scholarly journals The continuous and changing impact of affect on risky decision-making

Author(s):  
Erkin Asutay ◽  
Daniel Västfjäll

Abstract Affective experience has an important role in decision-making with recent theories suggesting a modulatory role of affect in ongoing subjective value computations. However, it is unclear how varying expectations and uncertainty dynamically influence affective experience and how dynamic representation of affect modulates risky choices. Using hierarchical Bayesian modeling on data from a risky choice task (N = 101), we find that the temporal integration of recently encountered choice parameters (expected value, uncertainty, and prediction errors) shapes affective experience and impacts subsequent choice behavior. Specifically, experienced arousal prior to choice was associated with increased loss aversion, risk aversion, and choice consistency. Taken together, these findings provide clear behavioral evidence for continuous affective modulation of subjective value computations during risky decision-making.

2020 ◽  
Author(s):  
Dannia Islas-Preciado ◽  
Steven R. Wainwright ◽  
Julia Sniegocki ◽  
Stephane E. Lieblich ◽  
Shunya Yagi ◽  
...  

AbstractDecision-making is a complex process essential to daily adaptation in many species. Risk is an inherent aspect of decision-making and it is influenced by gonadal hormones. Testosterone and 17β-estradiol may modulate decision making and impact the mesocorticolimbic dopamine pathway. Here, we explored sex differences, the effect of gonadal hormones and the dopamine agonist amphetamine on risk-based decision making. Intact or gonadectomised (GDX) male and female rats underwent to a probabilistic discounting task. High and low doses of testosterone propionate (1.0 or 0.2 mg) and 17β-estradiol benzoate (0.3 μg) were administered to assess acute effects on risk-based decision making. After 3-days of washout period, intact and GDX rats received high or low (0.5 or 0.125 mg/kg) doses of amphetamine and re-tested in the probabilistic discounting task. Under baseline conditions, males made more risky choices during probability discounting compared to female rats, particularly in the lower probability blocks, but GDX did not influence risky choice. The high, but not the low dose, of testosterone modestly reduced risky decision making in GDX male rats. Conversely, 17β-estradiol had no significant effect on risky choice regardless of GDX status in either sex. Lastly, a higher dose of amphetamine increased risky decision making in both intact males and females, but had no effect in GDX rats. These findings demonstrated sex differences in risk-based decision making, with males showing a stronger bias towards larger, uncertain rewards. GDX status influenced the effects of amphetamine, suggesting different dopaminergic regulation in risk-based choices among males and females.


2021 ◽  
Author(s):  
Lydia Hickman ◽  
Connor Keating ◽  
Jennifer Cook ◽  
Elliot Andrew Ludvig

Everyday risky decisions are susceptible to influence from a variety of sources, including the social context in which decisions take place. In the general population, people update their risk preferences based on knowledge of choices made by previous participants. In this study, we examined the influence of social information on the risky decision-making of autistic adults, a group in which differences in social processing have been observed. Autistic and non-autistic adults completed a risky decision-making task in the presence of both social and non-social information, either choosing for themselves or someone else on each trial. Notably, the social information comprised tokens that represented preferences of previous participants and was thus devoid of overt social cues such as faces or gestures. The non-social condition comprised a previously validated method where tokens represented “preferences” generated by weighted roulette wheels. Participants significantly shifted their choices when the influence (social or non-social) suggested a less risky choice. There were no group differences in risky decision-making when deciding for oneself compared to others. Interestingly, no differences in the effects of social and non-social influence were found between autistic and non-autistic adults. Considering previous evidence of social influence differences when using overtly social cues, we suggest that the removal of social cues in our paradigm led to comparable performance between the autistic and non-autistic groups. The current study paves the way for future studies investigating a confounding effect of social cues, which will lead to important insight for theories of social influence in autism.


2021 ◽  
Author(s):  
Lisheng He ◽  
Pantelis P. Analytis ◽  
Sudeep Bhatia

A wide body of empirical research has revealed the descriptive shortcomings of expected value and expected utility models of risky decision making. In response, numerous models have been advanced to predict and explain people’s choices between gambles. Although some of these models have had a great impact in the behavioral, social and management sciences, there is little consensus about which model offers the best account of choice behavior. In this paper, we conduct a large-scale comparison of 58 prominent models of risky choice, using 19 existing behavioral datasets involving more than 800 participants. This allows us to comprehensively evaluate models in terms of individual-level predictive performance across a range of different choice settings. We also identify the psychological mechanisms that lead to superior predictive performance and the properties of choice stimuli that favor certain types of models over others. Second, drawing on research on the wisdom of crowds, we argue that each of the existing models can be seen as an expert that provides unique forecasts in choice predictions. Consistent with this claim, we find that crowds of risky choice models perform better than individual models and thus provide a performance bound for assessing the historical accumulation of knowledge in our field. Our results suggest that each model captures unique aspects of the decision process, and that existing risky choice models offer complementary rather than competing accounts of behavior. We discuss the implications of our results on theories of risky decision making and the quantitative modeling of choice behavior.


