Distressing physical symptoms that persist for months are frequent, occur across all areas of medicine and strongly impact quality of life. The association with measurable and reproducible pathophysiological processes is often loose or even absent and for most persistent physical symptoms (PPS), positive diagnostic markers are lacking, which challenges diagnosis and treatment. This thesis aims to contribute towards a better mechanistic understanding of PPS that can inform treatment and diagnosis by investigating symptom perception and sensorimotor processing in two examples of PPS, i.e., functional dizziness and post COVID-19 condition. We adopt a Bayesian brain perspective that proposes that the brain infers the most likely causes of sensory inputs by inverting an internal model that constitutes a probabilistic mapping between different states and sensory input as well as prior knowledge about these states. Recent theories have proposed that erroneous internal models can lead to the emergence of symptoms and dysfunctional motor processing, also in the absence of pathophysiological processes. Here, we provide further evidence in support of this hypothesis for functional dizziness and post COVID-19 condition. Using two different experimental paradigms, we were able to show that sensorimotor deficits (in functional dizziness) and increased breathlessness perception (in post COVID-19 condition) do not reflect altered and potentially pathological body states but rather are due to involvement of incorrect internal models. We highlight that different mechanisms could underlie these results and discuss the role of incorrect but highly precise priors in functional dizziness and maladaptive cost-functions in patients with post COVID-19 condition. In addition, we bridge the gap between experimental data and theories by developing a mathematical model that proposes a potential mechanism of how processing of respiratory data can lead to the emergence of breathlessness perception. In summary, this thesis provides an explanatory framework, a measurable marker of incorrect internal model use and an improved mechanistic understanding for functional dizziness and post COVID-19 condition. These findings can contribute towards development and refinement of existing treatments and reduce stigmatization of PPS.