Closed-Loop Systems and Real-Time Neurofeedback in Mindfulness Meditation Research

Mindfulness meditation has numerous purported benefits to psychological wellbeing, however, problems such as adherence to mindfulness tasks, quality of mindfulness sessions, or dosage of mindfulness interventions may hinder individuals from accessing the purported benefits of mindfulness. Methodologies including closed-loop systems and real-time neurofeedback may provide tools to help bolster success in mindfulness task performance, titrate the exposure to mindfulness interventions, or improve engagement with mindfulness sessions. This review explores the use of closed-loop systems and real-time neurofeedback to influence, augment, or promote mindfulness interventions. Various closed-loop neurofeedback signals from functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) have been used to provide subjective correlates to mindfulness states including: fMRI region-of-interest based signals (e.g., posterior cingulate cortex), fMRI network-based signals (e.g., default mode network, central executive network, salience network), and EEG spectral-based signals (e.g., alpha, theta, and gamma bands). Past research has focused on how successful interventions has aligned with the subjective mindfulness meditation experience. Future research may pivot towards using appropriate control conditions (e.g., mindfulness-only or sham-neurofeedback) to quantify the effects of closed-loop systems and neurofeedback-guided mindfulness meditation in improving cognition and wellbeing.