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 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.

Reward Prediction Errors Drive Declarative Learning Irrespective of Agency

2020 ◽  
Author(s):  
Kate Ergo ◽  
Luna De Vilder ◽  
Esther De Loof ◽  
Tom Verguts
Keyword(s):  
Learning Theory ◽  
Learning Effect ◽  
Steady Increase ◽  
Prediction Errors ◽  
Experimental Paradigm ◽  
Reward Prediction ◽  
Declarative Learning

Recent years have witnessed a steady increase in the number of studies investigating the role of reward prediction errors (RPEs) in declarative learning. Specifically, in several experimental paradigms RPEs drive declarative learning; with larger and more positive RPEs enhancing declarative learning. However, it is unknown whether this RPE must derive from the participant’s own response, or whether instead any RPE is sufficient to obtain the learning effect. To test this, we generated RPEs in the same experimental paradigm where we combined an agency and a non-agency condition. We observed no interaction between RPE and agency, suggesting that any RPE (irrespective of its source) can drive declarative learning. This result holds implications for declarative learning theory.

When theory and biology differ: The relationship between reward prediction errors and expectancy

2017 ◽  
Vol 129 ◽  
pp. 265-272 ◽  
Author(s):  
Chad C. Williams ◽  
Cameron D. Hassall ◽  
Robert Trska ◽  
Clay B. Holroyd ◽  
Olave E. Krigolson
Keyword(s):  
Prediction Errors ◽  
Reward Prediction ◽  
The Relationship

scholarly journals Beyond reward prediction errors: the role of dopamine in movement kinematics

2015 ◽  
Vol 9 ◽  
Author(s):  
Joseph W. Barter ◽  
Suellen Li ◽  
Dongye Lu ◽  
Ryan A. Bartholomew ◽  
Mark A. Rossi ◽  
...  
Keyword(s):  
Prediction Errors ◽  
Movement Kinematics ◽  
Reward Prediction

scholarly journals Associative learning and animal cognition

2012 ◽  
Vol 367 (1603) ◽  
pp. 2733-2742 ◽  
Author(s):  
Anthony Dickinson
Keyword(s):  
Associative Learning ◽  
Practical Reasoning ◽  
Animal Cognition ◽  
Prediction Errors ◽  
Associative Processes ◽  
Directed Action ◽  
Processing Architectures ◽  
The Relationship ◽  
Theoretical Component

Associative learning plays a variety of roles in the study of animal cognition from a core theoretical component to a null hypothesis against which the contribution of cognitive processes is assessed. Two developments in contemporary associative learning have enhanced its relevance to animal cognition. The first concerns the role of associatively activated representations, whereas the second is the development of hybrid theories in which learning is determined by prediction errors, both directly and indirectly through associability processes. However, it remains unclear whether these developments allow associative theory to capture the psychological rationality of cognition. I argue that embodying associative processes within specific processing architectures provides mechanisms that can mediate psychological rationality and illustrate such embodiment by discussing the relationship between practical reasoning and the associative-cybernetic model of goal-directed action.

scholarly journals Acoustic stimulation increases implicit adaptation in sensorimotor adaptation

2020 ◽  
Author(s):  
Li-Ann Leow ◽  
James R. Tresilian ◽  
Aya Uchida ◽  
Dirk Koester ◽  
Tamara Spingler ◽  
...  
Keyword(s):  
Motor Skills ◽  
Brain Stimulation ◽  
Acoustic Stimulation ◽  
Individual Variability ◽  
Healthy Adults ◽  
Sensorimotor Adaptation ◽  
Prediction Errors ◽  
Motor Tasks ◽  
Non Invasive ◽  
Sensory Prediction

AbstractSensorimotor 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 interindividual 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 30° 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.

scholarly journals Both fast and slow learning processes contribute to savings following sensorimotor adaptation

2019 ◽  
Vol 121 (4) ◽  
pp. 1575-1583 ◽  
Author(s):  
Susan K. Coltman ◽  
Joshua G. A. Cashaback ◽  
Paul L. Gribble
Keyword(s):  
Force Field ◽  
Motor Adaptation ◽  
Retention Rates ◽  
Sensorimotor Adaptation ◽  
Prediction Errors ◽  
Fast Process ◽  
Learning Rates ◽  
History Of ◽  
Underlying Mechanisms ◽  
Sensory Prediction

