Concept: Expected value
People frequently change their preferences for options of gambles which they play once compared to those they play multiple times. In general, preferences for repeated play gambles are more consistent with the expected values of the options. According to the one-process view, the change in preference is due to a change in the structure of the gamble that is relevant to decision making. According to the two-process view, the change is attributable to a shift in the decision making strategy that is used. To adjudicate between these two theories, we asked participants to choose between gambles played once or 100 times, and to choose between them based on their expected value. Consistent with the two-process theory, we found a set of brain regions that were sensitive to the extent of behavioral change between single and aggregated play and also showed significant (de)activation in the expected value choice task. These results support the view that people change their decision making strategies for risky choice considered once or multiple times.
There is an unmet need for greater investment in preparedness against major epidemics and pandemics. The arguments in favour of such investment have been largely based on estimates of the losses in national incomes that might occur as the result of a major epidemic or pandemic. Recently, we extended the estimate to include the valuation of the lives lost as a result of pandemic-related increases in mortality. This produced markedly higher estimates of the full value of loss that might occur as the result of a future pandemic. We parametrized an exceedance probability function for a global influenza pandemic and estimated that the expected number of influenza-pandemic-related deaths is about 720 000 per year. We calculated that the expected annual losses from pandemic risk to be about 500 billion United States dollars - or 0.6% of global income - per year. This estimate falls within - but towards the lower end of - the Intergovernmental Panel on Climate Change’s estimates of the value of the losses from global warming, which range from 0.2% to 2% of global income. The estimated percentage of annual national income represented by the expected value of losses varied by country income grouping: from a little over 0.3% in high-income countries to 1.6% in lower-middle-income countries. Most of the losses from influenza pandemics come from rare, severe events.
Do economics students behave more selfishly than other students? Experiments involving monetary allocations suggest so. This article investigates the underlying motives for the economic students' more selfish behavior by separating three potential explanatory mechanisms: economics students are less concerned with fairness when making allocation decisions; have a different notion of what is fair in allocations; or are more skeptical about other people’s allocations, which in turn makes them less willing to comply with a shared fairness norm. The three mechanisms were tested by inviting students from various disciplines to participate in a relatively novel experimental game and asking all participants to give reasons for their choices. Compared with students of other disciplines, economics students were about equally likely to mention fairness in their comments; had a similar notion of what was fair in the situation; however, they expected lower offers, made lower offers, and were less willing to enforce compliance with a fair allocation at a cost to themselves. The economics students' lower expectations mediated their allocation decisions, suggesting that economics students behaved more selfishly because they expected others not to comply with the shared fairness norm.
- Proceedings of the National Academy of Sciences of the United States of America
- Published almost 6 years ago
The subjective well-being or happiness of individuals is an important metric for societies. Although happiness is influenced by life circumstances and population demographics such as wealth, we know little about how the cumulative influence of daily life events are aggregated into subjective feelings. Using computational modeling, we show that emotional reactivity in the form of momentary happiness in response to outcomes of a probabilistic reward task is explained not by current task earnings, but by the combined influence of recent reward expectations and prediction errors arising from those expectations. The robustness of this account was evident in a large-scale replication involving 18,420 participants. Using functional MRI, we show that the very same influences account for task-dependent striatal activity in a manner akin to the influences underpinning changes in happiness.
