Psychological dynamics in different classes of individuals

Several complex psychological phenomena, including for instance psychopathology and healthy personality emerge from interactions among lower-level phenomena such as cognitions, behaviors, emotions, motivations, and symptoms. Psychologists are often interested to examine whether and how the dynamics underlying different classes of individuals (e.g., patients and controls) are similar or different. The Gaussian Graphical Model (GGM) has been used as a parsimonious representation of between-person and within-person dynamics in psychology. GGMs are typically estimated from psychological data using the graphical lasso algorithm, which does not accommodate for multiple classes of individuals. The Fused Graphical Lasso can be used to jointly estimate GGMs in different classes and to identify similarities and differences in their underlying dynamics. We present applications of FGL to several psychological domains, including personality, situation perception, social interactions, and psychological disorders such as the post-traumatic stress disorder, pathological narcissism, and the borderline personality disorder. We discuss the most important insights afforded by this methodology for the dynamics underlying these phenomena.