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Subjective probability. When probability information is explicitly conveyed, low probabilities are typically overestimated, whereas high probabilities are underestimated.
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Individuals vary substantially in their tendency to take risks. In the past two decades, a large number of neuroimaging studies in humans have explored the neural mechanisms of several cognitive processes that contribute to risk taking. In this article, I focus on functional and structural MRI studies that investigated uncertainty processing, one o...
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... in a nonlinear manner. As Kahneman and Tversky described in their Prospect Theory (Kahneman and Tversky 1979;Tversky and Kahneman 1992), when participants are presented with explicit probabilities (e.g., "50% chance") they tend to overweigh low probabilities and underweigh high probabilities, in the form of an inverted S-shaped func- tion (Fig. 5). When probabilities are learned by experi- ence, from repeated sampling, an opposite effect is observed, where small probabilities are underestimated and large probabilities overestimated, in the form of an S-shaped function ( Hertwig and others 2004). fMRI data suggest that the inverted S-shaped nonlinear weighting of explicit ...
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... Since the neural basis of WRT has not been established, we draw on the findings of current neuroimaging work on individuals' risk-taking. As aforementioned, almost all prior neuroscience studies on the topic of risk-taking employed task-based fMRI with individual risk-taking tasks focusing on the financial domain (e.g., Hsu et al., 2005;Huettel et al., 2006;Kolling et al., 2014;Kuhnen & Knutson, 2005;Levy, 2017;Li et al., 2020;McCoy & Platt, 2005;Mohr et al., 2010;Paulus et al., 2002;Preuschoff et al., 2008;Ridderinkhof et al., 2004;Weller et al., 2007). These studies have observed that individual financial risk-taking is primarily associated with activation in brain regions including the amygdala, ventral striatum (VS), insula, orbitofrontal cortex (OFC), ventromedial prefrontal cortex (vmPFC), anterior cingulate cortex (ACC), medial frontal gyrus (MFG), and posterior parietal cotex (PPC). ...
Risk-taking in the ‘work’ domain constitutes a fundamental building block for a wide range of important decisions (e.g., investment) and behaviors (e.g., creativity) of individuals, groups, and organizations. Yet, what remains unknown is the neurofunctional basis of work-domain risk-taking (WRT) and how these brain substrates act as mediators in relating individual personality traits such as regulatory focus and the Big Five to WRT. This study, with a sample of 201 healthy full-time employees, investigated the above questions using resting-state fMRI. The results indicated that individuals who engage more in WRT showed increased brain activity (indicated by fALFF) in the right medial frontal gyrus (MFG) and right insula brain areas involved in goal-directed and self-regulated functions, therefore providing unique neuroimaging evidence for the notion that risk-taking is highly domain specific. More importantly, we found that fALFF in the right MFG and right insula areas has a significant mediating role in relating promotion focus and neuroticism to WRT, respectively, suggesting that these traits might have more important roles in associating with WRT, and the brain activity of the two regions (i.e., right MFG and right insula) may act as the underlying mediating mechanisms. Managerial implications are discussed.
... However, an association between the magnitude of a number and the spatial location of a response generalized to close versus far (small numbers were associated with close and large numbers were assocated with far, rather than with left to right) 85 . Thus, a general number-spatial location association seems to be represented in the brain, in part, in the posterior parietal cortex 86,87 , which is also associated with processing fundamental numerical concepts such as risk and probability 88,89 . Such results (and others) speak to whether brain activation during symbolic number, arithmetic and spatial processing (mental rotation) tasks are consistent with shared processing accounts (in other words, number processing and spatial processing overlap) 90 . ...
