Background: Bodily symptoms are highly prevalent in psychopathology, and in some specific disorders, such as somatic symptom disorder, they are a central feature. In general, the mechanisms underlying these symptoms are poorly understood. However, also in well-known physical diseases there seems to be a variable relationship between physiological dysfunction and self-reported symptoms challenging traditional assumptions of a biomedical disease model.
Method: Recently, a new, predictive processing conceptualization of how the brain works has been used to understand this variable relationship. According to this predictive processing view, the experience of a symptom results from an integration of both interoceptive sensations as well as from predictions about these sensations from the brain.
Results: In the present paper, we introduce the predictive processing perspective on perception (predictive coding) and action (active inference), and apply it to asthma in order to understand when and why asthma symptoms are sometimes strongly, moderately or weakly related to physiological disease parameters.
Conclusion: Our predictive processing view of symptom perception contributes to understanding under which conditions misperceptions and maladaptive action selection may arise.
Most read articles by the same author(s)
- Omer Van den Bergh, Nadine Lehnen, Embracing Computational Approaches Can Stimulate Clinical Psychology Research , Clinical Psychology in Europe: Vol. 1 No. 3 (2019)