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    <title language="eng">Increased breathlessness in post-COVID syndrome despite normal breathing patterns in a rebreathing challenge</title>
    <abstract language="eng">Severe symptoms in the absence of measurable body pathology are a frequent hallmark of post-COVID syndrome. From a Bayesian Brain perspective, such symptoms can be explained by incorrect internal models that the brain uses to interpret sensory signals. In this pre-registered study, we investigate whether induced breathlessness perception during a controlled CO2rebreathing challenge is reflected by altered respiratory measures (physiology and breathing patterns), and propose different computational mechanisms that could explain our findings in a Bayesian Brain framework. We analysed data from 40 patients with post-COVID syndrome and 40 healthy participants. Results from lung function, neurological and neurocognitive examination of all participants were within normal limits on the day of the experiment. Using a Bayesian repeated-measures ANOVA, we found that patients’ breathlessness was strongly increased (BF10,baseline&#13;
 =8.029, BF10,rebreathing&#13;
 =11636, BF10,recovery&#13;
 =43662) compared to controls. When excluding patients who hyperventilated (N = 8, 20%) during the experiment from the analysis, differences in breathlessness remained (BF10,baseline&#13;
 =1.283, BF10,rebreathing&#13;
 =126.812, BF10,recovery&#13;
 =751.282). For physiology and breathing patterns, all evidence pointed towards no difference between the two groups (0.307  BF10 &amp;lt; 0.704). In summary, we found intact breathing patterns and physiology but increased symptom perception in patients with post-COVID syndrome.</abstract>
    <parentTitle language="eng">Scientific reports</parentTitle>
    <identifier type="doi">10.1038/s41598-025-11728-x</identifier>
    <identifier type="issn">2045-2322</identifier>
    <enrichment key="Fprofil">2 Gesundheit und Lifes Sciences / Health and Life Sciences</enrichment>
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From a Bayesian Brain perspective, such symptoms can be explained by incorrect internal models that the brain uses to interpret sensory signals. In this pre-registered study, we investigate whether induced breathlessness perception during a controlled CO&lt;jats:sub&gt;2&lt;\/jats:sub&gt;rebreathing challenge is reflected by altered respiratory measures (physiology and breathing patterns), and propose different computational mechanisms that could explain our findings in a Bayesian Brain framework. We analysed data from 40 patients with post-COVID syndrome and 40 healthy participants. Results from lung function, neurological and neurocognitive examination of all participants were within normal limits on the day of the experiment. Using a Bayesian repeated-measures ANOVA, we found that patients\u2019 breathlessness was strongly increased (BF&lt;jats:sub&gt;10,&lt;jats:italic&gt;baseline&lt;\/jats:italic&gt;\n            &lt;\/jats:sub&gt;=8.029, BF&lt;jats:sub&gt;10,&lt;jats:italic&gt;rebreathing&lt;\/jats:italic&gt;\n            &lt;\/jats:sub&gt;=11636, BF&lt;jats:sub&gt;10,&lt;jats:italic&gt;recovery&lt;\/jats:italic&gt;\n            &lt;\/jats:sub&gt;=43662) compared to controls. When excluding patients who hyperventilated (&lt;jats:italic&gt;N&lt;\/jats:italic&gt;\u2009=\u20098, 20%) during the experiment from the analysis, differences in breathlessness remained (BF&lt;jats:sub&gt;10,&lt;jats:italic&gt;baseline&lt;\/jats:italic&gt;\n            &lt;\/jats:sub&gt;=1.283, BF&lt;jats:sub&gt;10,&lt;jats:italic&gt;rebreathing&lt;\/jats:italic&gt;\n            &lt;\/jats:sub&gt;=126.812, BF&lt;jats:sub&gt;10,&lt;jats:italic&gt;recovery&lt;\/jats:italic&gt;\n            &lt;\/jats:sub&gt;=751.282). 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