Oscillating Mindfully: Using Machine Learning to Characterize Systems-Level Electrophysiological Activity During Focused Attention Meditation.

ABSTRACT:

Background

There has been rapid growth of neuroelectrophysiological studies that aspire to uncover the "black box" of mindfulness and meditation. Reliance on traditional data analysis methods hinders understanding of the complex, nonlinear, multidimensional, and systemic nature of the functional neuroelectrophysiology of meditation states.

Methods

Thus, to reveal the complex systemic neuroelectrophysiology of meditation, we applied a machine learning extreme gradient boosting classification algorithm and 4 complementary feature importance methods to extract systemic electroencephalography features characterizing mindful states from electroencephalography recorded during a focused attention meditation and a control mind-wandering state among 26 experienced meditators.

Resu

SUBMITTER: Aviad N 

PROVIDER: S-EPMC11795585 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature