Finance - Research Publications
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ItemCaloric Primary Rewards Systematically Alter Time Perception(American Psychological Association, 2017-11-01)Human time perception can be influenced by contextual factors, such as the presence of reward. Yet, the exact nature of the relationship between time perception and reward has not been conclusively characterized. We implemented a novel experimental paradigm to measure estimations of time across a range of suprasecond intervals, during the anticipation and after the consumption of fruit juice, a physiologically relevant primary reward. We show that average time estimations were systematically affected by the consumption of reward, but not by the anticipation of reward. Compared with baseline estimations of time, reward consumption was associated with subsequent overproductions of time, and this effect increased for larger magnitudes of reward. Additional experiments demonstrated that the effect of consumption did not extend to a secondary reward (money), a tasteless, noncaloric primary reward (water), or a sweet, noncaloric reward (aspartame). However, a tasteless caloric reward (maltodexrin) did induce overproductions of time, although this effect did not scale with reward magnitude. These results suggest that the consumption of caloric primary rewards can alter time perception, which may be a psychophysiological mechanism by which organisms regulate homeostatic balance.
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ItemEndogenous formation of preferences: Choices systematically change willingness-to-pay for goods(American Psychological Association, 2017-12)Standard decision theory assumes that choices result from stable preferences. This position has been challenged by claims that the act of choosing between goods may alter preferences. To test this claim, we investigated in three experiments whether choices between equally valued snack food items can systematically shape preferences. We directly assessed changes in participants’ willingness-to-pay for these items, some of which could be bought at an auction after the experiment, while others could not. We found that chosen items were valued higher, and nonchosen items were valued lower; yet this postdecisional refinement of preferences was only observed for choices and valuations that were relevant, that is, incentive-compatible for items that were available for consumption. Supplementary analyses revealed that incentive-incompatible elicitations of preferences were unreliable and may have masked potential effects of choices on preferences. In conclusion, we propose that preferences can change endogenously, that is, in the absence of external feedback or information, but rather as a function of previous relevant choices.
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ItemDissociating neural variability related to stimulus quality and response times in perceptual decision-making(Elsevier, 2018-03-01)According to sequential sampling models, perceptual decision-making is based on accumulation of noisy evidence towards a decision threshold. The speed with which a decision is reached is determined by both the quality of incoming sensory information and random trial-by-trial variability in the encoded stimulus representations. To investigate those decision dynamics at the neural level, participants made perceptual decisions while functional magnetic resonance imaging (fMRI) was conducted. On each trial, participants judged whether an image presented under conditions of high, medium, or low visual noise showed a piano or a chair. Higher stimulus quality (lower visual noise) was associated with increased activation in bilateral medial occipito-temporal cortex and ventral striatum. Lower stimulus quality was related to stronger activation in posterior parietal cortex (PPC) and dorsolateral prefrontal cortex (DLPFC). When stimulus quality was fixed, faster response times were associated with a positive parametric modulation of activation in medial prefrontal and orbitofrontal cortex, while slower response times were again related to more activation in PPC, DLPFC and insula. Our results suggest that distinct neural networks were sensitive to the quality of stimulus information, and to trial-to-trial variability in the encoded stimulus representations, but that reaching a decision was a consequence of their joint activity.
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ItemHealth warnings promote healthier dietary decision making: Effects of positive versus negative message framing and graphic versus text-based warnings(Elsevier, 2018-08-01)Food product health warnings have been proposed as a potential obesity prevention strategy. This study examined the effects of text-only and text-and-graphic, negatively and positively framed health warnings on dietary choice behavior. In a 2 × 5 mixed experimental design, 96 participants completed a dietary self-control task. After providing health and taste ratings of snack foods, participants completed a baseline measure of dietary self-control, operationalized as participants' frequency of choosing healthy but not tasty items and rejecting unhealthy yet tasty items to consume at the end of the experiment. Participants were then randomly assigned to one of five health warning groups and presented with 10 health warnings of a given form: text-based, negative framing; graphic, negative framing; text, positive framing; graphic, positive framing; or a no warning control. Participants then completed a second dietary decision making session to determine whether health warnings influenced dietary self-control. Linear mixed effects modeling revealed a significant interaction between health warning group and decision stage (pre- and post-health warning presentation) on dietary self-control. Negatively framed graphic health warnings promoted greater dietary self-control than other health warnings. Negatively framed text health warnings and positively framed graphic health warnings promoted greater dietary self-control than positively framed text health warnings and control images, which did not increase dietary self-control. Overall, HWs primed healthier dietary decision making behavior, with negatively framed graphic HWs being most effective. Health warnings have potential to become an important element of obesity prevention.
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ItemHard Decisions Shape the Neural Coding of Preferences(Society for Neuroscience, 2019-01-23)Hard decisions between equally valued alternatives can result in preference changes, meaning that subsequent valuations for chosen items increase and decrease for rejected items. Previous research suggests that this phenomenon is a consequence of cognitive dissonance reduction after the decision, induced by the mismatch between initial preferences and decision outcomes. In contrast, this functional magnetic resonance imaging and eye-tracking study with male and female human participants found that preferences are already updated online during the process of decision-making. Preference changes were predicted from activity in left dorsolateral prefrontal cortex and precuneus while making hard decisions. Fixation durations during this phase predicted both choice outcomes and subsequent preference changes. These preference adjustments became behaviorally relevant only for choices that were remembered and were in turn associated with hippocampus activity. Our results suggest that preferences evolve dynamically as decisions arise, potentially as a mechanism to prevent stalemate situations in underdetermined decision scenarios.
