Review
Taking Aim at the Cognitive Side of Learning in Sensorimotor Adaptation Tasks

https://doi.org/10.1016/j.tics.2016.05.002Get rights and content

Trends

Behavioral, computational, and neuropsychological studies have provided a detailed picture of the processes involved in sensorimotor adaptation tasks.

Performance changes in response to perturbations are typically attributed to learning mechanisms that recalibrate a sensorimotor map based on the difference between predicted and observed feedback.

A growing body of research points to the operation of additional learning processes, including the use of strategies and heuristics that support flexible, goal-oriented behavior.

Theoretical models must address the interplay of these processes, specifying the algorithms and error signals used by different learning mechanisms.

Investigations of the neural substrates engaged during sensorimotor adaptation tasks should cast a wider net, looking beyond the cerebellum and motor cortex to regions involved in action selection.

Sensorimotor adaptation tasks have been used to characterize processes responsible for calibrating the mapping between desired outcomes and motor commands. Research has focused on how this form of error-based learning takes place in an implicit and automatic manner. However, recent work has revealed the operation of multiple learning processes, even in this simple form of learning. This review focuses on the contribution of cognitive strategies and heuristics to sensorimotor learning, and how these processes enable humans to rapidly explore and evaluate novel solutions to enable flexible, goal-oriented behavior. This new work points to limitations in current computational models, and how these must be updated to describe the conjoint impact of multiple processes in sensorimotor learning.

Section snippets

The Versatility of Human Motor Control

Flexible use of the upper limbs is fundamental to our species. The ability to manipulate objects with our hands, coupled with an expanding capacity to plan future states, was crucial for the survival of our ancestors [1]. Dexterous arm movements confer a tremendous advantage for efficiently harvesting foods in varied environments, as well as for manufacturing and manipulating tools. Indeed, Darwin argued that human ancestors’ use of thrown projectiles may have been an adaptation brought about

Using Multiple Learning Processes in Response to Sensorimotor Perturbations

The physics of the body and environment are in a continuous state of flux: not only do long-term changes arise from growth, development, and injury, but, in the short-term, muscles fatigue and sensory conditions fluctuate. The motor system must rapidly adjust to these variable conditions, and the ease with which we maintain calibration belies its computational complexity [29].

To study this calibration process, researchers have employed a variety of learning tasks–including prism adaptation 14,

Implications for Computational Models of Sensorimotor Learning

The field of sensorimotor learning has benefited from the development of rigorous computational models that not only account for observed behavioral results in healthy and neurologically impaired populations but also generate many testable predictions 18, 20, 46, 47. As noted in the introductory section, prevailing models of the canonical learning curve use algorithms that capture a gradient-descent reduction of error. The most prominent of such models is the two-parameter ‘state-space’ model

Neural Systems for Explicit Aiming and Implicit Recalibration

The notion that learning reflects the conjoint operation of multiple learning systems is prevalent in many cognitive domains such as category learning, recognition memory, and reinforcement learning 25, 26, 59. The work of Milner and colleagues with amnesic patient H.M. was, of course, highly influential in the development of memory taxonomies, and in particular the striking distinction between explicit, or declarative memory, and implicit, procedural memory 60, 61. Although the initial

Beyond Adaptation: Towards a Broader View of Motor Learning

Tools from statistical decision theory and Bayesian statistics may prove useful in developing descriptive models, as well as offering new ways to characterize mechanisms of motor learning 81, 82. Aiming locations could be thought of as (indirect) spatial goals, cached motor commands as action options, and the planning and execution of a specific command as an enacted decision. The honing of a true motor skill, as opposed to adaptation to an external perturbation, has been theorized to entail a

Concluding Remarks

Ultimately, it is crucial to incorporate the influence of cognitive planning into any realistic and comprehensive model of human sensorimotor learning. High-level motor planning is not only relevant to spearfishing, darts, or shooting: the ability to execute aimed movements–to rapidly, accurately, and flexibly perform planned, multi-joint movements to interact with the environment–is a hallmark of human behavior.

How should aiming strategies be modeled and integrated into standard models of

Acknowledgments

S.D.M was supported by the National Science Foundation Graduate Research Fellowship Program. R.B.I. was supported by National Institutes of Health grants NS074917 and NS092079. J.A.T. was supported by NS084948.

References (89)

  • M. Ito

    Neural design of the cerebellar motor control system

    Brain Res.

