Computational Psychiatry in Borderline Personality Disorder

TL;DR

This paper reviews how computational psychiatry methods are increasingly used to understand Borderline Personality Disorder by analyzing molecular, circuit, and behavioral data, especially in real-world social contexts.

Contribution

It highlights recent advances and suggests future research should focus on collaborative, clinically relevant experiments integrating computational approaches in BPD.

Findings

Computational methods help understand BPD's molecular and circuit basis.

Ecologically valid data collection in social settings is expanding.

Integrating behavior with molecular and circuit data offers new insights.

Abstract

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.