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Malcolm Wright

3 papers in the library · 114 citations · publishing 2023-2026

Papers

A Framework for the Empirical Investigation of Mindfulness Meditative Development

Mindfulness April 13, 2023 Julieta Galante, Andrea Grabovac, Malcolm Wright et al. 82 citations

About half of the millions of people who learn mindfulness meditation continue regular practice after initial instruction, but it is unclear whether benefits increase with ongoing practice or whether harm can occur. Evidence shows a wide range of experiences from positive to challenging and potentially harmful. Complex interactions and temporal sequences may explain these experiences and their links to health and well-being. Effects may vary systematically due to factors like initial dosage, accumulated practice, developing skill, and interactions with past experiences and environment. The authors call for interdisciplinary, ontologically agnostic research using longitudinal models and insights from contemplative traditions to develop safer, more effective applications.

Volitional mental absorption in meditation: Toward a scientific understanding of advanced concentrative absorption meditation and the case of jhana.

Heliyon May 14, 2024 Winson F.z. Yang, Terje Sparby, Malcolm Wright et al. 30 citations

Advanced concentrative absorption meditation, such as the jhanas, involves volitional mental absorption that can be scientifically studied. This paper argues that these states represent a distinct category of meditative experience characterized by deep, effortless focus and profound well-being. It proposes a scientific framework for understanding these measurable states of consciousness, drawing on existing research to outline how absorption, concentration, and positive outcomes like well-being can be systematically investigated. The authors suggest that developing a rigorous scientific approach to jhana and similar practices could bridge contemplative traditions and consciousness research, offering new insights into the nature of deep meditative states and their potential benefits.

Active inference, computational phenomenology, and advanced meditation: Toward the formalization of the experience of meditation.

Neuroscience and biobehavioral reviews March 1, 2026 Hagar Tal, Malcolm Wright, Shawn Prest et al. 2 citations

Computational models of advanced meditation, particularly those using Active Inference, increasingly point to precision weighting—the confidence assigned to different model parameters—as a shared mechanism that shapes shifts in experience. Early models emphasize top-down attentional modulation toward interoception or specific objects, while later models focus on layer-specific precision re-weighting within the meditator's hierarchical generative model to target more specific phenomenology. Despite progress, minimal phenomenal experiences such as nonduality and cessations remain largely unaddressed. Few models account for increased cognitive flexibility or learning from meditation, and mechanisms behind informal practice, affective processes, and compassion traditions are underexplored.