- Proceedings of the National Academy of Sciences of the United States of America
- Published over 2 years ago
The proportions of individuals involved in intergroup coalitional conflict, measured by war group size (W), conflict casualties ©, and overall group conflict deaths (G), have declined with respect to growing populations, implying that states are less violent than small-scale societies. We argue that these trends are better explained by scaling laws shared by both past and contemporary societies regardless of social organization, where group population (P) directly determines W and indirectly determines C and G. W is shown to be a power law function of P with scaling exponent X [demographic conflict investment (DCI)]. C is shown to be a power law function of W with scaling exponent Y [conflict lethality (CL)]. G is shown to be a power law function of P with scaling exponent Z [group conflict mortality (GCM)]. Results show that, while W/P and G/P decrease as expected with increasing P, C/W increases with growing W. Small-scale societies show higher but more variance in DCI and CL than contemporary states. We find no significant differences in DCI or CL between small-scale societies and contemporary states undergoing drafts or conflict, after accounting for variance and scale. We calculate relative measures of DCI and CL applicable to all societies that can be tracked over time for one or multiple actors. In light of the recent global emergence of populist, nationalist, and sectarian violence, our comparison-focused approach to DCI and CL will enable better models and analysis of the landscapes of violence in the 21st century.
There is general consensus that dopaminergic midbrain neurons signal reward prediction errors, computed as the difference between expected and received reward value. However, recent work in rodents shows that these neurons also respond to errors related to inferred value and sensory features, indicating an expanded role for dopamine beyond learning cached values. Here we utilize a transreinforcer reversal learning task and functional magnetic resonance imaging (fMRI) to test whether prediction error signals in the human midbrain are evoked when the expected identity of an appetitive food odor reward is violated, while leaving value matched. We found that midbrain fMRI responses to identity and value errors are correlated, suggesting a common neural origin for these error signals. Moreover, changes in reward-identity expectations, encoded in the orbitofrontal cortex (OFC), are directly related to midbrain activity, demonstrating that identity-based error signals in the midbrain support the formation of outcome identity expectations in OFC.
The present research examined when happy individuals' processing of a counterattitudinal message is guided by mood-congruent expectancies versus hedonic considerations. Recipients in positive, neutral, or negative mood read a strong or weak counterattitudinal message which either contained a threat to attitudinal freedom or did not contain such a threat. As expected, a freedom-threatening counterattitudinal message was more mood threatening than a counterattitudinal message not threatening freedom. Furthermore, as predicted by the mood-congruent expectancies approach, people in positive mood processed a nonthreatening counterattitudinal message more thoroughly than people in negative mood. Message processing in neutral mood lay in between. In contrast, as predicted by the hedonic-contingency view, a threatening counterattitudinal message was processed less thoroughly in positive mood than in neutral mood. In negative mood, processing of a threatening counterattitudinal message was as low as in positive mood. These findings suggest that message processing is determined by mood congruency unless hedonic considerations override expectancy-based processing inclinations.
In comparing multiple treatments, 2 error rates that have been studied extensively are the familywise and false discovery rates. Different methods are used to control each of these rates. Yet, it is rare to find studies that compare the same methods on both of these rates, and also on the per-family error rate, the expected number of false rejections. Although the per-family error rate and the familywise error rate are similar in most applications when the latter is controlled at a conventional low level (e.g., .05), the 2 measures can diverge considerably with methods that control the false discovery rate at that same level. Furthermore, we shall consider both rejections of true hypotheses (Type I errors) and rejections of false hypotheses where the observed outcomes are in the incorrect direction (Type III errors). We point out that power estimates based on the number of correct rejections do not consider the pattern of those rejections, which is important in interpreting the total outcome. The present study introduces measures of interpretability based on the pattern of separation of treatments into nonoverlapping sets and compares methods on these measures. In general, range-based (configural) methods are more likely to obtain interpretable patterns based on treatment separation than individual p-value-based measures. Recommendations for practice based on these results are given in the article. Although the article is complex, these recommendations can be understood without the necessity for detailed perusal of the supporting material. (PsycINFO Database Record © 2013 APA, all rights reserved).
The objective of this study was to assess the robustness of a novel test bolus (TB)-based computed tomographic angiography (CTA) contrast-enhancement-prediction (CEP) algorithm by retrospectively quantifying the systematic and random errors between the predicted and true enhancements.
The aim of this study was to evaluate the systematic and random errors of a new bolus tracking-based algorithm that predicts a patient-specific time of peak arterial enhancement and compare its performance with a best-case scenario for the current bolus tracking technique.