The onus on the average person is greater than ever before to make sense of large amounts of readily accessible quantitative information, but the ability and confidence to do so are frequently lacking. Many people lack practical mathematical skills that are essential for evaluating risks, probabilities and numerical outcomes such as survival rates for medical treatments, income from retirement savings plans or monetary damages in civil trials. In this Review, we integrate research on objective and subjective numeracy, focusing on cognitive and metacognitive factors that distort human perceptions and foment systematic biases in judgement and decision making. Paradoxically, an important implication of this research is that a literal focus on objective numbers and mechanical number crunching is misguided. Numbers can be a matter of life and death but a person who uses rote strategies (verbatim representations) cannot take advantage of the information contained in the numbers because 'rote' strategies are, by definition, processing without meaning. Verbatim representations (verbatim is only surface form, not meaning) treat numbers as data as opposed to information. We highlight a contrasting approach of gist extraction: organizing numbers meaningfully, interpreting them qualitatively and making meaningful inferences about them. Efforts to improve numerical cognition and its practical applications can benefit from emphasizing the qualitative meaning of numbers in context - the gist - building on the strengths of humans as intuitive mathematicians. Thus, we conclude by reviewing evidence that gist training facilitates transfer to new contexts and, because it is more durable, longer-lasting improvements in decision making.
... In light of the prior study [20], the present results, although still speculation-based, indicate increased ACC activation in female participants compared to their male counterparts when exposed to neutral pictures while accompanied by a significant other person (social presence condition). It is suggested that the increased neural activity associated with neutral pictures relates to the ACC's role in processing several components of uncertainty and ambiguity [65,66]. This heightened ACC activation may reflect an individuals' personal ambiguity attitudes in the choice between alternative strategies with the intention of choosing the best value option [26,65]. ...
... It is suggested that the increased neural activity associated with neutral pictures relates to the ACC's role in processing several components of uncertainty and ambiguity [65,66]. This heightened ACC activation may reflect an individuals' personal ambiguity attitudes in the choice between alternative strategies with the intention of choosing the best value option [26,65]. The potential of social presence to alter ACC activation is linked to the fact that mistakes made in the presence of others are more costly than made when alone. ...
This study represents a follow-up event-related potential (ERP) analysis of a prior investigation. The previous results showed that participants had most negative-tending ERPs in the mid-frontal brain region during exposure to neutral emotion pictures (compared to negative and positive pictures) while being accompanied by a significant other person (social presence condition). The present analysis aimed at investigating potential sex differences related to this phenomenon. Female and male participants’ brain activity data from the previous study were analyzed separately for one representative mid-frontal electrode location selected on the basis of having the highest significance level. As a result, only female participants showed significantly more negative-tending potentials in response to neutral pictures, compared to both other emotion categories (positive and negative) in the social presence condition. This was not found in male participants. The respective ERP effect was most dominant at 838 ms post stimulus onset, which is slightly later than the effect found in the prior study. However, this result is interpreted as evidence that the general effect from the prior study can be understood as a largely female phenomenon. In line with the prior study, the present results are interpreted as a predominantly female activation in the mid-frontal brain region in response to neutral picture stimuli while being accompanied by a significant other person (social presence condition). Although only speculative, this would align with previous studies demonstrating sex-related hormonal and structural differences in the anterior cingulate cortex (ACC). In general, ACC activation has been associated with an integrative weighting function in ambiguous social settings, which makes sense given the ambiguous nature of neutral pictures in combination with a social presence condition.
... Single-cell recordings revealed that expected values and variances are encoded by separate populations of neurons in the fronto-parietal network, and that increased uncertainty enhances fronto-parietal bottom-up functional connectivity thereby increasing the amount of sensory input that would reduce the uncertainty (Taghizadeh et al., 2020). The results of the neuroanatomical studies suggest that a greater volume of gray matter in the PPC is correlated with higher tolerance to risk (Levy, 2017). These studies indicate that this brain area might play a role in stable personality-related components of risk preferences. ...
