Competition between parallel sensorimotor learning systems

Albert, Scott T.; Jang, Jihoon; Haith, Adrian M.; Lerner, Gonzalo; Della‐Maggiore, Valeria; Krakauer, John W.; Shadmehr, Reza

doi:10.1101/2020.12.01.406777

Cited by 26 publications

(46 citation statements)

References 83 publications

(289 reference statements)

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“…In addition, we confirmed a previous finding of incomplete learning of the implicit process as depicted in all groups of the task-irrelevant error-clamp condition. This lower asymptote of the implicit component is consistent with previous reports (Kim et al, 2018), suggesting that this phenomenon probably reflects a balance between learning from errors and forgetting of the adaptive state from one trial to the next (Shmuelof et al, 2012;van der Kooij et al, 2015) Recent reports suggested that the implicit process could also be driven, at least in part, by performance errors and responds to strategic explicit processes (Albert et al, 2020). This is in line with previous studies that showed that strategy use interferes with the build-up of implicit adaptation (Benson et al, 2011;Jakobson & Goodale, 1989), as strategy use would decrease the performance errors that could drive implicit adaptation.…”

Section: Follow-through Movements Allow Separation Of Opposing Memories Through Explicit and Implicit Processessupporting

confidence: 89%

Separation of multiple motor memories through implicit and explicit processes

Mawase

2021

Preprint

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Acquisition of multiple motor skills without interference is a remarkable ability in sport and daily life. During adaptation to opposing perturbations, a common paradigm to study this ability, each perturbation can be successfully learned when a dynamical contextual cue, such as a follow-through movement, is associated with the direction of the perturbation. It is still unclear, however, to what extent this context-dependent learning engages the cognitive strategy-based explicit process and the implicit process that occurs without conscious awareness. Here, we designed four reaching experiments to untangle the individual contributions of the explicit and implicit components while participants learned opposing visuomotor perturbations, with a second unperturbed follow-through movement that served as a contextual cue. In Exp. 1 we replicated previous adaptation results and showed that follow-through movements also allow learning for opposing visuomotor rotations. For one group of participants in Exp. 2 we isolated strategic explicit learning by inducing a 2-sec time delay between movement and end-point feedback, while for another group we isolated the implicit component using the task-irrelevant error-clamp paradigm, in which participants were firmly instructed to aim their reaches directly to the target. Our data showed that opposing perturbations could be fully learned by explicit strategies; but when strategy was restricted, distinct implicit processes contributed to learning. In Exp.3, we examined whether the learned motor behaviors are influenced by the disparity between the follow-through contexts. We found that the location of follow-through targets had little effect on total learning, yet it led to more instances in which participants failed to learn the task. In Exp. 4, we explored the generalization capability to untrained novel targets. Participants showed near-flat generalization of the implicit and explicit processes to adjacent targets. Overall, our results indicate that follow-through contextual cues influence activity of both implicit and explicit processes during separation of motor memories. Furthermore, the follow-through context might activate, in part, top-down cognitive factors that influence not only the dynamics of the explicit learning but also the implicit process.

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Section: Follow-through Movements Allow Separation Of Opposing Memories Through Explicit and Implicit Processessupporting

confidence: 89%

Separation of multiple motor memories through implicit and explicit processes

Mawase

2021

Preprint

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“…However, we did observe that reaction time (Fig. S1A) appeared elevated after passive training in the experimental groups, which is known to commonly accompany cognitive operations (Fernandez-Ruiz et al, 2011; Sakamoto and Kondo, 2012; Anguera et al, 2010; Georgopoulos and Massey, 1987; McDougle et al, 2019; Albert et al, 2020).…”

Section: Discussionmentioning

confidence: 73%

“…When people adapt to two similar perturbations consecutively, re-adaptation evokes a hallmark of sensorimotor adaptation called savings: more rapid learning during the second exposure to a perturbation (Smith et al, 2006; Zarahn et al, 2008; Leow et al, 2013; Haith et al, 2015; Day et al, 2018; Coltman et al, 2020; Yin & Wei, 2020). These changes in learning are thought to be mediated by error sensitivity (Gonzalez-Castro & Hadjiosif, 2014; Herzfeld et al, 2014; Coltman et al, 2020), whereby the trial-by-trial experience of consistent errors makes the brain more sensitive to those errors in the future (Herzfeld et al, 2014; Leow et al, 2016; Albert et al, 2020). Do these changes in the brain’s learning systems require errors to be actively experienced, or can learning be improved by passive experiences as well?…”

