Reconceptualizing complex posttraumatic stress disorder: A predictive processing framework for mechanisms and...

Area of Science:

• Neuroscience
• Computational Psychiatry
• Psychology

Background:

• Complex Posttraumatic Stress Disorder (C-PTSD) involves disturbances in self-organization beyond PTSD symptoms.
• These disturbances include negative self-concept, affect dysregulation, and relational difficulties, often from prolonged trauma.

Purpose of the Study:

• To introduce a predictive processing framework for interpreting C-PTSD.
• To provide a mechanistic explanation for C-PTSD symptoms, particularly disturbances in self-organization (DSO).

Main Methods:

• Leveraging advances in computational psychiatry and neuroscience.
• Applying predictive processing models to understand brain function in C-PTSD.
• Focusing on how altered predictive mechanisms contribute to DSO.

Main Results:

• Negative self-concept arises from maladaptive priors biasing self-perception and interoceptive misalignment.
• Affect dysregulation results from a mismatch between predicted and actual interoceptive signals.
• Relationship difficulties stem from skewed social prediction errors, leading to mistrust.

Conclusions:

• The predictive processing framework offers a mechanistic understanding of C-PTSD.
• Altered predictive mechanisms are central to C-PTSD symptomatology, especially DSO.
• This approach identifies potential targets for interventions aimed at recalibrating predictive processing.