Rutgers-Princeton Center for Computational Cognitive Neuropsychiatry

Nadja R. Ging-Jehli
Department of Cognitive, Linguistic & Psychological Sciences
Brown University

In the digital age, where large-scale data collection is increasingly feasible, computational psychiatry faces a key question: can we rely solely on online studies with calibrated tasks that focus on behavior, or do we still need in-person studies that integrate physiological measures? Across two studies, I will demonstrate that combining mechanistic assessments with physiological measures provides more insights than behavioral analyses alone. In the first study, we employed an instrumental learning task to investigate learning impairments in major depressive disorder (MDD) and bipolar disorder (BP). The mechanistic task allowed us to distinguish between processes linked to reinforcement learning and working memory. Despite similar behavioral deficits across clinical groups, model-based EEG analyses revealed distinct neurocomputational profiles specific to each disorder. In the second study, we investigated how adults with attention-deficit/hyperactivity disorder (ADHD) respond to contextual changes during a social strategic interaction game, using eye-tracking and diffusion decision modeling to analyze their behavior. Although adults with ADHD engaged in riskier actions when stakes were high, model-based eye-tracking revealed that this was not due to impulsivity. Instead, they focused more on the potential benefits than the costs of collaboration. Further analysis showed that individuals with higher ADHD symptom severity were more sensitive to contextual changes, highlighting the dynamic nature of impulsivity.These findings emphasize the value of neurocomputational assessments, incorporating physiological measures, in distinguishing psychiatric disorders and capturing reactivity to contextual change as a potentially important transdiagnostic marker.

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Gabriela Rosenblau
Department of Psychological and Brain Sciences
The George Washington University

This talk will discuss our approach to examining social knowledge and how it is used for learning. In current projects, we are extending our previous line of work on social learning to investigate how various adult and adolescent cohorts flexibly represent, employ, and acquire rich social knowledge when learning about others. We are using a combination of computational modeling, and neuroimaging to understand how adults and adolescents efficiently employ and refine social knowledge structures during learning. These projects also involve individuals with clinical disorders, such as Autism Spectrum Disorder and Borderline Personality Disorder, but can be integrated into a transdiagnostic approach to specifying social deficits across a wide range of clinical disorders.

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Jonathan Rosier
Institute of Cognitive Neuroscience
Div of Psychology & Lang Sciences
University of College London

Motivational symptoms of depression are debilitating and associated with poor clinical outcome, but the mechanisms underlying them are poorly understood. This talk will present data examining how cognitive processes related to effort-based decision making for reward are associated with depressive symptoms, using a computational approach. In the first part of the talk results from two cross-sectional behavioural studies, including >250 participants (healthy volunteers, unmedicated depressed patients, first degree relatives and remitted depressed patients), will be presented. Participants completed a rewarded physical effort task using a grip squeeze device, and motivational symptoms were assessed through questionnaires. Data were analysed using a hierarchical computational approach, with model parameters estimated in a Bayesian framework using sampling. In the non-clinical study (N=90), general depressive symptoms were associated with lower reward sensitivity, while anhedonia was related to a lack of willingness to engage in high effort challenges. In the clinical study (N=180), current or past depression was associated with a lower overall propensity to accept challenges, independent of reward or effort level. Preliminary results from studies examining the effect of L-Dopa on effort-based decisions in healthy and depressed volunteers (N=80) and patients with Parkinson’s disease with (N=30) and without depression (N=30) will be presented, with clear effects on effort-based decision making observed only in the latter. Ongoing work examining the impact of physical activity on motivational symptoms and effort-based decisions will be outlined briefly. These studies illuminate the cognitive and brain mechanisms contributing to depressive symptoms related to disrupted motivational processing, providing some clues to potential avenues for intervention strategies for these debilitating symptoms.

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Julia Sheffield
Department of Psychiatry & Behavioral Sciences and Psychopharmacology
Vanderbilt University Medical Research Center

Persecutory delusions are common and distressing psychotic symptoms that represent the extreme end of a paranoia continuum. Treatments for persecutory delusions require advancement. Understanding the cognitive mechanisms underlying paranoia and persecutory delusions can help identify novel targets. In this talk, Dr. Sheffield will present background on the predictive coding model of delusions and evidentiary support for elevated volatility priors as a contributor to delusion severity. Dr. Sheffield utilizes longitudinal and clinical trials designs to test the modifiability of volatility priors, and their neurobiological correlates, in order to determine whether they represent a viable treatment target.

