◽  
Author(s):  
Ippei Nojima ◽  
Tatsunori Watanabe ◽  
Tomoya Gyoda ◽  
Hisato Sugata ◽  
Takashi Ikeda ◽  
...  
Keyword(s):  
Motor Cortex ◽  
Motor Learning ◽  
Magnetic Stimulation ◽  
Primary Motor Cortex ◽  
Implicit Motor Learning ◽  
Implicit Motor

scholarly journals Spinal microcircuits comprising dI3 interneurons are necessary for motor functional recovery following spinal cord transection

eLife ◽  
2016 ◽  
Vol 5 ◽  
Author(s):  
Tuan V Bui ◽  
Nicolas Stifani ◽  
Turgay Akay ◽  
Robert M Brownstone
Keyword(s):  
Spinal Cord ◽  
Functional Recovery ◽  
Motor System ◽  
Motor Training ◽  
Prediction Errors ◽  
Spinal Interneurons ◽  
Motor Activities ◽  
Afferent Inputs ◽  
To Receive ◽  
Sensory Prediction

The spinal cord has the capacity to coordinate motor activities such as locomotion. Following spinal transection, functional activity can be regained, to a degree, following motor training. To identify microcircuits involved in this recovery, we studied a population of mouse spinal interneurons known to receive direct afferent inputs and project to intermediate and ventral regions of the spinal cord. We demonstrate that while dI3 interneurons are not necessary for normal locomotor activity, locomotor circuits rhythmically inhibit them and dI3 interneurons can activate these circuits. Removing dI3 interneurons from spinal microcircuits by eliminating their synaptic transmission left locomotion more or less unchanged, but abolished functional recovery, indicating that dI3 interneurons are a necessary cellular substrate for motor system plasticity following transection. We suggest that dI3 interneurons compare inputs from locomotor circuits with sensory afferent inputs to compute sensory prediction errors that then modify locomotor circuits to effect motor recovery.

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