    (1972)
  • M. Ito

    Cerebellar learning in the vestibulo-ocular reflex

    Trends Cogn. Sci.

    (1998)
  • J.A. Taylor et al.

    Cerebellar and prefrontal cortex contributions to adaptation, strategies, and reinforcement learning

    Prog. Brain. Res.

    (2014)
  • D.M. Wolpert et al.

    Motor control is decision-making

    Curr. Opin. Neurobiol.

    (2012)
  • J. Trommershäuser

    Decision making, movement planning and statistical decision theory

    Trends Cogn. Sci.

    (2008)
  • D. Stout

    Neural correlates of Early Stone Age toolmaking: technology, language and cognition in human evolution

    Philos. Trans. R. Soc. Lond., B, Biol. Sci.

    (2008)
  • N.T. Roach

    Elastic energy storage in the shoulder and the evolution of high-speed throwing in Homo

    Nature

    (2013)
  • C. Darwin

    The Descent of Man, And Selection in Relation to Sex

    (1871)
  • J. Goodall

    Tool-using and aimed throwing in a community of free-living chimpanzees

    Nature

    (1964)
  • W.D. Hopkins

    The neural and cognitive correlates of aimed throwing in chimpanzees: a magnetic resonance image and behavioural study on a unique form of social tool use

    Philos. Trans. R. Soc. Lond., B, Biol. Sci.

    (2012)
  • R.S. Woodworth

    Accuracy of voluntary movement

    The Psychological Review: Monograph Supplements

    (1899)
  • P.M. Fitts

    The information capacity of the human motor system in controlling the amplitude of movement

    J. Exp. Psych.

    (1954)
  • R.A. Schmidt

    Motor-output variability: a theory for the accuracy of rapid motor acts

    Psychol. Rev.

    (1979)
  • D. Elliott

    A century later: Woodworth's (1899) two-component model of goal-directed aiming

    Psychol. Bull.

    (2001)
  • R. Shadmehr et al.

    Adaptive representation of dynamics during learning of a motor task

    J. Neurosci.

    (1994)
  • D.M. Wolpert

    An internal model for sensorimotor integration

    Science

    (1995)
  • M.J. Weiner

    Adaptation to lateral displacement of vision in patients with lesions of the central nervous system

    Neurology

    (1983)
  • T.A. Martin

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

    Brain

    (1996)
  • Y.W. Tseng

    Sensory prediction errors drive cerebellum-dependent adaptation of reaching

    J. Neurophysiol.

    (2007)
  • J. Izawa

    Cerebellar contributions to reach adaptation and learning sensory consequences of action

    J. Neurosci.

    (2012)
  • K. Rabe

    Adaptation to visuomotor rotation and force field perturbation is correlated to different brain areas in patients with cerebellar degeneration

    J. Neurophysiol.

    (2009)
  • K.A. Thoroughman et al.

    Learning of action through adaptive combination of motor primitives

    Nature

    (2000)
  • J-Y. Lee et al.

    Dual adaptation supports a parallel architecture of motor memory

    J. Neurosci.

    (2009)
  • M.A. Smith

    Interacting adaptive processes with different timescales underlie short-term motor learning

    PLoS Biol.

    (2006)
  • D.J. Herzfeld

    A memory of errors in sensorimotor learning

    Science

    (2014)
  • S. Cheng et al.

    Modeling sensorimotor learning with linear dynamical systems

    Neural Comput.

    (2006)
  • A. Newell et al.

    Mechanisms of skill acquisition and the law of practice

  • J.R. Morehead

    Savings upon re-aiming in visuomotor adaptation

    J. Neurosci.

    (2015)
  • F.G. Ashby

    A neuropsychological theory of multiple systems in category learning

    Psychol. Rev.

    (1998)
  • D.B. Willingham

    A neuropsychological theory of motor skill learning

    Psychol. Rev.

    (1998)
  • T.A. Martin

    Throwing while looking through prisms. II. Specificity and storage of multiple gaze-throw calibrations

    Brain

    (1996)
  • R. Shadmehr

    Error correction, sensory prediction, and adaptation in motor control

    Annu. Rev. Neurosci.

    (2010)
  • H.V. Helmholtz et al.

    Helmholtz's treatise on physiological optics

    (1924)
  • H.A. Cunningham

    Aiming error under transformed spatial mappings suggests a structure for visual-motor maps

    J. Exp. Psychol. Hum. Percept. Perform.

    (1989)
  • Cited by (134)

    View all citing articles on Scopus
    View full text