Computational Psychiatry in Borderline Personality Disorder

Attachment and borderline personality disorder as the dance unfolds: A quantitative analysis of a novel paradigm

Current research on personality disorders strives to identify key behavioural and cognitive facets of patient functioning, to unravel the underlying root causes and maintenance mechanisms. This process often involves the application of social paradigms - however, these often only include momentary affective depictions rather than unfolding interactions. This constitutes a limitation in our capacity to probe core symptoms, and leaves potential findings uncovered which could help those who are in close relationships with affected individuals. Here, we deployed a novel task in which subjects interact with four unknown virtual partners in a turn-taking paradigm akin to a dance, and report on their experience with each. The virtual partners embody four combinations of low/high expressivity of positive/negative mood. Higher scores on our symptomatic measures of attachment anxiety, avoidance, and borderline personality disorder (BPD) were all linked to a general negative appraisal of all the interpersonal experiences. Moreover, the negative appraisal of the partner who displayed a high negative/low positive mood was tied with attachment anxiety and BPD symptoms. The extent to which subjects felt responsible for causing partners' distress was most strongly linked to attachment anxiety. Finally, we provide a fully-fledged exploration of move-by-move action latencies and click distances from partners. This analysis underscored slower movement initiation from anxiously attached individuals throughout all virtual interactions. In summary, we describe a novel paradigm for second-person neuroscience, which allowed both the replication of established results and the capture of new behavioural signatures associated with attachment anxiety, and discuss its limitations.

To be or not to be: The active inference of suicide

Suicide presents an apparent paradox as a behavior whose motivation is not obvious since its outcome is non-existence and cannot be experienced. To address this paradox, we propose to frame suicide in the integrated theory of stress and active inference. We present an active inference-based cognitive model of suicide as a type of stress response hanging in cognitive balance between predicting self-preservation and self-destruction. In it, self-efficacy emerges as a meta-cognitive regulator that can bias the model toward either survival or suicide. The model suggests conditions under which cognitive homeostasis can override physiological homeostasis in motivating self-destruction. We also present a model proto-suicidal behavior, programmed cell death (apoptosis), in active inference terms to illustrate how an active inference model of self-destruction can be embodied in molecular mechanisms and to offer a hypothesis on another puzzle of suicide: why only humans among brain-endowed animals are known to practice it.

How childhood maltreatment alters perception and cognition - the predictive processing account of borderline personality disorder

Borderline personality disorder (BPD) is a severe mental disorder, comprised of heterogeneous psychological and neurobiological pathologies. Here, we propose a predictive processing (PP) account of BPD to integrate these seemingly unrelated pathologies. In particular, we argue that the experience of childhood maltreatment, which is highly prevalent in BPD, leaves a developmental legacy with two facets: first, a coarse-grained, alexithymic model of self and others - leading to a rigidity and inflexibility concerning beliefs about self and others. Second, this developmental legacy leads to a loss of confidence or precision afforded beliefs about the consequences of social behavior. This results in an over reliance on sensory evidence and social feedback, with concomitant lability, impulsivity and hypersensitivity. In terms of PP, people with BPD show a distorted belief updating in response to new information with two opposing manifestations: rapid changes in beliefs and a lack of belief updating despite disconfirmatory evidence. This account of distorted information processing has the potential to explain both the instability (of affect, self-image, and interpersonal relationships) and the rigidity (of beliefs about self and others) which is typical of BPD. At the neurobiological level, we propose that enhanced levels of dopamine are associated with the increased integration of negative social feedback, and we also discuss the hypothesis of an impaired inhibitory control of the prefrontal cortex in the processing of negative social information. Our account may provide a new understanding not only of the clinical aspects of BPD, but also a unifying theory of the corresponding neurobiological pathologies. We conclude by outlining some directions for future research on the behavioral, neurobiological, and computational underpinnings of this model, and point to some clinical implications of it.

