Interoceptive inference, emotion, and the embodied self.

Area of Science:

• Cognitive Neuroscience
• Affective Science
• Computational Psychiatry

Background:

• The brain is increasingly viewed as a prediction machine, particularly in exteroceptive perception and action.
• Existing predictive coding models have largely overlooked the domain of interoception (sensing internal body states).

Purpose of the Study:

• To propose a novel framework for understanding interoception through the lens of predictive processing.
• To introduce the concept of 'interoceptive inference' as a generative model for subjective feeling states.

Main Methods:

• Conceptual modeling integrating predictive coding principles with interoception.
• Generalizing existing appraisal theories of emotion within a predictive inference framework.

Main Results:

• Subjective emotional states arise from actively inferred generative models of interoceptive afferent signals.
• This model provides a unified account for emotions, body ownership, and conscious selfhood.

Conclusions:

• Interoceptive inference offers a powerful new perspective on the neurocognitive basis of emotions and self-consciousness.
• The framework has implications for understanding neuropsychiatric conditions characterized by altered self-awareness and emotional experience.