Insomnia disorder is very common, with an estimated prevalence ranging from 5.7% to 19%. This disorder is currently interpreted and treated in light of complex interactions of biological, psychological and social factors. Recently, the application of a predictive-inferential model based on the Bayesian theory of probability to the neurosciences has allowed several mental disorders to be reinterpreted from a new perspective. According to the Bayesian interpretation the brain can be considered a ‘probabilistic machine’ making inferences about what might happen in the future based on previous experiences, and continuously veryfying and refining the hypothesis based on its sensory perceptions.
In this article we will illustrate how the Bayesian model can account for both the current explanatory models of insomnia and some cognitive-behavioral therapetic interventions within a single conceptual framework. Finally, in the article we provide possible insights into using the Bayesian model in treating insomnia disorder.
Key words: sleep, insomnia, bayesian model, indcutive-predictive model, predictive brain
DOI: 10.36131/COGNCL20230102