Adolescents with borderline personality disorder show a higher response to stress but a lack of self-perception: Evidence through affective computing

Stress reactivity is a complex phenomenon associated with multiple and multimodal expressions and functions. Herein, we hypothesized that compared with healthy controls (HCs), adolescents with borderline personality disorder (BPD) would exhibit a stronger response to stressors and a deficit in self-perception of stress due to their lack of insight. Twenty adolescents with BPD and 20 matched HCs performed a socially evaluated mental arithmetic test to induce stress. We assessed self- and heteroperception using both human ratings and affective computing-based methods for the automatic extraction of 39 behavioral features (2D + 3D video recording) and 62 physiological features (Nexus-10 recording). Predictions were made using machine learning. In addition, salivary cortisol was measured. Human ratings showed that adolescents with BPD experienced more stress than HCs. Human ratings and automated machine learning indicated opposite results regarding self- and heteroperceived stress in adolescents with BPD compared to HCs. Adolescents with BPD had higher levels of heteroperceived stress than self-perceived stress. Similarly, affective computing achieved better classification for heteroperceived stress. HCs had an opposite profile; they had higher levels of self-perceived stress, and affective computing reached a better classification for self-perceived stress. We conclude that adolescents with BPD are more sensitive to stress and show a lack of self-perception (or insight). In terms of clinical implications, our affective computing measures may help distinguish hetero- vs. self-perceptions of stress in natural settings and may offer external feedback during therapeutic interaction.

Improving Research Practice for Studying Borderline Personality Disorder: Lessons From the Clinic

Borderline personality disorder is an often misunderstood and underdiagnosed mental illness characterized in part by affective lability. Clinicians’ unique understanding of the disorder has allowed them to develop disorder-specific approaches to treatment. In this review, we highlight how borderline personality disorder research can benefit from greater engagement with key disorder-specific features, including symptom variability and interpersonal sensitivity. In addition, we propose that research which employs interactive tasks will be more reflective of the kinds of volatility found in the real-life situations. Finally, we discuss how mixed-methodology can serve as a way for recovery-oriented research to practice the very ideals and recommendations it suggests. We use a patient case to contextualize each section. As interest in borderline personality disorder continues to grow, an intentional emphasis on a person-centered, recovery-focused, and disorder-specific approach to research is needed.

[Artificial intelligence and nursing care: reflections in psychiatry]

A key government priority, artificial intelligence (IA) in healthcare is a real opportunity for nursing professionals. Faced with the daily difficulties encountered, AI could bring a new perspective to nursing care in psychiatry and free up time for professionals which they can then spend with the patient. More training and a multi-disciplinary approach are required.

Differential Valuation and Learning From Social and Nonsocial Cues in Borderline Personality Disorder

BACKGROUND

Volatile interpersonal relationships are a core feature of borderline personality disorder (BPD) and lead to devastating disruption of patients' personal and professional lives. Quantitative models of social decision making and learning hold promise for defining the underlying mechanisms of this problem. In this study, we tested BPD and control subject weighting of social versus nonsocial information and their learning about choices under stable and volatile conditions. We compared behavior using quantitative models.

METHODS

Subjects (n = 20 BPD, n = 23 control subjects) played an extended reward learning task with a partner (confederate) that requires learning about nonsocial and social cue reward probability (the social valuation task). Task experience was measured using language metrics: explicit emotions/beliefs, talk about the confederate, and implicit distress (using the previously established marker self-referentiality). Subjects' weighting of social and nonsocial cues was tested in mixed-effect regression models. Subjects' learning rates under stable and volatile conditions were modeled (Rescorla-Wagner approach) and group × condition interactions tested.

RESULTS

Compared to control subjects, BPD subject debriefings included more mentions of the confederate and less distress language. BPD subjects also weighted social cues more heavily but had blunted learning responses to (nonsocial and social) volatility.

CONCLUSIONS

This is the first report of patient behavior in the social valuation task. The results suggest that BPD subjects expect higher volatility than control subjects. These findings lay the groundwork for a neurocomputational dissection of social and nonsocial belief updating in BPD, which holds promise for the development of novel clinical interventions that more directly target pathophysiology.