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The contemplative exercise through the lenses of predictive processing: A promising approach.

G. Pagnoni

Progress in Brain Research January 1, 2019 Peer reviewed DOI: 10.1016/bs.pbr.2018.10.022 via Semantic Scholar

Summary

Predictive processing theory, which explains perception, action, attention, and learning as free-energy minimization, can provide a unifying framework for contemplative research. Meditation research has grown rapidly but lacks theoretical organization. The article applies predictive processing to Zen shikantaza meditation as an example and suggests experimental paradigms to test hypotheses from this approach.

Study at a glance

Design theoretical or philosophical paper
Key finding Predictive processing theory offers a unitary framework for understanding meditation-related processes.

Abstract

The theory of predictive processing in the comprehensive articulation proposed by Karl Friston is a framework that boasts an impressively wide explanatory power in neurobiology, where processes apparently as diverse as perception, action, attention, and learning unfold, and are coherently orchestrated, according to the single general mandate of free-energy minimization. In the present opinion piece, I argue that the adoption of this theoretical perspective can provide a much needed unitary framework for contemplative research as well, whose explosive growth in terms of the number of published studies and amount of collected data has not been matched yet by a similarly extensive effort to theoretically organize the findings, so that a deeper understanding of meditation-related processes can be attained. After an introduction to the basic notions of predictive processing, a tentative application of the latter to the meditative exercise is discussed, taking as a paradigmatic example the Japanese Zen meditation practice of shikantaza. Finally, I provide a short list of experimental paradigms that seem particularly useful to test the hypotheses born out of the predictive processing approach to contemplative research.

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