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

Manohar SG, Chong TT, Apps MA, Batla A, Stamelou M, Jarman PR, Bhatia KP, Husain M - Curr. Biol. (2015)

Bottom Line: 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.On this view, the pattern of reduced reward sensitivity in PD patients can specifically be accounted for by a higher cost for controlling noise.

View Article: PubMed Central - PubMed

Affiliation: Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, Oxford OX3 9DU, UK; Department of Experimental Psychology, University of Oxford, Oxford OX1 3UD, UK; Institute of Neurology, University College London, London WC1N 3BG, UK; Institute of Cognitive Neuroscience, University College London, London WC1N 3AR, UK; National Hospital for Neurology and Neurosurgery, Queen Square, London WC1N 3BG, UK. Electronic address: sanjay.manohar@ndcn.ox.ac.uk.

No MeSH data available.


Related in: MedlinePlus

Oculomotor Capture Task with Trial-wise Incentives(A) Three equidistant discs were dimly illuminated. At the start of each trial, participants had to fixate one disc, which was brightened. A recorded voice gave an auditory reward cue of “0p maximum,” “10p maximum,” or “50p maximum,” which indicated the maximum amount of money that could be won if participants were fast to look at the target on that trial. After a variable foreperiod, the other two discs were illuminated asynchronously, with a delay of 40 to 120 ms. Participants were instructed to look as fast as possible to the second disc. Thus, the first onset acted as an early onset distractor, and the second disc indicated the target.(B) After gaze arrived at the target, participants were rewarded according to reaction time. Reward was calculated as a fraction of the maximum available, using an exponential falloff. The falloff was determined adaptively using quantiles of the last 20 trials, in order to maintain the difficulty level over the course of the experiment.(C) On approximately 30% of trials, gaze was “captured” by the distractor (errors), resulting in a brief saccade to the first disc, followed by a corrective saccade to the target. The trajectory of gaze was classified according to whether the first saccade terminated on the target or on the distractor. Correct trials exhibited a variety of curvatures; each trial is colored according to the initial direction of the eye velocity.(D) The task provided four measures of performance. Both speed and accuracy could be examined for motor execution of the saccade and for selection of the correct target.
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fig5: Oculomotor Capture Task with Trial-wise Incentives(A) Three equidistant discs were dimly illuminated. At the start of each trial, participants had to fixate one disc, which was brightened. A recorded voice gave an auditory reward cue of “0p maximum,” “10p maximum,” or “50p maximum,” which indicated the maximum amount of money that could be won if participants were fast to look at the target on that trial. After a variable foreperiod, the other two discs were illuminated asynchronously, with a delay of 40 to 120 ms. Participants were instructed to look as fast as possible to the second disc. Thus, the first onset acted as an early onset distractor, and the second disc indicated the target.(B) After gaze arrived at the target, participants were rewarded according to reaction time. Reward was calculated as a fraction of the maximum available, using an exponential falloff. The falloff was determined adaptively using quantiles of the last 20 trials, in order to maintain the difficulty level over the course of the experiment.(C) On approximately 30% of trials, gaze was “captured” by the distractor (errors), resulting in a brief saccade to the first disc, followed by a corrective saccade to the target. The trajectory of gaze was classified according to whether the first saccade terminated on the target or on the distractor. Correct trials exhibited a variety of curvatures; each trial is colored according to the initial direction of the eye velocity.(D) The task provided four measures of performance. Both speed and accuracy could be examined for motor execution of the saccade and for selection of the correct target.

Mentions: To test our theory and quantify how reward can make us apparently “more optimal,” we devised a novel saccadic task in which participants have to look toward a target quickly, while avoiding a salient early-onset distractor (Figure 5). The velocity of a saccade has often been regarded as rigidly determined by its amplitude [26–28], until recent studies demonstrated modulation by reward [4, 14, 16]. In our experiment, by manipulating incentives on each trial, we measured exactly how reward increases saccade velocity (speed) and endpoint accuracy. Furthermore, we were able to separately index cognitive control by measuring errors to the distractor and their relation to RT. Our model accounted well for the observed behavior.


