Reframing PTSD for computational psychiatry with the active inference framework.

Area of Science:

• Neurobiology
• Cognitive Neuroscience
• Computational Psychiatry

Background:

• Stress and disorders of perception, learning, and behavior are increasingly understood through neurobiological and computational approaches.
• Post-traumatic stress disorder (PTSD) and conditions like schizophrenia and autism share overlapping pathophysiological mechanisms.
• Active inference provides a framework for understanding cognitive function and dysfunction in embodied and embedded systems.

Purpose of the Study:

• To synthesize current insights from neurobiology, cognitive neuroscience, psychology of stress, and computational psychiatry.
• To apply the active inference framework to understand the pathophysiology of PTSD.
• To develop a novel perspective on PTSD integrating biological, cognitive, behavioral, and environmental factors.

Main Methods:

• Applying the active inference framework to PTSD.
• Viewing auditory phenomena and traditional models of auditory function from an evolutionary perspective based on active inference.
• Assessing and contextualizing evidence on audition, stress, psychosis, and PTSD.

Main Results:

• The active inference framework offers an explanatory model for how mental functioning can be impaired in psychopathological conditions.
• Auditory phenomena, relevant to PTSD and schizophrenia, are analyzed through the lens of active inference.
• Existing partial models of PTSD are brought into multilevel alignment.

Conclusions:

• A novel, integrated perspective on PTSD is presented.
• This perspective can inform new experimental designs for PTSD research.
• The findings aim to guide the development of therapeutic interventions for PTSD.