This study provides evidence that the posterior parietal cortex (PPC) is causally involved in risky decision making via the processing of reward values but not reward probabilities. In the within-group experimental design, participants performed a binary lottery choice task following transcranial magnetic stimulation of the right PPC, left PPC and a right PPC sham (placebo) stimulation. Both, mean-variance and the prospect theory approach to risky choice showed that the PPC stimulation changed participants' preferences towards greater risk aversion compared to sham. On the behavioral level, after the PPC stimulation the likelihood of choosing a safer option became more sensitive to the difference in standard deviations between lotteries, compared to sham, indicating greater risk avoidance within the mean-variance framework. We also estimated the shift in prospect theory parameters of risk preferences after PPC stimulation. The hierarchical Bayesian approach showed moderate evidence (BF = 7.44 and 5.41 for right and left PPC respectively) for a credible change in risk aversion parameter towards lower marginal reward value (and, hence, lower risk tolerance), while no credible change in probability weighting was observed. Additionally, we observed anecdotal evidence (BF = 2.9) for a credible increase in the consistency of responses after the left PPC stimulation compared to sham.
... Functional magnetic resonance imaging (fMRI) studies have shown that decisions under ambiguity recruit neural networks linked with processing affective and motivational information (FeldmanHall et al., 2019), including the orbitofrontal cortex, medial prefrontal cortex, amygdala, and insula (Blankenstein et al., 2018;Hsu et al., 2005;Pushkarskaya, Smithson, et al., 2015;Wu et al., 2021). In contrast, decisions under risk recruit brain areas supporting computational demands and cognitive control to a larger extent, such as the dorsolateral prefrontal cortex, dorsal anterior cingulate cortex, and posterior parietal cortex (Grubb et al., 2016;Huettel et al., 2006;Levy, 2017;Mohr et al., 2010;Platt & Huettel, 2008). Because of its poor temporal resolution, however, previous fMRI studies may conflate neural activities associated with cognitive processes that occur close in time but are psychologically distinguishable. ...
... According to recent models, decisions under ambiguity involve affective/motional salience to a larger extent (FeldmanHall et al., 2016(FeldmanHall et al., , 2019Herman et al., 2021), whereas decisions under risk depend more on cognitive control (Brand et al., 2006;Brand, Recknor, et al., 2007). This neural dissociation is supported by evidence from fMRI studies (Krain et al., 2006;Levy, 2017;Schultz et al., 2008;Wu et al., 2021). However, value-based decision making is heterogenous and includes several distinct cognitive processes (Berridge & Robinson, 2003;Fellows, 2004;Platt, 2002;Platt & Plassmann, 2014;Rangel et al., 2008), which could be not easily captured by previous fMRI studies because of its sluggish temporal resolution. ...
Uncertainty can be fractioned into risk and ambiguity psychologically and neurobiologically. However, whether and how risk and ambiguity are dissociated in terms of neural dynamics during value‐based decision making remain elusive. The present event‐related potential (ERP) study addressed these issues by asking participants to perform a wheel‐of‐fortune task either during a risky context (Experiment 1; N = 30) where outcome probability was known or during an ambiguous context (Experiment 2; N = 30) where outcome probability was unknown. Results revealed that the cue‐P3 was more enhanced for risk versus ambiguity during the anticipatory phase, whereas the RewP was more increased for ambiguity than risk during the consummatory phase. Moreover, the SPN and the fb‐P3 components were further modulated by the levels of risk and ambiguity, respectively. These findings demonstrate a neural dissociation between risk and ambiguity, which unfolds from the anticipatory phase to the consummatory phase. Our findings add a new perspective on neural dissociation between risk and ambiguity during value‐based decision making. We provide evidence that risk processing is associated uniquely with anticipatory ERPs, whereas ambiguity processing is more associated with consummatory ERPs. Our results highlight the multi‐phase nature of neural dissociation between risk and ambiguity.
... Functional neuroimaging studies have implicated the anterior insula, ventral striatum, anterior cingulate cortex, parietal cortex and prefrontal cortex in decisions under risk and uncertainty 8,9 . The DLPFC has been shown to be involved in decision making, particularly in making choices under risk 9 . ...
... uk/ spm/ softw are/ spm8/). The MNI coordinates were selected based on the previous fMRI study, which revealed the peak activity of the DLPFC (right DLPFC (8,18,44); left DLPFC (− 42, 16, 42)) correlated with subjective value of a lottery 17 . In the same study, activity in a similar region of the DLPFC correlated with expected return and subjective expected return of the lottery. ...
