Rutgers-Princeton Center for Computational Cognitive Neuropsychiatry

Frederike Petzschner
Department of Psychiatry and Human Behavior
Brown University

OCD has been conceptualized as a disorder arising from dysfunctional beliefs, such as overestimating threads or pathological doubts. Yet, how these beliefs lead to compulsions and obsessions remains unclear. Here, we develop a computational model to examine the specific beliefs that trigger and sustain compulsive behavior in a simple handwashing scenario. Our results demonstrate that a single belief disturbance – a lack of trust in one’s avoidance action– can trigger and maintain compulsions and is directly linked to compulsion severity. This distrust can further explain a number of seemingly unrelated phenomena in OCD including the role of not-just-right feelings, intolerance to uncertainty, overestimation of threat or perfectionisms, and deficits in reversal and state learning. In conclusion, our findings shed new light on the underlying beliefs that drive compulsive behavior in OCD, providing a step forward in building a more comprehensive theory of this complex condition.

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Gal Shoval
Princeton Neuroscience Institute
Princeton University

Gal Shoval, the clinical supervisor of the CCNP, will present the principles of diagnostic procedures of psychopathology and discuss different challenges in making diagnosis in therapy and research. The participants are welcome to prepare ahead and share some of their own concerns and prior experience for a vigorous discussion.

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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.

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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.

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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.

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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.

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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.

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Judith Mildner
Department of Psychology
Princeton University

The dynamics of spontaneous thought in mood disorders

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.

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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.

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