2021 ◽  
Author(s):  
Lisheng He ◽  
Pantelis P. Analytis ◽  
Sudeep Bhatia

A wide body of empirical research has revealed the descriptive shortcomings of expected value and expected utility models of risky decision making. In response, numerous models have been advanced to predict and explain people’s choices between gambles. Although some of these models have had a great impact in the behavioral, social, and management sciences, there is little consensus about which model offers the best account of choice behavior. In this paper, we conduct a large-scale comparison of 58 prominent models of risky choice, using 19 existing behavioral data sets involving more than 800 participants. This allows us to comprehensively evaluate models in terms of individual-level predictive performance across a range of different choice settings. We also identify the psychological mechanisms that lead to superior predictive performance and the properties of choice stimuli that favor certain types of models over others. Moreover, drawing on research on the wisdom of crowds, we argue that each of the existing models can be seen as an expert that provides unique forecasts in choice predictions. Consistent with this claim, we find that crowds of risky choice models perform better than individual models and thus provide a performance bound for assessing the historical accumulation of knowledge in our field. Our results suggest that each model captures unique aspects of the decision process and that existing risky choice models offer complementary rather than competing accounts of behavior. We discuss the implications of our results on theories of risky decision making and the quantitative modeling of choice behavior. This paper was accepted by Yuval Rottenstreich, behavioral economics and decision analysis.


2019 ◽  
Vol 116 (37) ◽  
pp. 18732-18737 ◽  
Author(s):  
Benjamin Chew ◽  
Tobias U. Hauser ◽  
Marina Papoutsi ◽  
Joerg Magerkurth ◽  
Raymond J. Dolan ◽  
...  

Human behavior is surprisingly variable, even when facing the same problem under identical circumstances. A prominent example is risky decision making. Economic theories struggle to explain why humans are so inconsistent. Resting-state studies suggest that ongoing endogenous fluctuations in brain activity can influence low-level perceptual and motor processes, but it remains unknown whether endogenous fluctuations also influence high-level cognitive processes including decision making. Here, using real-time functional magnetic resonance imaging, we tested whether risky decision making is influenced by endogenous fluctuations in blood oxygenation level-dependent (BOLD) activity in the dopaminergic midbrain, encompassing ventral tegmental area and substantia nigra. We show that low prestimulus brain activity leads to increased risky choice in humans. Using computational modeling, we show that increased risk taking is explained by enhanced phasic responses to offers in a decision network. Our findings demonstrate that endogenous brain activity provides a physiological basis for variability in complex human behavior.


2019 ◽  
Vol 8 (1) ◽  
pp. 198-207
Author(s):  
Kaileigh Byrne ◽  
Hunter Willis ◽  
Caitlin Peters ◽  
Deborah Kunkel ◽  
Thomas Tibbett

Previous research suggests that depressive symptoms are associated with altered sensitivity to reward and punishment in various decision-making contexts. Building on this work, this study investigated whether depressed-affect symptoms influenced risky decision making under time pressure. The effect of depressed affect on risky choice was assessed in a reward (Experiments 1A and 1B) and loss (Experiment 2) context under low- and high-pressure conditions. Decisions involved learning to choose between a “sure” option and a “risky” option with identical expected values. In Experiment 1A, depressed affect predicted increased risky decision making under time pressure but did not affect decision making under low pressure. Experiment 1B replicated this effect. In contrast, in Experiment 2, depressed affect led to reduced risk taking in low-pressure condition but did not affect decision making under high pressure. These results suggest that the pattern of risky decision making among those experiencing symptoms of depressed affect depends on performance pressure demands.


2020 ◽  
Author(s):  
Kaileigh A. Byrne ◽  
Stephanie Gabrielle Six ◽  
Reza Ghaiumy Anaraky ◽  
Maggie W. Harris ◽  
Emma L. Winterlind

To reduce the spread of COVID-19 transmission, government agencies in the United States (US) have recommended COVID prevention guidelines, including wearing masks and social distancing. However, compliance with these guidelines have been inconsistent. This study examined whether individual differences in decision-making and motivational propensities predicted compliance with COVID-19 preventative behaviors in a representative sample of US adults (N=225). Participants completed an online study in September 2020 that included a risky choice decision-making task, temporal discounting task, and measures of appropriate mask wearing, social distancing, and perceived risk of engaging in public activities. Linear regression results indicated that greater risky decision-making behavior and temporal discounting were associated with less appropriate mask-wearing behavior and social distancing. Additionally, demographic factors, including political affiliation and income level, were also associated with differences in COVID-19 preventative behaviors. Path analysis results showed that risky decision-making behavior, temporal discounting, and risk perception collectively predicted 61% of the variance in appropriate mask-wearing behavior. Individual differences in general decision-making patterns are therefore highly predictive of who complies with COVID-19 prevention guidelines.


