Computational modeling of behavior under uncertainty: Commonalities and differences between anxiety and depression

Individuals who are prone to experiencing high levels of anxiety and depression often exhibit dysfunctional behavior. For example, anxious individuals often avoid situations that have even the slightest chance of a highly negative outcome (e.g. a plane crash), and depressed individuals often show a reduced pursuit of activities that most people find enjoyable. Progress can be made in understanding dysfunctional behavior by using formal, mathematical frameworks of decision making, which break down behavior into its computational components, and in which we can start to pinpoint the specific abnormalities associated with anxiety and depression. Chapter 1.2 and 1.3 review prior literature, highlighting some of the computations that seem to be altered, such as the overestimation for the probability that rare, extremely negative events will occur. Chapter 2 and Chapter 3 empirically examine behavior in situations that require individuals to accurately estimate the probability that an outcome will (or will not) occur as a result of their actions. In a task where individuals have to estimate action-outcome probabilities by trial-and-error (Chapter 2), individuals with high overall levels of anxiety and depression show a reduced ability to align the rate at which they learn to the rate of change in the environment (i.e. the level of volatility). In a task where individuals have to choose between options that have known (risky) versus unknown (ambiguous) probabilities (Chapter 3), individuals who have high levels of physiological anxiety tend to avoid the ambiguous options more than other individuals, as information is removed about those probabilities. On the other hand, individuals who are prone to experiencing mania are more likely to make the opposite choice, seeking ambiguity, when the outcomes are rewarding. Chapter 4 examines possible sources for dysfunctional beliefs, as opposed to behaviors. In a hypothetical vocational setting where individuals estimate their rank relative to others, individuals with high levels of anhedonia-related symptoms show initial beliefs that are more negative relative to the beliefs of others. Individuals with high levels of anxiety, on the other hand, show negatively biased updating of those beliefs in response to unbiased information. Chapter 5 summarizes the empirical findings and discusses more broadly how anxiety and depression seem to impact behavior (and its underlying computations) in uncertain situations

Computational perspectives on human fear and anxiety

Fear and anxiety are adaptive emotions that serve important defensive functions, yet in excess, they can be debilitating and lead to poor mental health. Computational modelling of behaviour provides a mechanistic framework for understanding the cognitive and neurobiological bases of fear and anxiety, and has seen increasing interest in the field. In this brief review, we discuss recent developments in the computational modelling of human fear and anxiety. Firstly, we describe various reinforcement learning strategies that humans employ when learning to predict or avoid threat, and how these relate to symptoms of fear and anxiety. Secondly, we discuss initial efforts to explore, through a computational lens, approach-avoidance conflict paradigms that are popular in animal research to measure fear- and anxiety-relevant behaviours. Finally, we discuss negative biases in decision-making in the face of uncertainty in anxiety

The emotional gatekeeper: a computational model of attentional selection and suppression through the pathway from the amygdala to the inhibitory thalamic reticular nucleus

In a complex environment that contains both opportunities and threats, it is important for an organism to flexibly direct attention based on current events and prior plans. The amygdala, the hub of the brain's emotional system, is involved in forming and signaling affective associations between stimuli and their consequences. The inhibitory thalamic reticular nucleus (TRN) is a hub of the attentional system that gates thalamo-cortical signaling. In the primate brain, a recently discovered pathway from the amygdala sends robust projections to TRN. Here we used computational modeling to demonstrate how the amygdala-TRN pathway, embedded in a wider neural circuit, can mediate selective attention guided by emotions. Our Emotional Gatekeeper model demonstrates how this circuit enables focused top-down, and flexible bottom-up, allocation of attention. The model suggests that the amygdala-TRN projection can serve as a unique mechanism for emotion-guided selection of signals sent to cortex for further processing. This inhibitory selection mechanism can mediate a powerful affective 'framing' effect that may lead to biased decision-making in highly charged emotional situations. The model also supports the idea that the amygdala can serve as a relevance detection system. Further, the model demonstrates how abnormal top-down drive and dysregulated local inhibition in the amygdala and in the cortex can contribute to the attentional symptoms that accompany several neuropsychiatric disorders.R01MH057414 - NIMH NIH HHS; R01 MH057414 - NIMH NIH HHS; R01 MH101209 - NIMH NIH HHS; R01NS024760 - NINDS NIH HHS; R01MH101209 - NIMH NIH HHS; R01 NS024760 - NINDS NIH HH

