14 December 2022: Too Much of a Good Thing? Modeling Excess Goal Pursuit in Anorexia Nervosa

Ann Haynos
Department of Psychology
Virginia Commonwealth University

Historically, physical and mental health concerns have been conceptualized as resulting from deficits in the ability to pursue long-term goals resulting from dysfunctions in decision-making abilities and underlying executive functioning brain circuitry. However, this perspective neglects a subset of health concerns that arise from “too much of a good thing” or excess pursuit of goals that society typically encourages (e.g., order/organization, work or academic performance). This talk will focus on one such presentation: the over-pursuit of weight loss that characterizes anorexia nervosa. In this talk, I will present data from a series of studies using a neuroeconomic approach and computational modeling (i.e., Hierarchical Drift Diffusion Modeling) of data derived from a translational foraging task to demonstrate that: 1) anorexia nervosa may be maintained by over-use of computational strategies (i.e., rule-based or value-congruent decision-making) designed to maximize positive outcomes; 2) these strategies appear to be supported by over-engagement of executive functioning circuits conventionally considered to be positive for supporting mental health; and 3) this phenotype expands beyond restrictive eating disorders to other mental health concerns characterized by excess goal pursuit (e.g., “work addiction”). These findings suggest that, paradoxically, that it may be paramount to reduce use of “good” executive functioning skills to treat this group of clinical concerns. Finally, I will provide a roadmap for future research aimed at understanding the computational pathways into severe and underserved problems of excess goal pursuit.

30 November 2022: Temporal context effects in risky monetary decision-making

Hayley Brooks
Department of Psychology
University of Denver

Up until the late 20th century, influential decision theorists did not consider recent events (e.g. previous choices or outcomes) relevant to risk taking, in part because risky decision-making settings are not inherently contextual or temporal in nature. For example, an outcome on a previous trial does not causally influence or directly alter the outcome on a subsequent trial. However, over the last three decades, research spanning psychology, economics and neuroscience has begun to explore the possibility that risky decision-making may instead be fundamentally contextually sensitive. Using a combination of approaches, including computational modeling of behavior, physiological arousal, and fMRI, my research examines how risky monetary decision-making is temporally context-dependent. I will present results from a series of studies that demonstrate both value-dependent and value-independent effects of temporal context on risky choice behavior at multiple timescales. These data also suggest that risky choices reflect not only temporal context, but how people compare that context to their evolving expectations (i.e., a dynamic reference point). These results are perplexing because relying on recent events at any timescale appears to be at odds with the assumed goal of risky decision-making: to maximize payoff. I will discuss potential mechanisms, including physiological arousal and the hypothesized neural mechanisms, that may support context effects in risk. Finally, I will present a new project leveraging insights from emotion regulation and cognitive control research to understand how using cognitive strategies to change goals may mitigate such temporal context effects in an effort to improve risky decision-making.

16 November 2022: The Bayesian Battery : An analysis of brain computations under uncertainty

Caroline Bévalot
National Institute of Health and Medical Research, Unicog, Gif-sur-Yvette
Sorbonne University, Paris

Our brain is constantly facing uncertainty. One way to reduce uncertainty is to build a representation of our environment, use this representation together with our sensory inputs and update it according to its confidence. However, subjects are more or less optimal in doing so and the difference is striking in psychiatric disorders. This difference can be characterized under the Bayesian framework which constitutes an optimum of the computations under uncertainty. Yet, up to now, characterization of subjects’ behavior in psychiatric disorders and especially schizophrenia is very heterogeneous. During my PhD, we analysed several factors of this heterogeneity. First, we studied whether alterations of the Bayesian inference could be compared between experiments using implicit or explicit priors. We found a dissociation in the way implicit and explicit priors are used and a difference in the computations they elicit. Secondly, we identified two main types of uncertainty about the prior representation. Each of them is related to distinct steps in the Bayesian inference : either decision, or learning. We studied how psychotic, anxious and autistic features were associated with an alteration at one of these steps. We showed that subjects with higher psychotic features tend to neglect the sensory likelihood at the decision step. We showed the opposite pattern in anxious disorders. Finally, using magnetoencephalography, we wondered whether the alterations of the Bayesian inference were a core alteration leading to symptoms in schizophrenia rather than constituting a side alteration.

