PLoS ONE
September 2, 2008
Giuseppe Pagnoni, Milos Cekic, Ying Guo
189 citations
Zen meditation practitioners show a reduced duration of neural response in default-network brain regions during conceptual processing, suggesting that meditative training may help regulate the automatic cascade of semantic associations and spontaneous thought. Using fMRI and a lexical decision task, regular Zen practitioners and matched controls performed similarly behaviorally, but practitioners' brain activity linked to conceptual processing was briefer.
Review of philosophy and psychology
January 1, 2022
Maxwell J D Ramstead, Anil K Seth, Casper Hesp et al.
75 citations
A version of neurophenomenology is presented that uses generative modelling techniques from computational neuroscience and biology to formally model descriptions of lived experience from the phenomenological tradition (e.g., Husserl, Merleau-Ponty). The approach, called computational phenomenology, is situated within the broader project of naturalizing phenomenology. Philosophical objections to that project are evaluated, and the generative modelling framework is reviewed. The approach differs from previous uses of generative modelling for consciousness by constructing computational models of inferential or interpretive processes that best explain particular kinds of lived experience.
Frontiers in human neuroscience
January 1, 2013
Omar T Khachouf, Stefano Poletti, Giuseppe Pagnoni
34 citations
Neurophenomenology aims to bridge subjective experience and brain data by treating the body as central to consciousness. This paper argues that the Kantian concept of a priori structures, which make experience possible, can be grounded in biology through an extended theory of autopoiesis. Examples from simple models, bacteria, the immune system, mirror neurons, and the default mode network illustrate how knowledge is enacted. The free-energy principle is presented as a neural framework that fits these ideas. The authors maintain that first-person experience remains essential for understanding brain function because it shares the same transcendental structure, and they discuss how meditation can contribute to this research.
PsyArXiv
February 23, 2021
Maxwell James Ramstead, Anil Seth, Casper Hesp et al.
21 citations
preprint
A new approach called computational phenomenology uses generative modeling techniques from computational neuroscience to study conscious experience. The paper reviews efforts to naturalize phenomenology, addresses philosophical objections, and explains how generative models can simulate the inferential processes underlying specific types of lived experience. This differs from prior uses of generative modeling for consciousness by focusing on modeling the interpretive process that best accounts for particular phenomenal experiences.
August 2, 2022
Arnaud Poublan-Couzardot, Giuseppe Pagnoni, Antoine Lutz
10 citations
preprint
Pain perception is shaped by expectations and individual differences in how people think and feel about pain. Using predictive processing theory, which views the brain as a Bayesian inference machine, researchers analyzed pain intensity and unpleasantness ratings from 54 healthy meditation practitioners. They modeled how the brain integrates sensory information, expectations, and a stable personal prior about pain. The model extended previous work by separately accounting for sensory and affective pain components. Pain catastrophizing and cognitive defusion correlated oppositely with model parameters representing their computational counterparts. Lifetime meditation practice was strongly and inversely linked to the weight of short-term expectations and to a trait-like prior affecting the emotional dimension of pain.
January 24, 2019
Antoine Lutz, Jérémie Mattout, Giuseppe Pagnoni
7 citations
A predictive processing framework, grounded in active inference and free-energy minimization, can explain how focused attention meditation works. Paying voluntary attention to the body during meditation downweights habitual automatic reactions and distracting spontaneous thoughts, thereby settling the mind. The framework also links phenomenological concepts like opacity and de-reification to the voluntary allocation of attention and precision-weighting. The authors propose this theoretical approach as a promising strategy for contemplative research, though explicit computational simulations and comparisons with experimental data are still needed.
Biological psychiatry. Cognitive neuroscience and neuroimaging
April 1, 2025
Saampras Ganesan, Fernando A Barrios, Ishaan Batta et al.
6 citations
Meditation practices, which have shown therapeutic benefits for conditions like depression, pain, addiction, and anxiety, have been studied with neuroimaging over the past decade. However, existing neuroscientific models are based on small, heterogeneous datasets, limiting generalizability and replicability. The ENIGMA-Meditation consortium is the first worldwide collaborative effort to conduct systematic meta- and mega-analyses of globally distributed neuroimaging data using standardized methods. This framework aims to improve statistical power and address multidomain heterogeneity in meditation practice types, experience, and experimental design. The consortium will generate rigorous neuroscientific insights into the mechanisms underlying meditation's therapeutic effects on psychological and cognitive attributes.
Biological psychiatry global open science
July 1, 2025
Oussama Abdoun, Arnaud Poublan-Couzardot, Stéphane Offort et al.
5 citations
Most meditation research uses trait questionnaires that miss moment-to-moment changes during practice. The Lyon Assessment of Meditation Phenomenology (LAMP) questionnaire was developed to capture contextual, emotional, bodily, attentional, cognitive, and metacognitive dimensions of meditation. Fifty-three experienced meditators completed the LAMP after each session during a 10-day retreat. Over 60% of the assessed dimensions changed significantly over time, with distinct trajectories depending on meditation type (focused attention vs. open monitoring) and individual expertise. Three clusters of individual trajectories emerged, linked to prior experience and difficulties during the retreat. Findings on pain regulation were replicated and extended. This approach offers a rich, dynamic characterization of meditative experience.
April 8, 2024
Saampras Ganesan, Aki Tsuchiyagaito, Greg J. Siegle et al.
2 citations
preprint
Meditation practices, which have been adapted into manualized interventions for conditions like depression, pain, addiction, and anxiety, show therapeutic promise, but their neuroscientific basis remains unclear. Current neuroimaging studies rely on small, heterogeneous datasets that vary in practice types, participant experience, clinical targets, and imaging methods, limiting generalizability and replicability. To address this, the ENIGMA-Meditation consortium was formed as a global collaboration to conduct systematic meta- and mega-analyses of distributed neuroimaging data using standardized methods. This framework aims to improve statistical power and rigorously characterize the neural mechanisms underlying meditation's effects on psychological and cognitive attributes, advancing the field of contemplative neuroscience.
Neuroscience of Consciousness
November 7, 2025
Arnaud Poublan-Couzardot, Alexandre Foncelle, Éric Koun et al.
Active inference theory holds that motor actions rely on suppressing prediction errors from the body to match expected movements. This study investigated whether experienced meditators show altered somatosensory attenuation during a force-matching task. At baseline, a general somatosensory attenuation effect was present and correlated negatively with trait mindfulness, as predicted. However, intensive meditation practice did not produce a global reduction in attenuation. Instead, control participants showed a regression-to-the-mean effect that increased with task repetition, while active participants maintained their baseline level, suggesting the retreat may have affected the formation of prior expectations about force intensity. The authors discuss multiple, possibly opposite effects of meditation on proprioceptive inference.
Oussama Abdoun, Arnaud Poublan-Couzardot, Stéphane Offort et al.
preprint
A new questionnaire, the Lyon Assessment of Meditation Phenomenology (LAMP), captures how meditation experiences change over time across seven domains: context, intention, emotion, body, attention, thought, and self-awareness. Fifty-three experienced meditators completed the LAMP after each session during a 10-day retreat. Over 60% of the measured dimensions changed significantly, with distinct patterns for focused attention versus open monitoring meditation and for meditators of different expertise levels. Three clusters of individual trajectories emerged, linked to prior experience and difficulties during the retreat. The approach also replicated and extended prior findings on pain regulation. The findings suggest that meditation experience is dynamic and multidimensional, and the LAMP may help deepen understanding of meditation's mechanisms.