Implications and Ramifications of a Sample-Size Approach to Intuition

[...from the chapter] In the present article, we delineate a different approach, which is by no means inconsistent, but largely overlaps with the aforementioned definitions. However, our approach is simpler and refrains from a number of rather strong assumptions to which other conceptions subscribe. Using a simple and straightforward criterion, we define intuition in terms of the size of the sample used in reaching a decision: Judgments and decisions are intuitive to the extent that they rest on small samples.

Intolerance of uncertainty and impulsivity in opioid dependency

Opioid abuse has reached epidemic status in the United States, and opioids are the leading cause of drug-related deaths in Australia and worldwide. One factor that has not received attention in the addiction literature is intolerance of uncertainty (IU). IU is personality trait characterised by exaggerated negative beliefs about uncertainty and its consequences. This thesis investigates the links between IU and impulsive decision-making in the context of opioid-dependency. Four experimental studies examined impulsive decision-making from multiple perspectives, and assessed for the first time how impulsivity interacts with IU in opioid-dependent individuals. Across all four studies, opioid-dependent adults reported markedly higher levels of IU compared to a healthy control group. This consistent result provides strong evidence that IU is a personality trait that is related to drug addiction, whether it may be a pre-morbid risk factor, a result of chronic drug use or a co-occurring phenomenon based on shared neural correlates. A common thread between studies was that IU and impulsivity were meaningfully related in opioid-dependent individuals, but not in control groups. Specifically, IU was correlated with self-reported impulsive personality traits, poor attentional control, risk taking for monetary losses and risk-aversion for health improvements. No meaningful correlations were found between IU and impulsivity in control participants. These findings have important implications for addiction prevention and therapy. It is commonly accepted that pharmaceutical opioids are a driving factor for the upsurge in heroin abuse, and IU may be helpful to screen for at-risk individuals. Furthermore, addiction treatment could benefit by addressing IU in order to improve faulty beliefs about and reactions to uncertainty

What Lies Beneath: How Paranoid Cognition Explains the Relations Between Transgender Employees\u27 Perceptions of Discrimination at Work and their Job Attitudes and Wellbeing

With the recent public gender transitions of celebrities like Caitlin Jenner, greater visibility of transgender characters on television (e.g., Transparent), and controversial laws enacted in some U.S. states and cities banning transgender employees from accessing bathrooms that align with their gender identities, issues of gender expression have been thrust into the national spotlight. In order to promote greater awareness and acceptance of transgender people, greater knowledge of their life experiences is needed. Adding to a small, but growing, body of research on the work experiences of transgender individuals, the goal of the present study is to examine the cognitive processes that shape these individuals\u27 experiences in the workplace. Drawing on existing theory and research on paranoia, we examine the role of paranoid cognition, defined by hypervigilance, rumination, and sinister attributional tendencies, in explaining the relations between transgender employees\u27 perceptions of workplace discrimination and their job attitudes and psychological wellbeing. Our findings suggest that perceptions of transgender discrimination in the workplace are positively related to paranoid cognition at work; paranoid cognition is positively related to transgender employees\u27 turnover intentions and emotional exhaustion and negatively related to their job satisfaction; and paranoid cognition at work mediates the relations between perceptions of discrimination and each of these outcomes. We conclude by discussing the implications of our results, as well as avenues for future research on the work experiences of transgender employees