Rutgers-Princeton Center for Computational Cognitive Neuropsychiatry

Oriel FeldmanHall
Department of Department of Cognitive, Linguistic and Psychological Sciences
Brown University

Interacting with others is one of the most inherently uncertain acts we embark on. There are a multitude of unknowns, including how to express ourselves, who to confide in, or whether to engage in risky behavior with our peers. All this uncertainty makes successfully navigating the social world a tremendous challenge. Combining behavioral and neuroscientific methods, we explore the social and emotional factors that shape and ultimately guide how humans learn to make adaptive decisions amongst this great uncertainty. In particular, we borrow models from the animal learning literature, and methods from computational neuroscience and machine learning, to examine how humans experience, process, and resolve this uncertainty to make more adaptive decisions.  

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Yael Milgram
Department of Psychology
Harvard University

Emotion regulation deficits contribute to many mental health disorders. Most research sought to understand these deficits by investigating how people regulate emotions – specifically, which emotion regulation strategies people use and how effectively they implement them. However, emotion regulation strategies are used at the service of attaining desired emotional states. Therefore, people who struggle with psychopathology might differ not only in the strategies they use, but also in the emotional states they desire. In this talk, I will present evidence suggesting that some clinical populations differ from non-clinical populations in the degree to which they are motivated to experience painful and pleasant emotions, with an emphasis on Major Depressive Disorder. I will then present studies testing the implications of these differences for the use of emotion regulation strategies, emotional experiences, and mental health. Finally, I will offer a new perspective for understanding these findings, according to which motivation to experience painful emotions in psychopathology might reflect a form of emotional self-harm.

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Laura Bustamante
Department of Psychological and Brain Sciences
Washington University in St. Louis

In this talk I will present results from a recently completed CCNP study and seek feedback on a proposed add-on neuroimaging session.

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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