A Computational Theory of Mindfulness Based Cognitive Therapy from the “Bayesian Brain” Perspective
Zina-Mary Manjaly, Sandra Iglesias preprint
Mindfulness Based Cognitive Therapy (MBCT) combines cognitive behavioral therapy with meditation to prevent relapse in recurrent depression, but its cognitive mechanisms are poorly understood computationally or biologically. This article proposes a testable theory grounded in Bayesian brain concepts from cognitive neuroscience, such as predictive coding, where the brain models its environment and updates predictions based on error signals. Core MBCT concepts—being mode, decentring, and reactivity—are reinterpreted as perceptual and metacognitive processes relying on specific computational mechanisms. The theory can be tested experimentally with behavioral paradigms, computational modeling, and neuroimaging, potentially refining both conceptual and practical aspects of MBCT.