Sensitivity and Bias in Decision-Making under Risk: Evaluating the Perception of Reward, Its Probability and Value

Abstract

BackgroundThere are few clinical tools that assess decision-making under risk. Tests that characterize sensitivity and bias in decisions between prospects varying in magnitude and probability of gain may provide insights in conditions with anomalous reward-related behaviour.ObjectiveWe designed a simple test of how subjects integrate information about the magnitude and the probability of reward, which can determine discriminative thresholds and choice bias in decisions under risk.Design/MethodsTwenty subjects were required to choose between two explicitly described prospects, one with higher probability but lower magnitude of reward than the other, with the difference in expected value between the two prospects varying from 3 to 23%.ResultsSubjects showed a mean threshold sensitivity of 43% difference in expected value. Regarding choice bias, there was a ‘risk premium’ of 38%, indicating a tendency to choose higher probability over higher reward. An analysis using prospect theory showed that this risk premium is the predicted outcome of hypothesized non-linearities in the subjective perception of reward value and probability.ConclusionsThis simple test provides a robust measure of discriminative value thresholds and biases in decisions under risk. Prospect theory can also make predictions about decisions when subjective perception of reward or probability is anomalous, as may occur in populations with dopaminergic or striatal dysfunction, such as Parkinson's disease and schizophrenia.

Effect of experimental analogs of contingency management treatment on cocaine seeking behavior

“…We determined whether: (1) higher vs. lower magnitude predictable money reinforcement would decrease cocaine choice; and (2) probabilistic and predictable money reinforcement conditions equated for overall expected value would differentially alter cocaine choice. We predicted that fewer cocaine choices would be made with (1) higher vs. lower magnitude predictable money alternative, consistent with prior findings on the effect of non-drug magnitude on cocaine choice (Higgins et al, 1994a; Donny et al, 2003, 2004); and (2) higher vs. lower probability money reinforcement, consistent with findings that human subjects exhibit a predictability bias (Sharp et al, 2012). …”

“…Given that humans exhibit a predictability bias (Sharp et al, 2012) and that probability discounting is routinely observed in animals and human subjects (Green et al, 2010; Mobini et al, 2002; Rachlin et al, 1991), this was unanticipated. Several factors may explain this result.…”

Probability and magnitude evaluation in schizophrenia

“…We excluded one patient who performed poorer than 60% correct on catch trials (exclusion criteria from Sharp et al, 2012). Four patients and four controls did not show any deviation from responding by selecting the prospect with a higher probability of gain in every trial (Prospect 1).…”

“…1) and in Sharp et al (2012), we hypothesized that these deviations could be captured by taking into account variations in sensitivity to probability and magnitude. Alternate models separating out these effects of probability and magnitude were fitted (see Methods).…”

“…A second model (M2) included Prospect and Prelec function modifiers to reward magnitude and probability respectively (Sharp et al, 2012) that make non-linear adjustments to reward magnitude and probability to make them more consistent with the subjective appraisal of magnitude and probability (Kahneman and Tversky, 1979). The Prospect and Prelec functions adjusted reward magnitudes and probabilities such that:$\mathrm{italicSubjectiveMagnitude}=\mathrm{italicMagnitud}{e}^{0.57}$$\mathrm{italicSubjectiveProbability}=e^{\left(-{\left(-log\left(\mathit{Probability}\right)\right)}^{0.77}\right)}$…”