dc.contributor.author	Cui, Zhuoya	en
dc.contributor.committeechair	Casas, Brooks	en
dc.contributor.committeechair	Chiu, Pearl H.	en
dc.contributor.committeemember	Moran, Rosalyn J.	en
dc.contributor.committeemember	Morozov, Alexei	en
dc.contributor.department	Graduate School	en
dc.date.accessioned	2021-05-27T08:00:34Z	en
dc.date.available	2021-05-27T08:00:34Z	en
dc.date.issued	2021-05-26	en
dc.description.abstract	Impaired social functioning conferred by mental illnesses has been constantly implicated in previous literatures. However, studies of social abnormalities in psychiatric conditions are often challenged by the difficulties of formalizing dynamic social exchanges and quantifying their neurocognitive underpinnings. Recently, the rapid growth of computational psychiatry as a new field along with the development of multiplayer economic paradigms provide powerful tools to parameterize complex interpersonal processes and identify quantitative indicators of social impairments. By utilizing these methodologies, the current set of studies aimed to examine social decision making during multiplayer economic games in participants diagnosed with depression (study 1) and combat-related post-traumatic stress disorder (PTSD, study 2), as well as an online population with elevated symptoms of borderline personality disorder (BPD, study 3). We then quantified and disentangled the impacts of multiple latent decision-making components, mainly social valuation and social learning, on maladaptive social behavior via explanatory modeling. Different underlying alterations were revealed across diagnoses. Atypical social exchange in depression and BPD were found attributed to altered social valuation and social learning respectively, whereas both social valuation and social learning contributed to interpersonal dysfunction in PTSD. Additionally, model-derived indices of social abnormalities positively correlated with levels of symptom severity (study 1 and 2) and exhibited a longitudinal association with symptom change (study 1). Our findings provided mechanistic insights into interpersonal difficulties in psychiatric illnesses, and highlighted the importance of a computational understanding of social function which holds potential clinical implications in differential diagnosis and precise treatment.	en
dc.description.abstractgeneral	People with psychiatric conditions often suffer from impaired social relationships due to an inability to engage in everyday social interactions. As different illnesses can sometimes produce the same symptoms, social impairment can also have different causes. For example, individuals who constantly avoid social activities may find them less interesting or attempt to avoid potential negative experiences. While those who display elevated aggression may have a strong desire for social dominance or falsely believe that others are also aggressive. However, it is hard to infer what drives these alterations by just observing the behavior. To address this question, we enrolled people with three different kinds of psychopathology to play an interactive game together with another player and mathematically modeled their latent decision-making processes. By comparing their model parameters to those of the control population, we were able to infer how people with psychopathology made the decisions and which part of the decision-making processes went wrong that led to disrupted social interactions. We found altered model parameters differed among people with major depression, post-traumatic stress disorder and borderline personality disorder, suggesting different causes underlying impaired social behavior observed in the game, the extent of which also positively correlated with their psychiatric symptom severity. Understanding the reasons behind social dysfunctions associated with psychiatric illnesses can help us better differentiate people with different diagnoses and design more effective treatments to restore interpersonal relationships.	en
dc.description.degree	Doctor of Philosophy	en
dc.format.medium	ETD	en
dc.format.mimetype	application/pdf	en
dc.identifier.other	vt_gsexam:29923	en
dc.identifier.uri	http://hdl.handle.net/10919/103528	en
dc.language.iso	en	en
dc.publisher	Virginia Tech	en
dc.rights	In Copyright	en
dc.rights.uri	http://rightsstatements.org/vocab/InC/1.0/	en
dc.subject	computational psychiatry	en
dc.subject	behavioral economics	en
dc.subject	reinforcement learning	en
dc.subject	social decision making	en
dc.title	Understanding social function in psychiatric illnesses through computational modeling and multiplayer games	en
dc.type	Dissertation	en
dc.type.dcmitype	Text	en
thesis.degree.discipline	Translational Biology, Medicine and Health	en
thesis.degree.grantor	Virginia Polytechnic Institute and State University	en
thesis.degree.level	doctoral	en
thesis.degree.name	Doctor of Philosophy	en

Understanding social function in psychiatric illnesses through computational modeling and multiplayer games

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