A Computational Account of Borderline Personality Disorder: Impaired Predictive Learning about Self and Others Through Bodily Simulation

Abstract

Social dysfunction is a prominent and disabling aspect of borderline personality disorder. We reconsider traditional explanations for this problem, especially early disruption in the way an infant feels physical care from its mother, in terms of recent developments in computational psychiatry. In particular, social learning may depend on reinforcement learning though embodied simulations. Such modeling involves calculations based on structures outside the brain such as face and hands, calculations on one's own body that are used to make inferences about others. We discuss ways to test the role of embodied simulation in BPD and potential implications for treatment.

Keywords: associative learning; attachment; borderline personality disorder; computational psychiatry; embodied simulation.

Figure 1

Embodied simulation is a computational path from observing an action (such as scrunched eyebrows and mouth) in someone (A) to making a prediction about that action’s meaning (mad) (C). We depict several aspects of this process (as sequential steps here for clarity) (B): (a) imagining the other’s action, (b) imagining oneself, (c) thinking of one’s own experiences with that action and low level activation of motor program to do that action, and (d) development of a model based on the observed other and personal simulated thoughts/feelings. The model can be used to predict the other’s intentions (C).