The Neural Correlates of Subjective Utility of Monetary Outcome and Probability Weight in Economic and in Motor Decision under Risk

Wu, Shih-Wei; Delgado, Mauricio R.; Maloney, Laurence T.

doi:10.1523/jneurosci.0540-11.2011

Cited by 58 publications

(82 citation statements)

References 44 publications

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“…The results thus appear to replicate the description-experience gap (14, 15) § § and to replicate previous results comparing low-level decisions to classical ones (20,34, but see ref. 35).…”

supporting

confidence: 86%

“…The second noteworthy trend is that, consistent with studies that look at individual differences (20,34,36), parameter estimates were highly variable. Some participants appear near optimal with near-linear probability weights, whereas others show severe underor overweighting.…”

supporting

confidence: 61%

“…The description-experience gap is typically evaluated under the assumption that objective probabilities correspond to subjective probabilities (16,29,30), {{ and perceptuo-motor studies have typically assumed the same (20,34,37). Sometimes this assumption is tested (29), and other times it is not (30).…”

Section: Do People Deviate From Optimality When Biases Are Taken Intomentioning

confidence: 99%

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Perceptuo-motor, cognitive, and description-based decision-making seem equally good

Jarvstad

Hahn

Rushton

et al. 2013

Proc. Natl. Acad. Sci. U.S.A.

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Classical studies suggest that high-level cognitive decisions (e.g., choosing between financial options) are suboptimal. In contrast, low-level decisions (e.g., choosing where to put your feet on a rocky ridge) appear near-optimal: the perception-cognition gap. Moreover, in classical tasks, people appear to put too much weight on unlikely events. In contrast, when people can learn through experience, they appear to put too little weight on unlikely events: the description-experience gap. We eliminated confounding factors and, contrary to what is commonly believed, found results suggesting that (i) the perception-cognition gap is illusory and due to differences in the way performance is assessed; (ii) the description-experience gap arises from the assumption that objective probabilities match subjective ones; (iii) people's ability to make decisions is better than the classical literature suggests; and (iv) differences between decision-makers are more important for predicting peoples' choices than differences between choice tasks.

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supporting

confidence: 86%

supporting

confidence: 61%

Section: Do People Deviate From Optimality When Biases Are Taken Intomentioning

confidence: 99%

See 1 more Smart Citation

Perceptuo-motor, cognitive, and description-based decision-making seem equally good

Jarvstad

Hahn

Rushton

et al. 2013

Proc. Natl. Acad. Sci. U.S.A.

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“…These regions comprised ROIs in the ventromedial prefrontal cortex [vmPFC; 575 contiguous voxels, maximum z-stat at 4, 50, Ϫ2 (MNI)], the posterior cingulate cortex [pCC; 257 contiguous voxels, maximum z-stat at 0, Ϫ32, 32 (MNI)], and also an ROI in the left inferior frontal lobe [liPFC; 23 contiguous voxels, maximum z-stat at Ϫ34, 54, Ϫ8 (MNI)]. The vmPFC and pCC both have been linked to the subjective utility of monetary outcomes of risky choices (Wu et al 2011), and the liPFC has been associated with neural representations of loss aversion (Tom et al 2007).…”