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

Manohar SG, Chong TT, Apps MA, Batla A, Stamelou M, Jarman PR, Bhatia KP, Husain M - Curr. Biol. (2015)

Oculomotor Capture Task with Trial-wise Incentives(A) Three equidistant discs were dimly illuminated. At the start of each trial, participants had to fixate one disc, which was brightened. A recorded voice gave an auditory reward cue of “0p maximum,” “10p maximum,” or “50p maximum,” which indicated the maximum amount of money that could be won if participants were fast to look at the target on that trial. After a variable foreperiod, the other two discs were illuminated asynchronously, with a delay of 40 to 120 ms. Participants were instructed to look as fast as possible to the second disc. Thus, the first onset acted as an early onset distractor, and the second disc indicated the target.(B) After gaze arrived at the target, participants were rewarded according to reaction time. Reward was calculated as a fraction of the maximum available, using an exponential falloff. The falloff was determined adaptively using quantiles of the last 20 trials, in order to maintain the difficulty level over the course of the experiment.(C) On approximately 30% of trials, gaze was “captured” by the distractor (errors), resulting in a brief saccade to the first disc, followed by a corrective saccade to the target. The trajectory of gaze was classified according to whether the first saccade terminated on the target or on the distractor. Correct trials exhibited a variety of curvatures; each trial is colored according to the initial direction of the eye velocity.(D) The task provided four measures of performance. Both speed and accuracy could be examined for motor execution of the saccade and for selection of the correct target.
© Copyright Policy - CC BY
Related In: Results  -  Collection

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fig5: Oculomotor Capture Task with Trial-wise Incentives(A) Three equidistant discs were dimly illuminated. At the start of each trial, participants had to fixate one disc, which was brightened. A recorded voice gave an auditory reward cue of “0p maximum,” “10p maximum,” or “50p maximum,” which indicated the maximum amount of money that could be won if participants were fast to look at the target on that trial. After a variable foreperiod, the other two discs were illuminated asynchronously, with a delay of 40 to 120 ms. Participants were instructed to look as fast as possible to the second disc. Thus, the first onset acted as an early onset distractor, and the second disc indicated the target.(B) After gaze arrived at the target, participants were rewarded according to reaction time. Reward was calculated as a fraction of the maximum available, using an exponential falloff. The falloff was determined adaptively using quantiles of the last 20 trials, in order to maintain the difficulty level over the course of the experiment.(C) On approximately 30% of trials, gaze was “captured” by the distractor (errors), resulting in a brief saccade to the first disc, followed by a corrective saccade to the target. The trajectory of gaze was classified according to whether the first saccade terminated on the target or on the distractor. Correct trials exhibited a variety of curvatures; each trial is colored according to the initial direction of the eye velocity.(D) The task provided four measures of performance. Both speed and accuracy could be examined for motor execution of the saccade and for selection of the correct target.
Mentions: To test our theory and quantify how reward can make us apparently “more optimal,” we devised a novel saccadic task in which participants have to look toward a target quickly, while avoiding a salient early-onset distractor (Figure 5). The velocity of a saccade has often been regarded as rigidly determined by its amplitude [26–28], until recent studies demonstrated modulation by reward [4, 14, 16]. In our experiment, by manipulating incentives on each trial, we measured exactly how reward increases saccade velocity (speed) and endpoint accuracy. Furthermore, we were able to separately index cognitive control by measuring errors to the distractor and their relation to RT. Our model accounted well for the observed behavior.

Bottom Line: 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.On this view, the pattern of reduced reward sensitivity in PD patients can specifically be accounted for by a higher cost for controlling noise.

View Article: PubMed Central - PubMed

Affiliation: Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, Oxford OX3 9DU, UK; Department of Experimental Psychology, University of Oxford, Oxford OX1 3UD, UK; Institute of Neurology, University College London, London WC1N 3BG, UK; Institute of Cognitive Neuroscience, University College London, London WC1N 3AR, UK; National Hospital for Neurology and Neurosurgery, Queen Square, London WC1N 3BG, UK. Electronic address: sanjay.manohar@ndcn.ox.ac.uk.

No MeSH data available.


Related in: MedlinePlus