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ItemMeasuring the Adequacy of Retirement Savings(Wiley, 2018-12-01)This paper introduces four metrics for quantifying the adequacy of retirement savings, taking into account all major sources of retirement income. We then apply them to projections of expected future retirement income streams of a representative sample of the Australian population aged 40 and above. We find that omitting one or more pillars of savings significantly biases estimates of retirement savings adequacy. We also find that the four metrics are only weakly correlated with key commonly used indicators of financial well‐being, in particular current income and net worth. Our analysis also points to several shortcomings of the widely used income replacement ratio as an indicator of savings adequacy.
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ItemMonetary feedback modulates performance and electrophysiological indices of belief updating in reward learning.(Wiley, 2019-07-05)Belief updating entails the incorporation of new information about the environment into internal models of the world. Bayesian inference is the statistically optimal strategy for performing belief updating in the presence of uncertainty. An important open question is whether the use of cognitive strategies that implement Bayesian inference is dependent upon motivational state and, if so, how this is reflected in electrophysiological signatures of belief updating in the brain. Here, we recorded the EEG of participants performing a simple reward learning task with both monetary and nonmonetary instructive feedback conditions. Our aim was to distinguish the influence of the rewarding properties of feedback on belief updating from the information content of the feedback itself. A Bayesian updating model allowed us to quantify different aspects of belief updating across trials, including the size of belief updates and the uncertainty of beliefs. Faster learning rates were observed in the monetary feedback condition compared to the instructive feedback condition, while belief updates were generally larger, and belief uncertainty smaller, with monetary compared to instructive feedback. Larger amplitudes in the monetary feedback condition were found for three ERP components: the P3a, the feedback-related negativity, and the late positive potential. These findings suggest that motivational state influences inference strategies in reward learning, and this is reflected in the electrophysiological correlates of belief updating.
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ItemThe anticipation and outcome phases of reward and loss processing: A neuroimaging meta-analysis of the monetary incentive delay task(WILEY, 2018-08-01)The processing of rewards and losses are crucial to everyday functioning. Considerable interest has been attached to investigating the anticipation and outcome phases of reward and loss processing, but results to date have been inconsistent. It is unclear if anticipation and outcome of a reward or loss recruit similar or distinct brain regions. In particular, while the striatum has widely been found to be active when anticipating a reward, whether it activates in response to the anticipation of losses as well remains ambiguous. Furthermore, concerning the orbitofrontal/ventromedial prefrontal regions, activation is often observed during reward receipt. However, it is unclear if this area is active during reward anticipation as well. We ran an Activation Likelihood Estimation meta-analysis of 50 fMRI studies, which used the Monetary Incentive Delay Task (MIDT), to identify which brain regions are implicated in the anticipation of rewards, anticipation of losses, and the receipt of reward. Anticipating rewards and losses recruits overlapping areas including the striatum, insula, amygdala and thalamus, suggesting that a generalised neural system initiates motivational processes independent of valence. The orbitofrontal/ventromedial prefrontal regions were recruited only during the reward outcome, likely representing the value of the reward received. Our findings help to clarify the neural substrates of the different phases of reward and loss processing, and advance neurobiological models of these processes.
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ItemUncertainty and computational complexity(Royal Society, The, 2018-12-31)Modern theories of decision-making typically model uncertainty about decision options using the tools of probability theory. This is exemplified by the Savage framework, the most popular framework in decision-making research. There, decision-makers are assumed to choose from among available decision options as if they maximized subjective expected utility, which is given by the utilities of outcomes in different states weighted with subjective beliefs about the occurrence of those states. Beliefs are captured by probabilities and new information is incorporated using Bayes’ Law. The primary concern of the Savage framework is to ensure that decision-makers’ choices are rational. Here, we use concepts from computational complexity theory to expose two major weaknesses of the framework. Firstly, we argue that in most situations, subjective utility maximization is computationally intractable, which means that the Savage axioms are implausible. We discuss empirical evidence supporting this claim. Secondly, we argue that there exist many decision situations in which the nature of uncertainty is such that (random) sampling in combination with Bayes’ Law is an ineffective strategy to reduce uncertainty. We discuss several implications of these weaknesses from both an empirical and a normative perspective.
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ItemDefining Compulsive Behavior(Springer Verlag, 2019-03-15)Compulsive tendencies are a central feature of problematic human behavior and thereby are of great interest to the scientific and clinical community. However, no consensus exists about the precise meaning of ‘compulsivity,’ creating confusion in the field and hampering comparison across psychiatric disorders. A vague conceptualization makes compulsivity a moving target encompassing a fluctuating variety of behaviors, which is unlikely to improve the new dimension-based psychiatric or psychopathology approach. This article aims to help progress the definition of what constitutes compulsive behavior, cross-diagnostically, by analyzing different definitions in the psychiatric literature. We searched PubMed for articles in human psychiatric research with ‘compulsive behavior’ or ‘compulsivity’ in the title that focused on the broader concept of compulsivity—returning 28 articles with nine original definitions. Within the definitions, we separated three types of descriptive elements: phenomenological, observational and explanatory. The elements most applicable, cross-diagnostically, resulted in this definition: Compulsive behavior consists of repetitive acts that are characterized by the feeling that one ‘has to’ perform them while one is aware that these acts are not in line with one’s overall goal. Having a more unified definition for compulsive behavior will make its meaning precise and explicit, and therefore more transferable and testable across clinical and non-clinical populations.