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Computational Neuroscience Journal Club

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James Heald will cover:

  • A Representation of Effort in Decision-Making and Motor Control
  • Reza Shadmehr, Helen Huang, Alaa Ahmed
  • Current Biology (July 2016)
  • Link to paper

ABSTRACT : Given two rewarding stimuli, animals tend to choose the more rewarding (or less effortful) option. However, they also move faster toward that stimulus [ 1–5 ]. This suggests that reward and effort not only affect decision-making, they also influence motor control [ 6, 7 ]. How does the brain compute the effort requirements of a task? Here, we considered data acquired during walking, reaching, flying, or isometric force production. In analyzing the decision-making and motor-control behaviors of various animals, we considered the possibility that the brain may estimate effort objectively, via the metabolic energy consumed to produce the action. We measured the energetic cost of reaching and found that, like walking, it was convex in time, with a global minimum, implying that there existed a movement speed that minimized effort. However, reward made it worthwhile to be energetically inefficient. Using a framework in which utility of an action depended on reward and energetic cost, both discounted in time, we found that it was possible to account for a body of data in which animals were free to choose how to move (reach slow or fast), as well as what to do (walk or fly, produce force F1 or F2). We suggest that some forms of decision-making and motor control may share a common utility in which the brain represents the effort associated with performing an action objectively via its metabolic energy cost and then, like reward, temporally discounts it as a function of movement duration.

This talk is part of the Computational Neuroscience series.

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