Gut inference: A computational modelling approach

•Healthy individuals completed a gastrointestinal interoceptive awareness task.•Neural responses were measured using electroencephalography.•A Bayesian model estimated interoceptive precision, prior beliefs, and learning rates.•Neural responses in parieto-occipital leads correlated with sensory prec...

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Bibliographic Details
Published in:Biological psychology 2021-09, Vol.164, p.108152-108152, Article 108152
Main Authors: Smith, Ryan, Mayeli, Ahmad, Taylor, Samuel, Al Zoubi, Obada, Naegele, Jessyca, Khalsa, Sahib S.
Format: Article
Language:English
Subjects:
Active inference
Bayes Theorem
Bayesian perception
Computational modeling
Electroencephalography
Evoked Potentials
Gastrointestinal system
Heart Rate
Humans
Interoception
Learning rate
Precision
Priors
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Summary:•Healthy individuals completed a gastrointestinal interoceptive awareness task.•Neural responses were measured using electroencephalography.•A Bayesian model estimated interoceptive precision, prior beliefs, and learning rates.•Neural responses in parieto-occipital leads correlated with sensory precision.•Neural responses in frontal leads correlated with prior beliefs and learning rates. Neurocomputational theories have hypothesized that Bayesian inference underlies interoception, which has become a topic of recent experimental work in heartbeat perception. To extend this approach beyond cardiac interoception, we describe the application of a Bayesian computational model to a recently developed gastrointestinal interoception task completed by 40 healthy individuals undergoing simultaneous electroencephalogram (EEG) and peripheral physiological recording. We first present results that support the validity of this modelling approach. Second, we provide a test of, and confirmatory evidence supporting, the neural process theory associated with a particular Bayesian framework (active inference) that predicts specific relationships between computational parameters and event-related potentials in EEG. We also offer some exploratory evidence suggesting that computational parameters may influence the regulation of peripheral physiological states. We conclude that this computational approach offers promise as a tool for studying individual differences in gastrointestinal interoception.
ISSN:0301-0511
1873-6246
DOI:10.1016/j.biopsycho.2021.108152