A neural and behavioral tradeoff underlies exploratory decisions in normative anxiety

Aberg, Kristoffer C.; Toren, Ido; Paz, Rony

doi:10.1101/2020.09.16.300525

Cited by 5 publications

(6 citation statements)

References 104 publications

(225 reference statements)

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“…According to our factor structure, STAI-T primarily reflects the Negative Affect factor, which was associated with an increase in directed exploration in Experiment 1. This finding matches the recent work by Aberg et al (2021). However, this relationship disappeared in Experiment 2 when the reward prediction task was added, implying that the effect of Negative Affect might not be robust to task modification.…”

Section: Tablesupporting

confidence: 91%

“…On one hand, people with anxiety symptoms tend to avoid uncertain options (Charpentier et al, 2017), which reduces exploration. On the other hand, anxiety is associated with the elevated valuation of information (Aberg et al, 2021;Bennett et al, 2021), which encourages exploration behavior to reduce uncertainty. It is also possible that the apparently increased exploration reflects an overall tendency to behave more randomly (Aylward et al, 2019).…”

Section: Underestimation Of Uncertaintymentioning

confidence: 99%

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Trait somatic anxiety is associated with reduced directed exploration and underestimation of uncertainty

2022

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De-identified behavioral and self-report data as well as analysis code have been made publicly available via the Open Science Framework and can be assessed at https://osf.io/y6urc/?view_only=a9cf3daa9c1e4e69bdc79f6d00175fb8. The preregistration form for Experiment1 is available at https://aspredicted.org/BB2_1HT. Early versions of this work were presented at the 2021 Wisconsin Symposium on Emotion, 2021 virtual Society of Neuroeconomics conference, and seminars at Harvard University. We thank Dr. Thomas Rusch for his help with data analysis. We thank members of Phelps Lab and Gershman Lab for insightful discussions.

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Section: Tablesupporting

confidence: 91%

Section: Underestimation Of Uncertaintymentioning

confidence: 99%

Trait somatic anxiety is associated with reduced directed exploration and underestimation of uncertainty

2022

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“…Although we find a negative relationship between symptoms and directed exploration, our findings linking elevated symptoms to greater ambiguity aversion share some similarity to the greater exploration in depression (25) and trait anxiety (24) observed in previous work.…”

Section: Discussionsupporting

confidence: 88%

“…Faster learning rates were also associated with more severe psychotic symptoms. Another recent study in healthy participants showed that normative levels of trait anxiety were positively associated with exploratory behavior and that an inverted-U pattern characterized performance differences; namely, moderate anxiety and associated levels of exploration led to higher levels of performance than those with very high anxiety or very low anxiety (i.e., who explored too much or too little; (24)). This finding was in the context of a volatile environment with changing reward or loss probabilities and appeared to be driven by reduced reward-seeking behavior and an elevated drive to reduce uncertainty.…”

Section: Introductionmentioning

confidence: 99%

Lower levels of directed exploration and reflective thinking are associated with greater anxiety and depression

Smith¹,

Taylor²,

Wilson³

et al. 2021

Preprint

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Anxiety and depression are often associated with strong beliefs that entering specific situations will lead to aversive outcomes – even when these situations are objectively safe and avoiding them reduces well-being. A possible mechanism underlying this maladaptive avoidance behavior is a failure to reflect on: 1) appropriate levels of uncertainty about the situation, and 2) how this uncertainty could be reduced by seeking further information (i.e., exploration). To test this hypothesis, we asked a community sample of 417 individuals to complete measures of reflective cognition, exploration, and symptoms of anxiety and depression. Consistent with our hypotheses, we found significant associations between each of these measures in expected directions (i.e., positive relationships between reflective cognition and strategic information-seeking behavior or “directed exploration”, and negative relationships between these measures and anxiety/depression symptoms). Further analyses suggested that the relationship between directed exploration and depression/anxiety was due to an ambiguity aversion promoting exploration in conditions where information-seeking was not beneficial (as opposed to under-exploration when more information would aid future choices). In contrast, reflectiveness was associated with greater exploration in appropriate settings and separately accounted for differences in reaction times, decision noise, and choice accuracy in expected directions. These results shed light on the mechanisms underlying information-seeking behavior and how they may contribute to symptoms of emotional disorders. They also highlight the possibility that reflectiveness and exploration could represent novel treatment targets for those who show low levels of these tendencies – consistent with the need to develop individualized precision medicine approaches within computational psychiatry.

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“…Empirical studies in AI have only very recently begun to examine differences in preference precision (and hence informationseeking; see (Smith, Schwartenbeck, et al, 2020;Smith, Taylor, Stewart, et al, 2021)). However, work on exploratory drives within expanded RL models has suggested altered patterns of information-seeking in depression, anxiety, and other psychiatric disorders (Aberg et al, 2022;Fan et al, 2021;Smith, Taylor, Wilson, et al, 2021;Waltz et al, 2020). Whether and how information-seeking drives relate to SWB has not been empirically assessed (for some interesting Smith,Varshney,Nagayama,Kazama,Kitagawa,Managi,& Ishikawa www.internationaljournalofwellbeing.org 14 recent theoretical discussion, see (Miller et al, 2022)).…”

Section: Information-seeking and Sensitivity To Uncertaintymentioning

confidence: 99%

A computational neuroscience perspective on subjective wellbeing within the active inference framework

Smith¹,

Varshney²,

Nagayama³

et al. 2022

Preprint

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Understanding and promoting subjective wellbeing (SWB) has been the topic of increasing research, due in part to its potential contributions to health and productivity. To date, the conceptualization of SWB has been grounded within social psychology and largely focused on self-report measures. In this paper, we explore the potentially complementary tools and theoretical perspectives offered by computational neuroscience, with a focus on the active inference (AI) framework. This framework is motivated by the fact that the brain does not have direct access to the world; to select actions, it must instead infer the most likely external causes of the sensory input it receives from both the body and the external world. Because sensory input is always consistent with multiple interpretations, the brain’s internal model must use background knowledge, in the form of prior expectations, to make a “best guess” about the situation it is in and how it will change by taking one action or another. This best guess arises by minimizing an error signal representing the deviation between predicted and observed sensations given a chosen action – quantified mathematically by a variable called free energy (FE). Crucially, recent proposals have illustrated how emotional experience may emerge within AI as a natural consequence of the brain keeping track of the success of its model in selecting actions to minimize FE. In this paper, we draw on the concepts and mathematics in AI to highlight how different computational strategies can be used to minimize FE – some more successfully than others. This affords a characterization of how diverse individuals may adopt unique strategies for achieving high SWB. It also highlights novel ways in which SWB could be effectively improved. These considerations lead us to propose a novel computational framework for understanding SWB. We highlight several parameters in these models that could explain individual and cultural differences in SWB, and how they might inspire novel interventions. We conclude by proposing a line of future empirical research based on computational modelling that could complement current approaches to the study of wellbeing and its improvement.

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A neural and behavioral tradeoff underlies exploratory decisions in normative anxiety

Cited by 5 publications

References 104 publications

Trait somatic anxiety is associated with reduced directed exploration and underestimation of uncertainty

Trait somatic anxiety is associated with reduced directed exploration and underestimation of uncertainty

Lower levels of directed exploration and reflective thinking are associated with greater anxiety and depression

A computational neuroscience perspective on subjective wellbeing within the active inference framework

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