AI Article Synopsis

  • Recent research in Bayesian theories indicates that how we perceive bodily states depends on a combination of incoming signals and our prior beliefs about those signals.
  • A study involving heartbeat tapping showed that healthy individuals adapt their perception of cardiac signals during breath-holding, while those with anxiety or related disorders do not adjust their perception, indicating a problem with how they weight these signals.
  • Expanding a previous study with a larger sample size confirmed these findings and suggests that future research could look into how understanding interoceptive precision might help improve treatment outcomes and identify new therapeutic targets.

Article Abstract

Recent Bayesian theories of interoception suggest that perception of bodily states rests upon a precision-weighted integration of afferent signals and prior beliefs. In a previous study, we fit a computational model of perception to behavior on a heartbeat tapping task to test whether aberrant precision-weighting could explain misestimation of cardiac states in psychopathology. We found that, during an interoceptive perturbation designed to amplify afferent signal precision (inspiratory breath-holding), healthy individuals increased the precision-weighting assigned to ascending cardiac signals (relative to resting conditions), while individuals with anxiety, depression, substance use disorders, and/or eating disorders did not. In this pre-registered study, we aimed to replicate and extend our prior findings in a new transdiagnostic patient sample (N = 285) similar to the one in the original study. As expected, patients in this new sample were also unable to adjust beliefs about the precision of cardiac signals - preventing the ability to accurately perceive changes in their cardiac state. Follow-up analyses combining samples from the previous and current study (N = 719) also afforded power to identify group differences between narrower diagnostic categories, and to examine predictive accuracy when logistic regression models were trained on one sample and tested on the other. With this confirmatory evidence in place, future studies should examine the utility of interoceptive precision measures in predicting treatment outcomes and test whether these computational mechanisms might represent novel therapeutic targets.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11416323PMC
http://dx.doi.org/10.1016/j.biopsycho.2024.108825DOI Listing

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