A Computational Theory of Mindfulness Based Cognitive Therapy from the “Bayesian Brain” Perspective

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This paper proposes a computational theory of Mindfulness Based Cognitive Therapy (MBCT) grounded in Bayesian brain concepts, specifically predictive coding. It aims to explain the cognitive mechanisms behind MBCT's effectiveness in preventing depressive relapse by framing core practices like decentering and acceptance as perceptual and metacognitive processes. The resource is intended for researchers or clinicians interested in the theoretical underpinnings of MBCT and suggests experimental methods to test these hypotheses.

ID
2ce2c1be54274c65
Source org
OpenAlex
Author
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Published
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OA status
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DOI
10.3389/fpsyt.2020.00404
PMID
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BibTeX

@article{allodium:2ce2c1be54274c65,
  title = {A Computational Theory of Mindfulness Based Cognitive Therapy from the “Bayesian Brain” Perspective},
  journal = {OpenAlex},
  doi = {10.3389/fpsyt.2020.00404},
  url = {https://doi.org/10.3389/fpsyt.2020.00404}
}

RIS

TY  - JOUR
TI  - A Computational Theory of Mindfulness Based Cognitive Therapy from the “Bayesian Brain” Perspective
PB  - OpenAlex
DO  - 10.3389/fpsyt.2020.00404
UR  - https://doi.org/10.3389/fpsyt.2020.00404
ER  -

APA

A Computational Theory of Mindfulness Based Cognitive Therapy from the “Bayesian Brain” Perspective. (n.d.). OpenAlex. https://doi.org/10.3389/fpsyt.2020.00404

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