In this study, we provide causal evidence that the dorsolateral prefrontal cortex (DLPFC) supports the computation of subjective value in choices under risk via its involvement in probability weighting. Following offline continuous theta-burst transcranial magnetic stimulation (cTBS) of the DLPFC subjects (N = 30, mean age 23.6, 56% females) completed a computerized task consisting of 96 binary lottery choice questions presented in random order. Using the hierarchical Bayesian modeling approach, we then estimated the structural parameters of risk preferences (the degree of risk aversion and the curvature of the probability weighting function) and analyzed the obtained posterior distributions to determine the effect of stimulation on model parameters. On a behavioral level, temporary downregulation of the left DLPFC excitability through cTBS decreased the likelihood of choosing an option with higher expected reward while the probability of choosing a riskier lottery did not significantly change. Modeling the stimulation effects on risk preference parameters showed anecdotal evidence as assessed by Bayes factors that probability weighting parameter increased after the left DLPFC TMS compared to sham.
... Bilateral VS, an area sensitive to rewards, is characterized by risk processing related to impulsive behaviour (Beck et al., 2009;Hampton et al., 2017). The activity of the VS has also been shown to promote risk-seeking (Levy, 2017), which is positively correlated with sensory seeking scores (Bjork et al., 2008). The insula inputs the body's internal state into the medial prefrontal lobe and the VS through functionally connecting with those regions (Droutman et al., 2015;Sellitto et al., 2016). ...
The relationship between intertemporal and risky decision-making has received considerable attention in decision research. Single-process theories suggest that choices involving delay and risk are simply two manifestations of the same psychological mechanism, which implies similar patterns of neural activation. Conversely, the dual-system theory suggests that delayed and risky choices are two contrasting types of processes, which implies distinct brain networks. How these two types of choices relate to each other remains unclear. The current study addressed this issue by performing a meta-analysis of 28 intertemporal decision-making studies (862 subjects) and 51 risky decision-making studies (1539 subjects). We found no common area activated in the conjunction analysis of the delayed and risky rewards. Based on the contrast analysis, delayed rewards were associated with stronger activation in the left dorsal insula, while risky rewards were associated with activation in the bilateral ventral striatum and the right anterior insula. The results align with the dual-system theory with separate neural networks for delayed and risky rewards.
... Although RT can explain the observed human risk-attitudes qualitatively [23], it overlooks subjective riskperception, another necessary component of risk-awareness [46,48], which is included in PT as probability weighting. The neural substrate of probability weighting was later found [20]. When trying to build a human-like computational decision-making model in our previous work [12], we found RT alone could not explain the measured data, and we therefore added probability weighting into RT to obtain an extended version called RTx. ...
The expected value (EV) based optimization principle often used in engineering ignores risk-related human characteristics which are however important to human-robot interaction (HRI). The characteristics include risk-perception and risk-attitudes which can be called risk-awareness collectively. In this work, we study the effects of risk-awareness in a human-multi-robot collaborative search task. In such a task, the correctness of robotic visual detection is uncertain, but the robots can request human assistance. Assume there is only one human in the team, the requesting robots must be ordered into a sequence. To optimize the ordering, we propose to construct a risk-aware cost function with an extended version of regret theory (RTx). RTx is a decision theory modeling risk-awareness and is backed by neuroscientific and psychological evidences. We cast the optimal ordering into multi-option choice problems and use RTx to make human-like risk-aware decisions. This optimal ordering is combinatorial optimization with a nonlinear cost function which is generally difficult to solve. However, we prove the properties of RTx enable simplification of the optimal ordering to a sorting problem which has fast off-the-shelf solvers. The simplification has two parts. One part concerns with ordering a fixed number of robots optimally. The other concerns with selecting a not-yet-ordered sequence of robots with the optimal length. We examine the RTx-based ordering in simulation and show risk-aware decision-making is more advantageous than EV-based decision-making. The results indicate that risk-awareness renders improved performance of robotic decision-making for HRI and RTx is a tractable embodiment of risk-awareness.
