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Inside the brain of an elite athlete: the neural processes that support high achievement in sports

A Corrigendum to this article was published on 20 July 2009

Key Points

  • Elite athletes exhibit enhanced motor, perceptual and decision-making abilities developed over extensive periods of task-relevant practise.

  • Their motor acts are very precise, but are not confined to stereotypical kinematic patterns; it is the goal-relevant outcome that is controlled precisely, in line with current computational theories of motor control such as optimal feedback control.

  • Because sporting skills are highly complex and take years of practise, determining how learning is achieved in the setting of very delayed rewards represents a challenge for current theories of reinforcement learning.

  • The performance of expert athletes seems automatic, and often operates best in the absence of conscious control, but it is the level of performance, for example a new speed–accuracy trade-off, not automaticity per se, that defines expertise. The development of perceptual and motor skill correlates with structural changes in primary sensory and motor cortices, whereas functional imaging suggests a more efficient and focused use of neural resources across the brain.

  • Expert–novice paradigms suggest that athletes predict how events will unfold based on the movements of their opponents, and use these predictions to increase the speed and accuracy of their decisions.

  • The ability to make such predictions is consistent with the idea of a forward model that predicts the consequence of an opponent's actions.

  • The impressive ability of athletes to make good time-pressured decisions is compatible with recent models of motor decision making, which suggest that multiple motor acts are specified in parallel in sensorimotor regions of the cortex and compete through biased inhibitory connections to yield a single winning motor choice.

Abstract

Events like the World Championships in athletics and the Olympic Games raise the public profile of competitive sports. They may also leave us wondering what sets the competitors in these events apart from those of us who simply watch. Here we attempt to link neural and cognitive processes that have been found to be important for elite performance with computational and physiological theories inspired by much simpler laboratory tasks. In this way we hope to inspire neuroscientists to consider how their basic research might help to explain sporting skill at the highest levels of performance.

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Figure 1: The learning curve for skill acquisition.
Figure 2: Neural substrates of the affordance competition model.
Figure 3: Anticipatory information pickup by expert athletes.

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Acknowledgements

Peter Brown is supported by the Medical Research Council. John W. Krakauer is supported by NIH grant R01-052804. The authors thank Drs R. Shadmehr and Y. Niv for crucial comments on sections of the manuscript.

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Glossary

Mirror system

A network of premotor and parietal cortical areas that is activated by both the execution and the observation of action.

Policy

Defines the relationship between a state and the action to be taken.

Cost to go

The total cost remaining in the current trial. It is computed by combining expected rewards, end point variability, effort and other variables.

Degrees of freedom

The number of parameters needed to specify the posture of a mechanical linkage such as an arm.

Kinematic pattern

A description of the spatial position of body parts over time.

Execution noise

Random fluctuations in motor output that are not present in the central motor command.

Prism glasses

Lenses that distort the visual input received by the eyes, typically displacing it by a set amount.

Rotation adaptation

An experimental procedure in which artificial visual feedback (a hand position that is rotated by a constant amount relative to the true direction of hand movement) is presented during reaching movements.

Reward function

The relationship between a given state and its associated reward.

Value function

The total amount of reward over current and all future states.

Actor–critic architecture

A reinforcement learning model in which the policy structure (the actor) is separate from the value function (the critic).

Neural tuning

A function describing how a neuron modulates its firing rate as the variable that it is encoding changes; more precise tuning reflects modulation over a narrower range.

Corticospinal facilitation

Increased excitability of the corticospinal tract, measured using motor-evoked potentials.

VO2max

A measure of aerobic capacity: The maximum volume of oxygen that can be used in one minute of exhaustive exercise.

Spike-field coherence

A measure of frequency-specific shared variance between spiking activity and local field potentials, the latter provide a measure of synchronised synaptic potentials in a neural population.

Random-dot motion discrimination

A task in which observers view a set of short-lived dots moving in random directions and attempt to determine the direction of a subset of dots that move coherently.

Decision variable

A single quantity, reflecting the combination of prior judgements, current evidence and subjective costs and benefits, which is compared with a decision rule to produce a choice.

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Yarrow, K., Brown, P. & Krakauer, J. Inside the brain of an elite athlete: the neural processes that support high achievement in sports. Nat Rev Neurosci 10, 585–596 (2009). https://doi.org/10.1038/nrn2672

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