Saketh Malipeddi

This paper presents an open-source pipeline for EEG-based brain age modeling using the TUEG dataset, evaluating multiple regression models and incorporating SHAP for interpretability.

The paper analyzes EEG data from meditators and controls to identify neurodynamic features distinguishing meditation techniques from non-meditative states, finding shared yet distinct signatures across traditions.

This study examines non-duality in advanced meditators using EEG-based intrinsic neural timescales and psychological scales, finding that advanced meditators show reduced distinction between internal and external attention.

This study examines the time-to-onset and temporal dynamics of EEG changes during breath-watching meditation across three groups, finding significant differences in power changes between groups.

This study investigates the neural correlates of equanimity in advanced meditators using EEG data and finds shorter intrinsic neural timescales correlate with higher equanimity.