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. 2017 Mar;4(1):31-40.
doi: 10.1007/s40473-017-0104-y. Epub 2017 Feb 4.

Computational Psychiatry in Borderline Personality Disorder

Sarah K Fineberg  1 , Dylan Stahl  1   2 , Philip Corlett  1
Affiliations

Computational Psychiatry in Borderline Personality Disorder

Sarah K Fineberg et al. Curr Behav Neurosci Rep. 2017 Mar.

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.

Keywords: Bayesian learning; Borderline Personality Disorder; computational psychiatry; neural circuit; social cognition; social rejection; trust.

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