Recent work suggests that the rate of learning in sensorimotor adaptation is likely not fixed, but rather can change based on previous experience. One example is savings, a commonly observed phenomenon whereby the relearning of a motor skill is faster than the initial learning. Sensorimotor adaptation is thought to be driven by sensory prediction errors, which are the result of a mismatch between predicted and actual sensory consequences. It has been proposed that during motor adaptation the generation of sensory prediction errors engages two processes (fast and slow) that differ in learning and retention rates. We tested the idea that a history of errors would influence both the fast and slow processes during savings. Participants were asked to perform the same force field adaptation task twice in succession. We found that adaptation to the force field a second time led to increases in estimated learning rates for both fast and slow processes. While it has been proposed that savings is explained by an increase in learning rate for the fast process, here we observed that the slow process also contributes to savings. Our work suggests that fast and slow adaptation processes are both responsive to a history of error and both contribute to savings. NEW & NOTEWORTHY We studied the underlying mechanisms of savings during motor adaptation. Using a two-state model to represent fast and slow processes that contribute to motor adaptation, we found that a history of error modulates performance in both processes. While previous research has attributed savings to only changes in the fast process, we demonstrated that an increase in both processes is needed to account for the measured behavioral data.

scholarly journals What, If, and When to Move: Basal Ganglia Circuits and Self-Paced Action Initiation

2019 ◽  
Vol 42 (1) ◽  
pp. 459-483 ◽  
Author(s):  
Andreas Klaus ◽  
Joaquim Alves da Silva ◽  
Rui M. Costa
Keyword(s):  
Basal Ganglia ◽  
Prediction Errors ◽  
Movement Initiation ◽  
Reward Prediction ◽  
Behavioral Transitions ◽  
Main Input ◽  
Action Initiation

Deciding what to do and when to move is vital to our survival. Clinical and fundamental studies have identified basal ganglia circuits as critical for this process. The main input nucleus of the basal ganglia, the striatum, receives inputs from frontal, sensory, and motor cortices and interconnected thalamic areas that provide information about potential goals, context, and actions and directly or indirectly modulates basal ganglia outputs. The striatum also receives dopaminergic inputs that can signal reward prediction errors and also behavioral transitions and movement initiation. Here we review studies and models of how direct and indirect pathways can modulate basal ganglia outputs to facilitate movement initiation, and we discuss the role of cortical and dopaminergic inputs to the striatum in determining what to do and if and when to do it. Complex but exciting scenarios emerge that shed new light on how basal ganglia circuits modulate self-paced movement initiation.

scholarly journals The relationship between reinforcement and explicit strategies during visuomotor adaptation

2017 ◽  
Author(s):  
Olivier Codol ◽  
Peter J Holland ◽  
Joseph M Galea
Keyword(s):  
Prediction Error ◽  
Visuomotor Adaptation ◽  
Strategy Use ◽  
Asymptotic Performance ◽  
Preparation Time ◽  
Learning Success ◽  
Error Learning ◽  
The Relationship ◽  
Sensory Prediction

AbstractThe motor system’s ability to adapt to changes in the environment is essential for maintaining accurate movements. During such adaptation several distinct systems are recruited: cerebellar sensory-prediction error learning, success-based reinforcement, and explicit strategy-use. Although much work has focused on the relationship between cerebellar learning and strategy-use, there is little research regarding how reinforcement and strategy-use interact. To address this, participants first learnt a 20° visuomotor displacement. After reaching asymptotic performance, binary, hit-or-miss feedback (BF) was introduced either with or without visual feedback, the latter promoting reinforcement. Subsequently, retention was assessed using no-feedback trials, with half of the participants in each group being instructed to stop using any strategy. Although BF led to an increase in retention of the visuomotor displacement, instructing participants to remove their strategy nullified this effect, suggesting strategy-use is critical to BF-based reinforcement. In a second experiment, we prevented the expression or development of a strategy during BF performance, by either constraining participants to a short preparation time (expression) or by introducing the displacement gradually (development). As both strongly impaired BF performance, it suggests reinforcement requires both the development and expression of a strategy. These results emphasise a pivotal role of strategy-use during reinforcement-based motor learning.

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.

Sign in / Sign up

Export Citation Format

Share Document