Potential self-regulatory mechanisms of yoga for psychological health.

A theoretical framework and systems-based network model proposes that yoga integrates top-down and bottom-up forms of self-regulation to improve psychological health. The model emphasizes how specific components of yoga practice affect cognitive, emotional, behavioral, and autonomic output under stress through interoception and bottom-up input, resulting in bidirectional feedback between high- and low-level brain networks and afferent input from interoceptive processes. From a predictive coding perspective, yoga shifts perceptual inference for stress modulation and optimal self-regulation. Over time and practice, self-regulatory processes become more automatized and efficient, requiring less effort to initiate and terminating more rapidly when no longer needed. The paper synthesizes evidence from behavior theory and cognitive neuroscience with emerging yoga and meditation research to guide future research on stress-mediated psychological disorders.

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Abstract

Research suggesting the beneficial effects of yoga on myriad aspects of psychological health has proliferated in recent years, yet there is currently no overarching framework by which to understand yoga's potential beneficial effects. Here we provide a theoretical framework and systems-based network model of yoga that focuses on integration of top-down and bottom-up forms of self-regulation. We begin by contextualizing yoga in historical and contemporary settings, and then detail how specific components of yoga practice may affect cognitive, emotional, behavioral, and autonomic output under stress through an emphasis on interoception and bottom-up input, resulting in physical and psychological health. The model describes yoga practice as a comprehensive skillset of synergistic process tools that facilitate bidirectional feedback and integration between high- and low-level brain networks, and afferent and re-afferent input from interoceptive processes (somatosensory, viscerosensory, chemosensory). From a predictive coding perspective we propose a shift to perceptual inference for stress modulation and optimal self-regulation. We describe how the processes that sub-serve self-regulation become more automatized and efficient over time and practice, requiring less effort to initiate when necessary and terminate more rapidly when no longer needed. To support our proposed model, we present the available evidence for yoga affecting self-regulatory pathways, integrating existing constructs from behavior theory and cognitive neuroscience with emerging yoga and meditation research. This paper is intended to guide future basic and clinical research, specifically targeting areas of development in the treatment of stress-mediated psychological disorders.