2 November 2022: Using Language to Measure and Modify Emotion Regulation and Mental Health: From the Lab to the E-Clinic

Eric Nook
Department of Psychology
Princeton University

Both theory and empirical evidence show that taking a distanced perspective on stressors helps us down-regulate our negative emotional reactions and respond more adaptively. But what if our words, our language, could be tools for increasing psychological distance, and consequently emotion regulation? This talk will present a series of studies on linguistic distancing (i.e., changing one’s words to increase psychological distance by reducing use of first-person singular pronouns like “I” and present tense-verbs) and its relationship with emotion regulation and mental health. Experimental studies (Ns = 107-207) showed that having participants write about aversive images without using the word “I” or present-tense verbs reduced their self-reported negative affect. Conversely, asking participants to engage in emotion regulation (by cognitively reinterpreting or reappraising) aversive images while writing their thoughts revealed spontaneous increases in linguistic distance that correlated with reap-praisal success. Finally, a large naturalistic study of psychotherapy transcripts (N = 6,229) showed that linguistic distancing increased over treatment and tracked within-person reductions in depression and anxiety symptoms. All studies included replications of key findings, strengthening conclusions. Together, this line of research shows that language is a powerful tool for measuring and manipulating both emotion regulation and mental health at large scales.

26 October 2022: Scaling Single-Session Interventions to Bridge Gaps in Mental Healthcare Ecosystems

Jessica Schleider
Department of Psychology
Stony Brook University

In this talk, I will overview my lab’s research on developing brief, mechanism-targeted interventions for youth mental health problems; identifying the mechanisms underlying their effects; and testing novel approaches to dissemination. First, I will present meta-analytic evidence supporting the promise of very brief (single-session) youth mental health interventions. Next, I will share work on two interconnected targets that may inform the design of such interventions: youth cognitions, such as beliefs about whether personal traits are malleable (versus fixed) by nature, and family-level factors, such as parenting behaviors and expectancies for mental health treatment. This will include results from recent, large-scale randomized trials targeting youths and parents testing single-session, online interventions. Finally, I will preview ongoing and future projects, which aim to harness modifiable targets to build novel, theoretically precise interventions; capitalize on technological innovations and cross-sector partnerships to expand how and where such interventions might be accessed; and tailor evidence-based single-session interventions for historically underserved populations, including sexual minority, gender-diverse, and racial and ethnic minority youth.

28 September 2022: Associations Between Neural Activity During Reward-Effort Decision-Making and Suicidal Ideation in a Recently Traumatized Sample

Courtney Forbes
Department of Psychology
University of California, Los Angeles (UCLA)

Background: Trauma exposure is associated with heightened risk for suicidality. Reward processing abnormalities have also been linked to suicidality; however, these relations have not been examined among individuals with recent trauma exposure. Research in this domain could inform understanding of specific risk factors for suicidality and highlight targets for intervention. Thus, the present study examined cross-sectional and longitudinal relations between self-report, behavioral, and neural reward processing and suicidal ideation (SI) in a sample with past 2-week trauma exposure.
Method: Participants were adults (N = 19, mean age = 31, 79% women, 53% racial/ethnic minority) recruited from hospital emergency departments. Within two weeks of the traumatic event, participants completed several self-report measures of reward processing as well as a behavioral fMRI task (the Staggered Effort-Based Decision-Making Task; Arulpragasam et al., 2018), in which they made decisions about whether to exert effort to obtain monetary rewards. Task-based neural activity was examined via whole-brain analyses, corrected for multiple comparisons, using the fixation point between trials as an implicit baseline. SI was assessed using the Quick Inventory of Depressive Symptomatology.
Results: No self-report or behavioral measure of reward processing was associated with SI, either cross-sectionally or longitudinally. Task-based activation in regions relevant to reward processing, specifically the insula and thalamus (rs = -.70 to -.53, ps ≤ .05), significantly correlated with baseline SI. Task-based activation in regions relevant to cognitive and regulatory processes (e.g., superior and inferior frontal gyri; paracingulate gyrus) also significantly correlated with baseline SI (rs = -.71 to -.46, ps < .05). Task-based activation did not significantly predict SI at 3-month follow-up.
Conclusions: In a recently traumatized sample, less activation in neural regions relevant to decision-making during a reward-effort task was associated with more frequent and intense SI cross-sectionally, but not longitudinally. If replicated, these results may indicate that impaired reward-effort decision-making following traumatic exposure contributes to risk for suicide. Relations between SI and task-based activation in regions related to cognitive and regulatory processes warrant further investigation.

