Individual differences in explicit and implicit visuomotor learning and working memory capacity

Christou, Antonios I.; Miall, R. Chris; McNab, Fiona; Galea, Joseph M.

doi:10.1038/srep36633

Cited by 97 publications

(122 citation statements)

References 34 publications

Supporting

Mentioning

104

Contrasting

Order By: Relevance

“…This result corroborates previous work, although the effect of cerebellar anodal tDCS on error compensation in response to the perturbation here was substantially weaker in comparison to the first study which did not control movement preparation time [46]. Recent attempts to replicate the effect of tDCS on visuomotor adaptation without constraining movement preparation time has shown only a moderate (cohen’s d = 0.6) effect of cerebellar anodal tDCS on error compensation in visuomotor adaptation: this effect size is consistent with the effect size shown in our dataset.…”

Section: Discussionsupporting

confidence: 92%

Cerebellar anodal tDCS increases implicit learning when strategic re-aiming is suppressed in sensorimotor adaptation

et al. 2017

View full text Add to dashboard Cite

Neurophysiological and neuroimaging work suggests that the cerebellum is critically involved in sensorimotor adaptation. Changes in cerebellar function alter behaviour when compensating for sensorimotor perturbations, as shown by non-invasive stimulation of the cerebellum and studies involving patients with cerebellar degeneration. It is known, however, that behavioural responses to sensorimotor perturbations reflect both explicit processes (such as volitional aiming to one side of a target to counteract a rotation of visual feedback) and implicit, error-driven updating of sensorimotor maps. The contribution of the cerebellum to these explicit and implicit processes remains unclear. Here, we examined the role of the cerebellum in sensorimotor adaptation to a 30° rotation of visual feedback of hand position during target-reaching, when the capacity to use explicit processes was manipulated by controlling movement preparation times. Explicit re-aiming was suppressed in one condition by requiring subjects to initiate their movements within 300ms of target presentation, and permitted in another condition by requiring subjects to wait approximately 1050ms after target presentation before movement initiation. Similar to previous work, applying anodal transcranial direct current stimulation (tDCS; 1.5mA) to the right cerebellum during adaptation resulted in faster compensation for errors imposed by the rotation. After exposure to the rotation, we evaluated implicit remapping in no-feedback trials after providing participants with explicit knowledge that the rotation had been removed. Crucially, movements were more adapted in these no-feedback trials following cerebellar anodal tDCS than after sham stimulation in both long and short preparation groups. Thus, cerebellar anodal tDCS increased implicit remapping during sensorimotor adaptation, irrespective of preparation time constraints. The results are consistent with the possibility that the cerebellum contributes to the formation of new visuomotor maps that correct perturbations in sensory feedback, even when explicit processes are suppressed during sensorimotor adaptation.

show abstract

Section: Discussionsupporting

confidence: 92%

Cerebellar anodal tDCS increases implicit learning when strategic re-aiming is suppressed in sensorimotor adaptation

et al. 2017

View full text Add to dashboard Cite

show abstract

“…Reducing shoulder muscle activity after shoulder fixation with instruction and feedback Many previous studies have investigated the role of explicit cognitive strategies in motor learning de Brouwer et al 2018;Christou et al 2016;Mazzoni and Krakauer 2006;McDougle et al 2015;Miyamoto et al 2020;Poh et al 2016;Rand and Rentsch 2015;Stark-Inbar et al 2017; . Regardless of the type of learning studied (i.e., visuomotor rotation, forcefield, etc.…”

Section: Discussionmentioning

confidence: 99%

Explicit feedback and instruction do not change shoulder muscle activity reduction after shoulder fixation

