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Towards an Active Inference Account of Deep Meditative Deconstruction

Shawn Prest, Kevin Berryman

January 26, 2024 preprint DOI: 10.31234/osf.io/d3gpf via OpenAlex

Summary

The paper examines how deep meditative deconstruction in Buddhism relates to computational mechanisms within the active inference framework. It suggests that Buddhist defabrication can be seen as a process that reduces belief precision, which aligns with concepts like equanimity and meditative stillness. The authors illustrate how this deconstruction leads to a cessation of phenomenal experience and discuss its implications for understanding core-knowledge structuring and experience generation.

Study at a glance

Key finding Buddhist defabrication is characterized as a deconstructive process that reduces belief precision, allowing for interpretations of equanimity and meditative stillness within the active inference framework.

Abstract

This paper explores the intersection of deep meditative deconstruction, in particular the Buddhist defabrication process and its associated phenomenology, and computational mechanisms under the active inference framework (AIF). We contextualise states such as the jhānas within this process, drawing on both Buddhist theoretical frameworks and contemporary phenomenological understanding. We take a step towards ‘translating’ Buddhist meditation-based phenomenology into computational neurophenomenology. We demonstrate how Buddhist defabrication can be understood as a deconstructive process driving inference ever lower in an agent’s hierarchical generative model by the repeated release of mental tensing associated with clinging and aversion. We cast this release of mental tensing as corresponding to a hierarchical level-specific reduction in belief precision, permitting the interpretation of Buddhist notions such as equanimity and meditative stillness under AIF. We then illustrate the deconstruction process up to its conclusion in a cessation of phenomenal experience, touching on how states traversed during the process may inform areas related to core-knowledge structuring and the generation of experience.

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