PLoS ONE ◽  
2021 ◽  
Vol 16 (5) ◽  
pp. e0251073
Author(s):  
Kaileigh A. Byrne ◽  
Stephanie G. Six ◽  
Reza Ghaiumy Anaraky ◽  
Maggie W. Harris ◽  
Emma L. Winterlind

To reduce the spread of COVID-19 transmission, government agencies in the United States (US) recommended precautionary guidelines, including wearing masks and social distancing to encourage the prevention of the disease. However, compliance with these guidelines has been inconsistent. This correlational study examined whether individual differences in risky decision-making and motivational propensities predicted compliance with COVID-19 preventative behaviors in a sample of US adults (N = 404). Participants completed an online study from September through December 2020 that included a risky choice decision-making task, temporal discounting task, and measures of appropriate mask-wearing, social distancing, and perceived risk of engaging in public activities. Linear regression results indicated that greater temporal discounting and risky decision-making were associated with less appropriate mask-wearing behavior and social distancing. Additionally, demographic factors, including personal experience with COVID-19 and financial difficulties due to COVID-19, were also associated with differences in COVID-19 preventative behaviors. Path analysis results showed that risky decision-making behavior, temporal discounting, and risk perception collectively predicted 55% of the variance in appropriate mask-wearing behavior. Individual differences in general decision-making patterns are therefore highly predictive of who complies with COVID-19 prevention guidelines.


2016 ◽  
Author(s):  
Dongil Chung ◽  
Kelly Kadlec ◽  
Jason A. Aimone ◽  
Katherine McCurry ◽  
Brooks King-Casas ◽  
...  

AbstractThe clinical diagnosis and symptoms of major depressive disorder (MDD) have been closely associated with impairments in reward processing. In particular, various studies have shown blunted neural and behavioral responses to the experience of reward in depression. However, little is known about whether depression affects individuals’ valuation of potential rewards during decision-making, independent from reward experience. To address this question, we used a gambling task and a model-based analytic approach to measure two types of individual sensitivity to reward values in participants with MDD: ‘risk preference,’ indicating how objective values are subjectively perceived and ‘inverse temperature,’ determining the degree to which subjective value differences between options influences participants’ choices. On both of these measures of value sensitivity, participants with MDD were comparable to non-psychiatric controls. Both risk preference and inverse temperature were also stable over four laboratory visits and comparable between the groups at each visit. Moreover, neither value sensitivity measure varied with severity of clinical symptoms in MDD. These data suggest intact and stable value processing in MDD during risky decision-making.


2017 ◽  
Author(s):  
Caitlin A. Orsini ◽  
Caesar M. Hernandez ◽  
Sarthak Singhal ◽  
Kyle B. Kelly ◽  
Charles J. Frazier ◽  
...  

AbstractDecision making is a multifaceted process, consisting of several distinct phases that likely require different cognitive operations. Previous work showed that the basolateral amygdala (BLA) is a critical substrate for decision making involving risk of punishment; however, it is unclear how the BLA is recruited at different stages of the decision process. To this end, the current study used optogenetics to inhibit the BLA during specific task phases in a model of risky decision making (Risky Decision-making Task; RDT) in which rats choose between a small, “safe” reward and a large reward accompanied by varying probabilities of footshock punishment. Rats received intra-BLA microinjections of viral vectors carrying either halorhodopsin (eNpHR3.0-mCherry) or mCherry alone (control) followed by optic fiber implants and were trained in the RDT. Laser stimulation during the task occurred during either intertrial interval, deliberation, or reward outcome phases, the latter of which was further divided into the three possible outcomes (small, safe; large, unpunished; large, punished). Inhibition of the BLA selectively during the deliberation phase decreased choice of the large, risky outcome (decreased risky choice). In contrast, BLA inhibition selectively during delivery of the large, punished outcome increased risky choice. Inhibition had no effect during the other phases, nor did it affect performance in control rats. Collectively, these data indicate that the BLA can either inhibit or promote choice of risky options, depending on the phase of the decision process in which it is active.Significance StatementTo date, most behavioral neuroscience research on neural mechanisms of decision making has employed techniques that preclude assessment of distinct phases of the decision process. Here we show that optogenetic inhibition of the basolateral amygdala (BLA) has opposite effects on choice behavior in a rat model of risky decision making depending on the phase in which inhibition occurs. BLA inhibition during a period of deliberation between small, safe and large, risky outcomes decreased risky choice. In contrast, BLA inhibition during receipt of the large, punished outcome increased risky choice. These findings highlight the importance of temporally targeted approaches to understand neural substrates underlying complex cognitive processes. More importantly, they reveal novel information about dynamic BLA modulation of risky choice.


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