Decoding the Self: Single-Trial Prediction of Self-Boundary Meditation States From Magnetoencephalography Recordings.
Hum Brain Mapp January 1, 2026 Henrik Röhr, Daniel A. Atad, Fynn‐mathis Trautwein et al. 1 citation
Meditation can deliberately alter the sense of self, allowing comparison between an active and suspended self. In 41 experienced meditators, magnetoencephalography recordings distinguished a state of reduced sense of self (self-boundary dissolution) from rest and a control meditation state. Machine learning using source band power and Lempel-Ziv complexity features predicted mental states with above-chance accuracy. The best performance, classifying self-boundary dissolution versus rest using Lempel-Ziv complexity, achieved average accuracy of about 0.64 for within-participant prediction and about 0.57 for across-participant prediction. This neural marker could support decoded neurofeedback for clinical treatments of self disorders or meditation training.