Throwing while looking through prisms: I. Focal olivocerebellar lesions impair adaptation

Martin, T. A.; Keating, J. G.; Goodkin, Howard P.; Bastian, Amy J.; Thach, W. T.

doi:10.1093/brain/119.4.1183

Cited by 596 publications

(482 citation statements)

References 36 publications

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“…Alternatively, subpopulations of neurons could have different tuning functions, but only select neurons, appropriate for the current environment, would participate in movements and adaptation. A candidate for contributing to selection among cortical neurons is the cerebellum, because it is necessary for visuomotor adaptation (Baizer and Glickstein, 1974;Martin et al, 1996) and has a unique structure (Marr, 1969) suitable for rapid adaptation of an internal model (Schweighofer et al, 1998a,b). This circuitry provides a likely mechanism for rapid fine-tuning of cortical networks by selectively gating those neurons that beneficially contribute to compensate for specific environments.…”

Section: Discussionmentioning

confidence: 99%

Rapid Reshaping of Human Motor Generalization

Thoroughman

Taylor

2005

J. Neurosci.

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People routinely learn how to manipulate new tools or make new movements. This learning requires the transformation of sensed movement error into updates of predictive neural control. Here, we demonstrate that the richness of motor training determines not only what we learn but how we learn. Human subjects made reaching movements while holding a robotic arm whose perturbing forces changed directions at the same rate, twice as fast, or four times as fast as the direction of movement, therefore exposing subjects to environments of increasing complexity across movement space. Subjects learned all three environments and learned the low-and medium-complexity environments equally well. We found that subjects lessened their movement-by-movement adaptation and narrowed the spatial extent of generalization to match the environmental complexity. This result demonstrated that people can rapidly reshape the transformation of sense into motor prediction to best learn a new movement task. We then modeled this adaptation using a neural network and found that, to mimic human behavior, the modeled neuronal tuning of movement space needed to narrow and reduce gain with increased environmental complexity. Prominent theories of neural computation have hypothesized that neuronal tuning of space, which determines generalization, should remained fixed during learning so that a combination of neuronal outputs can underlie adaptation simply and flexibly. Here, we challenge those theories with evidence that the neuronal tuning of movement space changed within minutes of training.

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Section: Discussionmentioning

confidence: 99%

Rapid Reshaping of Human Motor Generalization

Thoroughman

Taylor

2005

J. Neurosci.

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“…According to the alternative position, the cerebellum monitors and controls the execution of movements, and thus provides performance-related signals as a crucial prerequisite for adaptation. In support for the first view, cerebellar patients show adaptation deficits even when executing ballistic responses, which are too fast for online error monitoring (Deuschl et al 1996;Martin et al 1996;Maschke et al 2004;Tseng et al 2007). In support for the second view, cerebellar activation in healthy subjects is more closely associated with performance errors than with adaptive progress (Flament et al 1996).…”

Section: Introductionmentioning

confidence: 87%

“…The cerebellum has also been implicated in a more complex form of motor learning, namely, sensorimotor adaptation to visual and mechanical distortions. This view is supported by clinical studies, which found that adaptation is often reduced or abolished in patients with cerebellar disease (Deuschl et al 1996;Diedrichsen et al 2005;Gauthier et al 1979;Martin et al 1996;Maschke et al 2004;Tseng et al 2007;Weiner et al 1983). Further support comes from functional neuroimaging studies, which observed an increase of cerebellar activity during an adaptation task (e.g., Flament et al 1996;Graydon et al 2005;Imamizu et al 2000;Krakauer et al 2004;Krebs et al 1998;Lang et al 1988).…”

Section: Introductionmentioning

confidence: 91%

The effect of cerebellar cortical degeneration on adaptive plasticity and movement control