... The brain networks supporting the processing of the subjective value of rewards and punishments and those involved in conflict monitoring in decision-making have been linked to a risky behavior. These networks are located in brain regions such as the striatum, the orbitofrontal cortex (OFC), superior and posterior parietal cortex, the lateral prefrontal cortex (LPFC), the medial temporal lobe, the insula, or the anterior cingulate cortex (ACC) [8][9][10][11][12][13][14]. Only a few recent studies have investigated the relationship between risky driving behavior and the volume of brain gray matter of these structures. ...
... Some of these regions, such as the OFC, the parahippocampus, the caudate, or the putamen, are part of the brain's socioemotional or reward system [50,[80][81][82][83][84][85][86][87]. This system is involved in the sensitivity, detection, and processing of incentive signals; the prospection and representation of reward expectations based on previous experience; and in the search, evaluation, and approach to reinforcers [11,[82][83][84][87][88][89]. Thus, our results suggest an alteration in the detection, processing, and valuation of rewards in the riskiest drivers, which may involve maladaptive decision-making in traffic situations. ...
Personality traits such as impulsivity or sensitivity to rewards and punishments have been associated with risky driving behavior, but it is still unclear how brain anatomy is related to these traits as a function of risky driving. In the present study, we explore the neuroanatomical basis of risky driving behavior and how the level of risk-taking influences the relationship between the traits of impulsivity and sensitivity to rewards and punishments and brain gray matter volume. One hundred forty-four participants with different risk-taking tendencies assessed by real-life driving situations underwent MRI. Personality traits were assessed with self-report measures. We observed that the total gray matter volume varied as a function of risky driving tendencies, with higher risk individuals showing lower gray matter volumes. Similar results were found for volumes of brain areas involved in the reward and cognitive control networks, such as the frontotemporal, parietal, limbic, and cerebellar cortices. We have also shown that sensitivity to reward and punishment and impulsivity are differentially related to gray matter volumes as a function of risky driving tendencies. Highly risky individuals show lower absolute correlations with gray matter volumes than less risk-prone individuals. Taken together, our results show that risky drivers differ in the brain structure of the areas involved in reward processing, cognitive control, and behavioral modulation, which may lead to dysfunctional decision-making and riskier driving behavior.
... The first model, prospect theory, describes risk aversion using diminishing returns for subjective value, accounts for preference reversals in losses (loss aversion), and weights subjective probabilities to explain how people behave in the face of uncertain outcomes (Barberis, 2013). Applying this theory allows researchers to estimate subjective value at an individual level with results indicating that the vmPFC, lateral PFC (Holper, Wolf, & Tobler, 2014;Schultz, 2010), and VS track the subjective value of risky prospects (Blankenstein et al., 2017;Levy, 2017;Levy et al., 2010). These processes are likely supported by dopamine action in those regions (Castrellon et al., 2019;Morgado et al., 2015;Soutschek et al., 2020). ...
In the past decade, decision neuroscience and neuroeconomics have developed many new insights in the study of decision making. This review provides an overarching update on how the field has advanced in this time period. Although our initial review a decade ago outlined several theoretical, conceptual, methodological, empirical, and practical challenges, there has only been limited progress in resolving these challenges. We summarize significant trends in decision neuroscience through the lens of the challenges outlined for the field and review examples where the field has had significant, direct, and applicable impacts across economics and psychology. First, we review progress on topics including reward learning, explore–exploit decisions, risk and ambiguity, intertemporal choice, and valuation. Next, we assess the impacts of emotion, social rewards, and social context on decision making. Then, we follow up with how individual differences impact choices and new exciting developments in the prediction and neuroforecasting of future decisions. Finally, we consider how trends in decision‐neuroscience research reflect progress toward resolving past challenges, discuss new and exciting applications of recent research, and identify new challenges for the field.
This article is categorized under: Psychology > Reasoning and Decision Making
Psychology > Emotion and Motivation
