Scientific Reports
November 22, 2019
Isaac N. Treves, Lawrence Y. Tello, Richard J. Davidson et al.
118 citations
A meta-analysis of 15 studies (17 samples, 879 adults) found a small positive relationship between mindfulness and the accuracy of body awareness, with an effect size of g = 0.21. When analyzed by study design, only randomized controlled trials showed a significant link (g = 0.20). Heterogeneity was low, but low fail-safe N estimates reduce confidence in the findings. The results suggest a small but potentially detectable association between mindfulness and body awareness accuracy.
Scientific Reports
November 6, 2025
Isaac N. Treves, Ya‐Yun Chen, Caitlyn L. Wilson et al.
5 citations
A meta-analysis of 29 randomized controlled trials with 2,191 participants found that mindfulness-based interventions produce a small-to-medium improvement in self-reported interoceptive awareness (g = 0.31). Mindfulness-based programs showed the largest effects (g = 0.41). Improvements in interoception were similar in size to improvements in self-reported mindfulness and were linked to reductions in psychological distress. No evidence of publication bias was detected, and no other factors such as practice dosage or clinical sample significantly moderated the results. These findings suggest mindfulness interventions can positively alter how people subjectively experience bodily sensations, which may contribute to better mental health.
October 28, 2024
Sebastian Ehmann, Idil Sezer, Isaac N. Treves et al.
2 citations
preprint
Long-term meditators show a distinct pattern of cognitive and brain changes, including enhanced integration of sensory and cognitive processes, reduced emotional reactivity, more rational decision-making, and altered self-awareness. Neuroimaging reveals increased activity in brain networks related to interoception and pain, along with reduced connectivity between executive and salience networks, decreased amygdala response to fear, and changes in default-mode network activity linked to emotional neutrality and non-ordinary states of consciousness. Methodological limitations, such as varied meditation practices among participants, prevent clear conclusions about specific cognitive changes over time. A unified research framework is needed to systematically study advanced meditation's unfolding stages and endpoints.
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.
bioRxiv (Cold Spring Harbor Laboratory)
July 14, 2024
Isaac N. Treves, Aaron Kucyi, Madelynn Park et al.
1 citation
preprint
Trait mindfulness—the tendency to attend to present-moment experience non-judgmentally—is linked to better mental health, but its neural basis remains unclear. In the largest resting-state fMRI study of trait mindfulness to date, involving 367 adults across three samples, researchers used connectome predictive modeling to test whether brain connectivity patterns could predict mindfulness scores. No connections predicted overall trait mindfulness, but models for two subscales—Acting with Awareness and Non-judging—were identified. Positive networks for these subscales involved fronto-parietal and default-mode networks, respectively. Negative networks, which overlapped across subscales, included somatomotor, visual, and default-mode connections. Only negative networks generalized to predict subscale scores in some out-of-sample datasets, and predictions correlated negatively with a mind-wandering model. The incomplete generalization and model overlap highlight the challenge of identifying robust brain markers for mindfulness facets.