Computational Psychiatry in Borderline Personality Disorder

• Published in: Current behavioral neuroscience reports Vol. 4; no. 1; pp. 31 - 40
• Main Authors: Fineberg, Sarah K, Stahl, Dylan S, Corlett, Philip R
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 01.03.2017; Springer Nature B.V
• Subjects: Animal cognition; Behavior; Behavioral Therapy; Borderline personality disorder; Datasets; Decision making; Experiments; Games; Hypotheses; Medicine; Medicine & Public Health; Narratives; Neurology; Neurosciences; Paradigms; Pediatrics; Personality and Impulse Control Disorders (R Lee; Personality disorders; Psychiatry; Section Editor; Social interaction; Topical Collection on Personality and Impulse Control Disorders; Computational psychiatry; Bayesian learning; Social rejection; Neural circuit; Trust; Borderline personality disorder; Social cognition; trust; computational psychiatry; neural circuit; social cognition; Borderline Personality Disorder; social rejection
• ISSN: 2196-2979; 2196-2979
• DOI: 10.1007/s40473-017-0104-y

Purpose of Review We review the literature on the use and potential use of computational psychiatry methods in borderline personality disorder. Recent Findings Computational approaches have been used in psychiatry to increase our understanding of the molecular, circuit, and behavioral basis of mental illness. This is of particular interest in BPD, where the collection of ecologically valid data, especially in interpersonal settings, is becoming more common and more often subject to quantification. Methods that test learning and memory in social contexts, collect data from real-world settings, and relate behavior to molecular and circuit networks are yielding data of particular interest. Summary Research in BPD should focus on collaborative efforts to design and interpret experiments with direct relevance to core BPD symptoms and potential for translation to the clinic.