2008

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Clinical and neuroimaging studies provide converging evidence that the cerebellum plays an important role for sensorimotor adaptation by participating in the adaptive process per se, and/or by evaluating motor performance errors as a prerequisite for adaptation. Recent experimental evidence suggests that error signals pertinent to adaptation are related to sensory prediction rather than to online corrections (Tseng et al. in J Neurophysiol 98(1):54-62, 2007). To further elucidate the role of the cerebellum, the present study uses a multiple regression approach to separate out three independent determinants of adaptive success. Seventeen patients with cerebellar atrophy but without extra-cerebellar lesions, and 17 healthy, sex-and age-matched controls participated. Both subject groups performed center-out pointing movements before, during, and after exposure to 60°rotated visual feedback. From the registered data, we quantified four indicators of adaptive success (adaptive improvement, retention without feedback, intermanual transfer, and de-adaptation under normal feedback), as well as five measures of motor performance (reaction time, peak velocity, movement time, response variability, and ability for online error corrections). The variance of each adaptation indicator was then partitioned into three components, one related to subject group but not to motor performance, a second related to group and motor performance, and a third related to motor performance but not to group. In accordance with previous work, adaptation and motor performance were degraded in patients. The deficit was similar in magnitude for all four adaptation indicators, which suggests that adaptive recalibration rather than strategic control were affected in our patients. No adaptation indicator shared statistically significant variance with group alone; we therefore found no evidence for cerebellar circuitry dedicated to adaptation but not motor performance. Three indicators shared significant variance jointly with group and motor performance; this suggests that the cerebellar contribution to motor performance is related to adaptive success. All four indicators shared significant variance with motor performance alone; this indicates that extracerebellar contributions to motor performance are also related to adaptive success. In conclusion, our data support the view that neural structures inside and outside the cerebellum are processing motor performance-related signals as a prerequisite for adaptation, but provide no evidence for a cerebellar structure related exclusively to adaptation.

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“…A clue comes from the performance of patients with cerebellar disease on sensorimotor adaptation tasks. These patients are unable to compensate for large perturbations (Martin et al, 1996; Rabe et al, 2009; Criscimagna-Hemminger et al, 2010). It would appear that, for these individuals, self-generated exploration is insufficient for solving such tasks (Vaca-Palomares et al, 2013); they must be given the explicit strategy (Taylor et al, 2010).…”

Section: The Nature Of Explicit Learningmentioning

confidence: 99%

Explicit and Implicit Contributions to Learning in a Sensorimotor Adaptation Task

Taylor¹,

2014

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Visuomotor adaptation has been thought to be an implicit process that results when a sensory-prediction error signal is used to update a forward model. A striking feature of human competence is the ability to receive verbal instructions and employ strategies to solve tasks; such explicit processes could be used during visuomotor adaptation. Here, we used a novel task design that allowed us to obtain continuous verbal reports of aiming direction while participants learned a visuomotor rotation. We had two main hypotheses: the contribution of explicit learning would be modulated by instruction and the contribution of implicit learning would be modulated by the form of error feedback. By directly assaying aiming direction, we could identify the time course of the explicit component and, via subtraction, isolate the implicit component of learning. There were marked differences in the time courses of explicit and implicit contributions to learning. Explicit learning, driven by target error, was achieved by initially large then smaller explorations of aiming direction biased toward the correct solution. In contrast, implicit learning, driven by a sensory-prediction error, was slow and monotonic. Continuous error feedback reduced the amplitude of explicit learning and increased the contribution of implicit learning. The presence of instruction slightly increased the rate of initial learning and only had a subtle effect on implicit learning. We conclude that visuomotor adaptation, even in the absence of instruction, results from the interplay between explicit learning driven by target error and implicit learning of a forward model driven by prediction error.

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Throwing while looking through prisms: I. Focal olivocerebellar lesions impair adaptation

Cited by 596 publications

References 36 publications

Rapid Reshaping of Human Motor Generalization

Rapid Reshaping of Human Motor Generalization

The effect of cerebellar cortical degeneration on adaptive plasticity and movement control

Explicit and Implicit Contributions to Learning in a Sensorimotor Adaptation Task

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