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Decoding the Self: Single-Trial Prediction of Self-Boundary Meditation States From Magnetoencephalography Recordings.

Henrik Röhr, Daniel A Atad, Fynn-Mathis Trautwein, Pedro A. M. Mediano, Yair Dor-Ziderman, Yoav Schweitzer, Aviva Berkovich-Ohana, Stefan Schmidt, Marieke K. van Vugt

Human Brain Mapping 2026 DOI: 10.1002/hbm.70440 (opens in new tab)

Study at a glance

AI-extracted from the abstract
Characteristics Experimental study Peer reviewed
Sample size 41
Population Experienced meditation practitioners
Intervention Meditation
Topics Meditation
Citations 1
Key findings Multivariate patterns of brain activity, especially Lempel-Ziv complexity, distinguish meditation-induced self-boundary dissolution from rest with above-chance accuracy.

Abstract

The sense of self is a multidimensional feature of human experience. Different dimensions of self-experience can change drastically during altered states of consciousness induced through meditation or psychedelic drugs, as well as in a variety of mental disorders. Some experienced meditation practitioners are able to modulate their sense of self deliberately, which allows for a direct comparison between an active and suspended sense of self. Meditation therefore has the potential to serve as a model-system for alterations in the sense of self. The current study aims to identify a neural marker of such meditation-induced alterations in the sense of self based on magnetoencephalography (MEG) recordings of meditation practitioners (N = 41). Participants alternated between a state of reduced sense of self, termed self-boundary dissolution, a resting state and a control meditation state of maintaining their sense of self. Machine learning methods were used to find multivariate patterns of brain activity which distinguish these states on a single-trial basis. Source band power and Lempel-Ziv complexity features allowed to predict the mental state from MEG recordings with significantly above-chance accuracy (> 0.5). The highest performance was obtained for the self-boundary dissolution versus rest classification based on Lempel-Ziv complexity, which showed an average accuracy of ~0.64 when training and testing were performed on data from the same individual (within-participant prediction) and ~0.57 when models trained on one group of individuals were tested on different participants (across-participant prediction). Potential applications include decoded neurofeedback, for example, for clinical treatments of disorders of the sense of self, or for assistance in meditation training.

Comparable studies

Other experimental studies on meditation, most cited first.

Study Year Design Participants
The benefits of being present: Mindfulness and its role in psychological well-being. Cancer patients (clinical intervention study) 2003 Mixed methods: scale development, correlational, quasi-experimental, laboratory, experience-sampling, and clinical intervention study
Loving-kindness meditation increases social connectedness. 2008 Controlled laboratory experiment
Mindfulness and mind-wandering: Finding convergence through opposing constructs. 2012 Two studies: correlational study and experimental study
Mental Training Enhances Attentional Stability: Neural and Behavioral Evidence 2009 Experimental study
Mindfulness meditation and substance use in an incarcerated population. Incarcerated population 2006 Quasi-experimental with treatment-as-usual control condition

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