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Avram Holmes
Department of Psychiatry
Robert Wood Johnson Medical School (RWJMS)

Research in my laboratory focuses on discovering the fundamental organization of large-scale human brain networks. A core motivation that drives this work is the search for specific network-level signatures or “fingerprints” that co-vary with heritable behavioral variation in the general population and mark vulnerability for psychiatric illness onset. To date, research on the biological origins of psychopathology has largely focused on discrete illness categories. Although patient groups within this diagnostic system are treated as distinct entities, there are often murky boundaries between health and disease and across the disorders themselves. To establish the etiology of these complex syndromes, we must account for diagnostic heterogeneity, both relatively selective and disorder-spanning symptoms, and the dimensional nature of genetic risk.
In this talk, I will present converging lines of research from my laboratory that aim to identify neurobiological markers of psychiatric illness. First, I will discuss our recent efforts to link individual variability across the collective set of functional brain connections with the nature and severity of symptom profiles across unipolar depression, bipolar depression, and schizophrenia. Second, I will discuss a pending research project where we will seek to identify cellular and genetic contributors to the functioning of large-scale brain networks and characterize their relationship to longitudinal trajectories of clinical presentation in patients with affective and psychotic illnesses.

Alexander Harris
Department of Psychiatry
Columbia University

Reward seeking is disrupted in a variety of psychiatric disorders impacted by stress. However, it remains unclear what neural activity is responsible for stress-induced disruptions in reward seeking. In this talk, I will describe our work using in vivo electrophysiology and optogenetic manipulations in freely moving mice demonstrating that a subpopulation of inhibitory neurons in the reward circuit form the link between acute stress and subsequent decreased reward anticipation. I will also share our ongoing work exploring the role of reward circuitry during the social buffering of stress.  

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Katharina Schmack
Department of Psychiatry
Francis Crick Institute & University College London

Is computational psychiatry more than a buzzword? This talk will explore how computational psychiatry can capture psychotic symptoms across species and facilitate biological investigations into psychosis. I will present a computational-behavioural approach for measuring hallucination-like perception in humans and mice, which has helped to elucidate a causal neural circuit mechanism relevant to psychosis. I will conclude by discussing the tremendous opportunities that arise from using computational psychiatry to unlock the toolkit of biological science for psychiatry.  

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Warren Mansell
Professor of Mental Health
Curtin University, Perth

Perceptual Control Theory (PCT) was first introduced by William T. Powers in 1960 to provide an alternative account of behaviour to the dominant behavioural theories and emergent cognitive theories at the time. Derived from the principles of classical control engineering, Powers proposed that behaviour is the control of perceptual input, and specified the computational framework to operationalise the purposive behaviour of living organisms, including humans. Control is the default functioning of our brain and bodies, and it runs smoothly unless conflict occurs – defined as having opposing goal states for the same variable. According to PCT, psychopathology is characterised by loss of control that is maintained by processes that exacerbate conflict and/or prevent the exploration of conflict within conscious awareness. I will provide an overview of my own work in this field including: (a) basic lab tests of PCT; (b) modelling of individualised sensorimotor control processes; (c) modelling of goal conflict resolution; (d) plans for modelling of mental health recovery for personalised interventions – known as Dynamic Catalysts.  

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Michael Treadway
Department of Psychology
Emory University

Despite the broad literature examining the causes and consequences of mood, the concept of mood remains to be ambiguous. Prior work suggests that reward, effort, and exploration each contribute to mood, yet most laboratory assessments have assessed the impact of these variables in isolation. In this talk, I will present data from six samples using a novel effortful exploration task. We find that effort expenditure, exploration, reward and their trial-wise prediction-errors are independent predictors of momentary mood. Importantly, effort appeared to have dual, opposing effects on mood: on one hand, increased effort expenditure predicted more negative mood, and on the other hand, reward predicted subsequent mood only when foraging required effort. Finally, I will present preliminary evidence supporting a causal role for dmPFC in the impact of effort on mood using temporal interference (TI), a novel non-invasive deep-brain stimulation method. Taken together, these data seek to advance our understanding of mood and shed light on the paradoxical nature of effort as having both value-enhancing and discounting effects.  

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Rebecca Kazinka
Department of Psychiatry
University of Minnesota Medical School

Persecutory ideation is a common experience in psychosis, yet also presents in other neuropsychiatric disorders and even in the general population. However, our understanding of the neural mechanism of persecutory ideation is relatively unclear. My work focuses on building a construct strongly related to persecutory ideation to better understand the associated neural processes that drive decisions. In this talk, I will present our findings showing that spite sensitivity, i.e., a worry that another person will intentionally incur a loss to ensure that you do as well, provides a model for understand persecutory ideation. We built a computational model of spite sensitivity using an economic game called the Minnesota Trust Game (MTG), which is a modified version of the trust game with two conditions in which the partner is either incentivized or disincentivized to behave fairly. Through several studies in undergraduates, individuals with psychosis, and monozygotic twins, we show that spite sensitivity predicts persecutory ideation and is associated with activation in the lateral OFC. This model provides a means of quantifying persecutory ideation and may be useful for future clinical applications.  

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