Maeda

Zdybal

Gribble

et al. 2020

Preprint

View full text Add to dashboard Cite

Generating pure elbow rotation requires contracting muscles at both the shoulder and elbow joints to counter torques that arise at the shoulder when the forearm rotates (i.e., intersegmental dynamics). Previous work has shown that human participants learn to reduce their shoulder muscle activity if the same elbow movement is performed after the shoulder joint is mechanically locked, which is appropriate because locking the shoulder joint eliminates the torques that arise at the shoulder when the forearm rotates. However, this learning is slow (i.e., it unfolds over hundreds of trials) and incomple te (i.e., shoulder activity is not fully eliminated). Here we investigated whether and how the addit ion of explicit strategies and biofeedback modulate this type of learning. Three groups of human participants (N = 55) performed voluntary pure elbow rotations using a robotic exoskeleton that permits shoulder and elbow rotation in a horizontal plane. Participants did the task with the shoulder free to move (baseline), then with the shoulder joint locked by the robotic manipulandum (adaptation), and then with the shoulder free to move again (post-adaptation). The first group of participants performed this protocol and received no instructions about what to do after their shoulder was locked. The second group of participants received visual feedback about their shoulder muscle activity after each movement and was instructed to reduce their shoulder activity to zero. The third group of participants also received visual biofeedback, but it was removed part way through the experiment. We found that, although all groups learned, the rate and magnitude of learning was not reliably different across the groups. Taken together, our results suggest that learning new arm dynamics, unlike other motor learning paradigms, unfolds independent of explicit instructions, biofeedback and task instructions.

show abstract

“…Likewise, considering the proposal of fast and slow processes underlying sensorimotor adaptation (Smith et al 2006; Trewartha et al 2014; Huberdeau et al 2015), higher variability might drive greater change in the fast process, while the slow process would be relatively immune to trial-by-trial variation (Baddeley et al 2003; Huang and Shadmehr 2009). Other possibilities are that individuals plan idiosyncratic trajectories, or differ in their ability to detect a mismatch between planned and executed trajectories, thus leading to different levels of adaptation (Kanai and Rees 2011; Seidler et al 2015; Raket et al 2016; Christou et al 2016). …”

Section: Introductionmentioning

confidence: 99%

Proprioceptive loss and the perception, control and learning of arm movements in humans: evidence from sensory neuronopathy

et al. 2018

Self Cite

View full text Add to dashboard Cite

It is uncertain how vision and proprioception contribute to adaptation of voluntary arm movements. In normal participants, adaptation to imposed forces is possible with or without vision, suggesting that proprioception is sufficient; in participants with proprioceptive loss (PL), adaptation is possible with visual feedback, suggesting that proprioception is unnecessary. In experiment 1 adaptation to, and retention of, perturbing forces were evaluated in three chronically deafferented participants. They made rapid reaching movements to move a cursor toward a visual target, and a planar robot arm applied orthogonal velocity-dependent forces. Trial-by-trial error correction was observed in all participants. Such adaptation has been characterized with a dual-rate model: a fast process that learns quickly, but retains poorly and a slow process that learns slowly and retains well. Experiment 2 showed that the PL participants had large individual differences in learning and retention rates compared to normal controls. Experiment 3 tested participants’ perception of applied forces. With visual feedback, the PL participants could report the perturbation’s direction as well as controls; without visual feedback, thresholds were elevated. Experiment 4 showed, in healthy participants, that force direction could be estimated from head motion, at levels close to the no-vision threshold for the PL participants. Our results show that proprioceptive loss influences perception, motor control and adaptation but that proprioception from the moving limb is not essential for adaptation to, or detection of, force fields. The differences in learning and retention seen between the three deafferented participants suggest that they achieve these tasks in idiosyncratic ways after proprioceptive loss, possibly integrating visual and vestibular information with individual cognitive strategies.

show abstract

Individual differences in explicit and implicit visuomotor learning and working memory capacity

Cited by 97 publications

References 34 publications

Cerebellar anodal tDCS increases implicit learning when strategic re-aiming is suppressed in sensorimotor adaptation

Cerebellar anodal tDCS increases implicit learning when strategic re-aiming is suppressed in sensorimotor adaptation

Explicit feedback and instruction do not change shoulder muscle activity reduction after shoulder fixation

Proprioceptive loss and the perception, control and learning of arm movements in humans: evidence from sensory neuronopathy

Contact Info

Product

Resources

About