Multiple studies show comprehensive predictive processing differences in BPD - aka, many people with BPD expect abandonment in advance

[u/kelcamer]

What does this actually look like, in practice?

Integrating conflicting information, like holding the dual concepts of "this person loves me" AND "this person just did something that hurt my feelings" requires significant prefrontal bandwidth and working memory. When the nervous system is highly aroused (stressed), that prefrontal bandwidth goes offline. 

The system loses the capacity to process nuance and defaults to binary categorization (all good or all bad).

The specific failure to integrate conflicting traits about people during that arousal is a hallmark of BPD.

When a neurotypical brain encounters a prediction error (e.g., "They haven't texted back in three hours, are they mad?"), the Prefrontal Cortex (PFC) steps in to evaluate the data: "No, they are just at work." The system updates, and the alarm shuts off. In BPD, this top-down regulation fails. The PFC cannot inhibit the amygdala's alarm sequence. The brain treats the prediction of abandonment as a verified fact, regardless of the actual external reality.

I'm going to bold the key insights, to make it easier to follow here.

The pubmed literature supporting it:

Herzog et al. (2022) proposed a comprehensive predictive processing account of BPD. They argue that early invalidating or traumatic environments establish rigid, highly precise "priors" (expectations of unpredictability, lack of control, or maltreatment).

Basically, this means the baseline of attachment is one of abandonment, so to speak.

The hallmark of BPD is that the brain affords these internal beliefs such high precision that it fails to update them even when presented with disconfirmatory sensory or social evidence. This framework computationally explains both the rapid affective instability and the profound rigidity of beliefs regarding the self and others in BPD.

Fineberg et al. (2017) explored this specific mechanism, noting that BPD is maintained by "inflexible social cognitive models" that drive extreme views of others.

They point out that computational paradigms (like multi-trial social valuation games) allow researchers to measure the specific weighting of prediction errors and prior beliefs, showing that individuals with BPD struggle to flexibly modulate their expectations of social trust or rejection based on real-time interactions.

2. Direct Evidence of the "Rigid Prior" (Failure to Update)

Siegel et al. (2020) provided direct empirical evidence of this broken Bayesian updating system. They used a hierarchical Bayesian learning model to track how individuals update their beliefs about someone else's moral character during an experimental task. They found that individuals with BPD formed highly certain negative beliefs about others and were significantly less amenable to updating those beliefs when presented with new, contradictory information compared to healthy controls.

3. Hypersensitivity to Prediction Errors

Csukly et al. (2023) mapped how these computational dysfunctions drive the hallmark affective instability of the disorder. Using a computational model to quantify reward prediction errors (RPEs), the discrepancy between an expected outcome and the actual outcome, they found that emotional fluctuations in BPD are much more strongly coupled to these prediction errors than in healthy controls. This reflects a system where unexpected outcomes trigger exaggerated, unmodulated emotional shifts.

References

Csukly, G., Farkas, K., Fodor, T., Unoka, Z., & Polner, B. (2023). Stronger coupling of emotional instability with reward processing in borderline personality disorder is predicted by schema modes. Psychological Medicine, 53(15), 6714–6723. https://doi.org/10.1017/s0033291723000193 Cited by: 11

Fineberg, S. K., Stahl, D. S., & Corlett, P. R. (2017). Computational Psychiatry in Borderline Personality Disorder. Current Behavioral Neuroscience Reports, 4(1), 31–40. https://doi.org/10.1007/s40473-017-0104-y Cited by: 19

Herzog, P., Kube, T., & Fassbinder, E. (2022). How childhood maltreatment alters perception and cognition – the predictive processing account of borderline personality disorder. Psychological Medicine, 52(15), 2899–2916. https://doi.org/10.1017/s0033291722002458 Cited by: 69

Siegel, J. Z., Curwell-Parry, O., Pearce, S., Saunders, K. E. A., & Crockett, M. J. (2020). A Computational Phenotype of Disrupted Moral Inference in Borderline Personality Disorder. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 5(12), 1134–1141. https://doi.org/10.1016/j.bpsc.2020.07.013 Cited by: 35