Section: Fmri Data Analysismentioning

confidence: 99%

Intelligence moderates neural responses to monetary reward and punishment

Hawes

DeYoung

Gray

et al. 2014

Journal of Neurophysiology

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Hawes DR, DeYoung CG, Gray JR, Rustichini A. Intelligence moderates neural responses to monetary reward and punishment. J Neurophysiol 111: 1823-1832, 2014. First published February 12, 2014 doi:10.1152/jn.00393.2013The relations between intelligence (IQ) and neural responses to monetary gains and losses were investigated in a simple decision task. In 94 healthy adults, typical responses of striatal blood oxygen level-dependent (BOLD) signal after monetary reward and punishment were weaker for subjects with higher IQ. IQ-moderated differential responses to gains and losses were also found for regions in the medial prefrontal cortex, posterior cingulate cortex, and left inferior frontal cortex. These regions have previously been identified with the subjective utility of monetary outcomes. Analysis of subjects' behavior revealed a correlation between IQ and the extent to which choices were related to experienced decision outcomes in preceding trials. Specifically, higher IQ predicted behavior to be more strongly correlated with an extended period of previously experienced decision outcomes, whereas lower IQ predicted behavior to be correlated exclusively to the most recent decision outcomes. We link these behavioral and imaging findings to a theoretical model capable of describing a role for intelligence during the evaluation of rewards generated by unknown probabilistic processes. Our results demonstrate neural differences in how people of different intelligence respond to experienced monetary rewards and punishments. Our theoretical discussion offers a functional description for how these individual differences may be linked to choice behavior. Together, our results and model support the hypothesis that observed correlations between intelligence and preferences may be rooted in the way decision outcomes are experienced ex post, rather than deriving exclusively from how choices are evaluated ex ante.

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“…Humans are highly capable of tracking the value of stimuli, varying their behavior on the basis of reinforcement history (1,2), and exhibiting sensitivity to intrinsic motor noise when reward outcomes depend on movement accuracy (3)(4)(5). In real-world behavior, the underlying cause of unrewarded events is often ambiguous: A lost point in tennis could occur because the player made a poor choice about where to hit the ball or failed to properly execute the stroke.…”

mentioning

confidence: 99%

Credit assignment in movement-dependent reinforcement learning

McDougle

Boggess

Crossley

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

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When a person fails to obtain an expected reward from an object in the environment, they face a credit assignment problem: Did the absence of reward reflect an extrinsic property of the environment or an intrinsic error in motor execution? To explore this problem, we modified a popular decision-making task used in studies of reinforcement learning, the two-armed bandit task. We compared a version in which choices were indicated by key presses, the standard response in such tasks, to a version in which the choices were indicated by reaching movements, which affords execution failures. In the key press condition, participants exhibited a strong risk aversion bias; strikingly, this bias reversed in the reaching condition. This result can be explained by a reinforcement model wherein movement errors influence decision-making, either by gating reward prediction errors or by modifying an implicit representation of motor competence. Two further experiments support the gating hypothesis. First, we used a condition in which we provided visual cues indicative of movement errors but informed the participants that trial outcomes were independent of their actual movements. The main result was replicated, indicating that the gating process is independent of participants' explicit sense of control. Second, individuals with cerebellar degeneration failed to modulate their behavior between the key press and reach conditions, providing converging evidence of an implicit influence of movement error signals on reinforcement learning. These results provide a mechanistically tractable solution to the credit assignment problem.decision-making | reinforcement learning | sensory prediction error | reward prediction error | cerebellum W hen a diner reaches across the table and knocks over her coffee, the absence of anticipated reward should be attributed to a failure of coordination rather than diminish her love of coffee. Although this attribution is intuitive, current models of decision-making lack a mechanistic explanation for this seemingly simple computation. We set out to ask if, and how, selection processes in decision-making incorporate information specific to action execution and thus solve the credit assignment problem that arises when an expected reward is not obtained because of a failure in motor execution.Humans are highly capable of tracking the value of stimuli, varying their behavior on the basis of reinforcement history (1, 2), and exhibiting sensitivity to intrinsic motor noise when reward outcomes depend on movement accuracy (3-5). In real-world behavior, the underlying cause of unrewarded events is often ambiguous: A lost point in tennis could occur because the player made a poor choice about where to hit the ball or failed to properly execute the stroke. However, in laboratory studies of reinforcement learning, the underlying cause of unrewarded events is typically unambiguous, either solely dependent on properties of the stimulus or on motor noise. Thus, it remains unclear how people assign credit to either extrins...

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The Neural Correlates of Subjective Utility of Monetary Outcome and Probability Weight in Economic and in Motor Decision under Risk

Cited by 58 publications

References 44 publications

Perceptuo-motor, cognitive, and description-based decision-making seem equally good

Perceptuo-motor, cognitive, and description-based decision-making seem equally good

Intelligence moderates neural responses to monetary reward and punishment

Credit assignment in movement-dependent reinforcement learning

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