2015年7月15日水曜日

Reward Pays the Cost of Noise Reduction in Motor and Cognitive Control

Sanjay G. Manohar, Trevor T.-J. Chong, Matthew A.J. Apps, Amit Batla, Maria Stamelou, Paul R. Jarman, Kailash P. Bhatia, Masud Husain

Current Biology
Volume 25, Issue 13, p1707–1716, 29 June 2015

報酬を与えることで、被験者は(コストを掛けて)運動/知覚のノイズを軽減し、それが運動のスピードと正確さの両方を改善する。

Speed-accuracy trade-off is an intensively studied law governing almost all behavioral tasks across species. Here we show that motivation by reward breaks this law, by simultaneously invigorating movement and improving response precision. We devised a model to explain this paradoxical effect of reward by considering a new factor: the cost of control. Exerting control to improve response precision might itself come at a cost—a cost to attenuate a proportion of intrinsic neural noise. Applying a noise-reduction cost to optimal motor control predicted that reward can increase both velocity and accuracy. Similarly, application to decision-making predicted that reward reduces reaction times and errors in cognitive control. We used a novel saccadic distraction task to quantify the speed and accuracy of both movements and decisions under varying reward. Both faster speeds and smaller errors were observed with higher incentives, with the results best fitted by a model including a precision cost. Recent theories consider dopamine to be a key neuromodulator in mediating motivational effects of reward. We therefore examined how Parkinson’s disease (PD), a condition associated with dopamine depletion, alters the effects of reward. Individuals with PD showed reduced reward sensitivity in their speed and accuracy, consistent in our model with higher noise-control costs. Including a cost of control over noise explains how reward may allow apparent performance limits to be surpassed. On this view, the pattern of reduced reward sensitivity in PD patients can specifically be accounted for by a higher cost for controlling noise.

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