A cerebellar population coding model for sensorimotor learning

Wang, Tianhe; Ivry, Richard B

doi:10.1101/2023.07.04.547720

Cited by 2 publications

(2 citation statements)

References 110 publications

(307 reference statements)

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“…For example, when participants are re-exposed to a perturbation after the system has been reset (i.e., a washout phase), implicit adaptation is attenuated [ 40 , 41 ]. We have proposed a neurophysiological-feasible model of the cerebellum in which contextual effects are an emergent property of the population activity of units that embody the rigid properties of the NLMC model [ 42 ]. The aggregate response of the system produces contextual effects due to persistence in the activation of the units, even though the learning parameters of the units themselves remain rigid.…”

Section: Discussionmentioning

confidence: 99%

Perturbation Variability Does Not Influence Implicit Sensorimotor Adaptation

Wang,

Avraham,

Tsay

et al. 2024

PLoS Comput Biol

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Implicit adaptation has been regarded as a rigid process that automatically operates in response to movement errors to keep the sensorimotor system precisely calibrated. This hypothesis has been challenged by recent evidence suggesting flexibility in this learning process. One compelling line of evidence comes from work suggesting that this form of learning is context-dependent, with the rate of learning modulated by error history. Specifically, learning was attenuated in the presence of perturbations exhibiting high variance compared to when the perturbation is fixed. However, these findings are confounded by the fact that the adaptation system corrects for errors of different magnitudes in a non-linear manner, with the adaptive response increasing in a proportional manner to small errors and saturating to large errors. Through simulations, we show that this non-linear motor correction function is sufficient to explain the effect of perturbation variance without referring to an experience-dependent change in error sensitivity. Moreover, by controlling the distribution of errors experienced during training, we provide empirical evidence showing that there is no measurable effect of perturbation variance on implicit adaptation. As such, we argue that the evidence to date remains consistent with the rigidity assumption.

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Section: Discussionmentioning

confidence: 99%

Perturbation Variability Does Not Influence Implicit Sensorimotor Adaptation

Wang,

Avraham,

Tsay

et al. 2024

PLoS Comput Biol

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“…However, by using methods that isolate the contribution of this recalibration process, we have found that implicit sensorimotor adaptation is actually attenuated during relearning (Avraham et al, 2021; see also Hamel et al, 2022, 2021; Leow et al, 2020; Stark-Inbar et al, 2016; Tsay et al, 2021b; Wang and Ivry, 2023; Yin and Wei, 2020). Savings, when observed in adaptation tasks, appears to largely reflect the operation of other learning processes such as the recall of a successful explicit strategy (Avraham et al, 2021; Haith et al, 2015; Huberdeau et al, 2019; Morehead et al, 2015).…”

Section: Introductionmentioning

confidence: 97%

Interference underlies attenuation upon relearning in sensorimotor adaptation

Avraham,

Ivry

2024

Preprint

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Savings refers to the gain in performance upon relearning a task. In sensorimotor adaptation, savings is tested by having participants adapt to perturbed feedback and, following a washout block during which the system resets to baseline, presenting the same perturbation again. While savings has been observed with these tasks, we have shown that the contribution from implicit sensorimotor adaptation, a process that uses sensory prediction errors to recalibrate the sensorimotor map, is actually attenuated upon relearning (Avraham et al., 2021). In the present study, we test the hypothesis that this attenuation is due to interference arising from the washout block, and more generally, from experience with a different relationship between the movement and the feedback. In standard adaptation studies, removing the perturbation at the start of the washout block results in a salient error signal in the opposite direction to that observed during learning. As a starting point, we replicated the finding that implicit adaptation is attenuated following a washout period in which the feedback now signals a salient opposite error. When we eliminated visual feedback during washout, implicit adaptation was no longer attenuated upon relearning, consistent with the interference hypothesis. Next, we eliminated the salient error during washout by gradually decreasing the perturbation, creating a scenario in which the perceived errors fell within the range associated with motor noise. Nonetheless, attenuation was still prominent. Inspired by this observation, we tested participants with an extended experience with veridical feedback during an initial baseline phase and found that this was sufficient to cause robust attenuation of implicit adaptation during the first exposure to the perturbation. This effect was context-specific: It did not generalize to movements that were not associated with the interfering feedback. Taken together, these results show that the implicit sensorimotor adaptation system is highly sensitive to memory interference from a recent experience with a discrepant action-outcome contingency.

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A cerebellar population coding model for sensorimotor learning

Cited by 2 publications

References 110 publications

Perturbation Variability Does Not Influence Implicit Sensorimotor Adaptation

Perturbation Variability Does Not Influence Implicit Sensorimotor Adaptation

Interference underlies attenuation upon relearning in sensorimotor adaptation

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