Commentary: A Computational Theory of Mindfulness Based Cognitive Therapy from the “Bayesian Brain” Perspective
Study at a glance
AI-extracted from the abstract| Characteristics | Commentary |
|---|---|
| Topics | Meditation |
| Key points | Argues that the proposed mechanisms in Manjaly and Iglesias's model conflict and proposes an alternative mechanism of dynamic updating of prior beliefs. |
Abstract
Manjaly and Iglesias (2020) introduce a neurocomputational model of mechanisms through which Mindfulness Based Cognitive Therapy may work, based on a Bayesian perspective. They claim that mindfulness increases the precision of likelihood, but decreases the precision of prior. In this commentary, we argue that these two mechanisms conflict when describing mindful functioning. We suggest an alternative mechanism – namely the dynamic updating of prior beliefs as a function of context, which contributes to active inference. The moment-to-moment attentional pattern of mindfulness could promote the optimal adjustment of prior beliefs to the context of each present experience.
Citations in the library
Cites 3
- Investigating the phenomenological matrix of mindfulness-related practices from a neurocognitive perspective. American Psychologist October 1, 2015
- Thought insertion as a self-disturbance: An integration of predictive coding and phenomenological approaches Frontiers in Human Neuroscience December 22, 2016
- Experimental and theoretical approaches to conscious processing. Neuron April 28, 2011