22 June 2022: Identifying and targeting cognitive control dysfunction in bulimia nervosa

Laura Berner
Department of Psychiatry
Ichan School of Medicine at Mount Sinai

Every day, our brains bring together information from our bodies and environments to control our eating behavior. Extremes in the control of eating behavior, as well as other non-food-related behaviors, characterize individuals with bulimia nervosa. I will present research that uses neuroimaging and well-established and novel paradigms to investigate how various aspects of the control process go awry in bulimia nervosa, and how these disturbances may drive binge eating and purging. Further, I will discuss recent and ongoing and research that leverages computational modeling to test whether problems flexibly adjusting control-related strategies and difficulty tracking one’s control over others people’s behavior may maintain bulimic symptoms. Finally, I will review how disruptions in control and its underlying circuitry may help us develop new treatments.

View a recording of this session here.

15 June 2022: The computational varieties of emotion

Eran Eldar
Department of Cognitive and Brain Sciences
The Hebrew University of Jerusalem

Emotions ubiquitously impact action, learning, and perception, yet their essence and role remain widely debated. The recent emergence of computational cognitive accounts of emotion has the potential to offer greater conceptual precision informed by normative principles and neurobiological data. However, these nascent efforts have so far been mutually inconsistent and limited in scope. In this talk, I will offer an integrative computational account of the human emotional landscape as composed of different emotions, each promoting adaptive behavior by mediating a distinct type of inference concerning oneself and the environment. This account builds on three parsimonious assumptions. First, that the inference each emotion mediates can be deduced from the circumstances that evoke it and the behavior it promotes. Second, emotions that primarily differ in valence reflect similar inferences about positive versus negative experiences. Third, emotional states that primarily differ in scope (timespan and object-specificity) reflect similar inferences about the immediate context versus the general environment. We apply these principles to integrate a large body of empirical research on the causes and consequences of different emotions with the computational and cognitive neuroscience of learning and decision making. The results bring to light an emotional ecosystem composed of multiple interacting elements which together serve to evaluate outcomes (pleasure & pain), learn expected values (happiness & sadness), adjust behavior (content & anger), and plan in order to realize (desire & hope) or avoid (fear & anxiety) uncertain future prospects.

View a recording of this session here.

25 May 2022: How does action training affect perception and cognition?

Joo-Hyun Song
Department of Cognitive, Linguistic & Psychological Sciences
Brown University

Our daily experience can be thought of as a sequence of acquiring perceptual input to make decisions, then planning and executing appropriate actions. Hence, examining the influence of perception on action flows logically. Investigating the inverse may seem unusual. However, in a series of studies, we have accumulated evidence supporting co-dependence between action and perception. First, we demonstrated that simultaneous easy-action preparation or even prior action training can enhance sensitivity to an action-relevant low-level visual property, such as orientation. This newly-observed modulation of visual perception by action fluency cannot be explained by the traditional sequence of information processing stages. In addition, we discovered that improvement of motor timing enhances the sensitivity of time perception, even for implicit timing patterns inherent to a complex motor task. We interpret this as evidence for a shared temporal mechanism between perception and movement, regardless of the rhythmicity or complexity of the motor tasks. Furthermore, we found that learning a visuomotor rotation, but not actions without a rotation component, facilitated response time on a subsequent mental rotation task. This result suggests that visuomotor learning can enhance mental processes through common components. Taken together, our work supports a close interplay between the action system and perception, which highlights the necessity of an integrated approach to understand our adaptive behavior in a complex environment. The integrated approach would allow us to investigate a range of broader questions that would have not been possible by studying the motor system alone or vision alone.

View a recording of this session here.