Section: Resultsmentioning

confidence: 99%

“…Thus, it is interesting to wonder whether the discrepancy between the visual (target) and proprioceptive (arm position) state created by our passive intervention, might too have somehow engaged the cerebellar cortex with a prediction error (Popa & Ebner, 2019; Shadmehr et al, 2010). If true, the repeated experience of consistent prediction errors may have upregulated error sensitivity in the cerebellar cortex (Herzfeld et al, 2014; Albert et al, 2020), thus facilitating learning in the active condition. Alternatively, lingering changes in the somatosensory and motor cortices induced by passive movements may have indirectly altered cerebellar state throughout adaptation (as opposed to passive errors driving the cerebellar cortex directly).…”

Section: Discussionmentioning

confidence: 99%

“…On the other hand, when two consecutive perturbations oppose one another, learning during the second period is impaired due to anterograde interference (Brashers-Krug, Shadmehr, & Bizzi, 1996; Sing & Smith, 2010; Tong & Flanagan, 2003; Wigmore, Tong, & Flanagan, 2002). Current models have suggested that these history-dependent changes in learning rate are mediated by one’s sensitivity to error (Herzfeld et al, 2014; Albert et al, 2020). When two consecutive perturbations are similar, a given error causes more learning, resulting in savings.…”

Section: Introductionmentioning

confidence: 99%

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A conversion from slow to fast memory in response to passive motion

Javidialsaadi

Wang

2021

Preprint

Self Cite

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When the same perturbation is experienced consecutively, learning is accelerated on the second attempt. This savings is a central property of sensorimotor adaptation. Current models suggest that these improvements in learning are due to changes in the brain's sensitivity to error. Here, we tested whether these increases in error sensitivity could be facilitated by passive movement experiences. In each experimental group, the robot moved the arm passively in the direction that solved the upcoming rotation, but no visual feedback was provided. Then, following a break in time, participants adapted to a visuomotor rotation. Prior passive movements substantially improved motor learning, increasing total compensation in each group by approximately 30%. Similar to savings, a state-space model suggested that this improvement in learning was due to an increase in error sensitivity, but not memory retention. Thus, passive memories appeared to increase the motor learning system's sensitivity to error. However, some features in the observed behavior were not captured by this model, nor by similar empirical models, which assumed that learning was due a single exponential process. When we considered the possibility that learning was supported by parallel fast and slow adaptive processes, a striking pattern emerged; whereas initial improvements in learning were driven by a slower adaptive state, increases in error sensitivity gradually transferred to a faster learning system with the passage of time.

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“Leap before you look”: Conditions that suppress explicit, knowledge-based learning during visuomotor adaptation.

Savalia,

Cowell,

Huber

2024

Journal of Experimental Psychology: Human Perception and Perfor

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When learning a novel visuomotor mapping (e.g., mirror writing), accuracy can improve quickly through explicit, knowledge-based learning (e.g., aim left to go right), but after practice, implicit or procedural learning takes over, producing fast, natural movements. This procedural learning occurs automatically, whereas it has recently been found that knowledge-based learning can be suppressed by the gradual introduction of the novel mapping when participants must make fast movements and visuomotor perturbations are small (e.g., 30°rotations). We explored the range of task instructions, perturbation parameters, and feedback that preclude or encourage this suppression. Using a reaching task with a rotation between screen position and movement direction, we found that knowledge-based learning could be suppressed even for an extreme 90°rotation, but only if it was introduced gradually and only under instructions to move quickly. If the rotation was introduced abruptly or if instructions emphasized accuracy over speed, knowledge-based learning occurred. A second experiment indicated that knowledge-based learning always occurred in the absence of continuous motion feedback, evidenced by the time course of learning, the aftereffects of learning when the rotation was abruptly removed, and the outcome of formal model comparison between a dual-state (procedural and knowledge-based) versus a single-state (procedural only) learning model of the data. A third experiment replicated the findings and verified that the knowledge-based component of the dual-state model corresponded to explicit aiming, whereas the procedural component was slow to unlearn. Public Significance StatementSome situations require adaptation to a novel mapping between visual directions and motor directions, such as when attempting to cut one's own hair in the mirror. Prior results established that slowly learned procedural adaptation to a novel visuomotor mapping is automatic and always occurs. More recent results established that explicit, knowledge-based learning (e.g., a learned strategy to move left for a rightward target or to move south for a target located due east) can be suppressed by introducing the novel mapping gradually. The current study replicates this finding and demonstrates that this suppression can occur even for visuomotor remappings of large magnitude (a rotation of 90°). Importantly, it also establishes that this suppression does not occur when task instructions emphasize accuracy nor in the absence of continuous online visual feedback during motor actions.

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Competition between parallel sensorimotor learning systems

Cited by 26 publications

References 83 publications

Separation of multiple motor memories through implicit and explicit processes

Separation of multiple motor memories through implicit and explicit processes

A conversion from slow to fast memory in response to passive motion

“Leap before you look”: Conditions that suppress explicit, knowledge-based learning during visuomotor adaptation.

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