People who are beginners at meditation often struggle to keep their attention focused on an object because of being lost in distraction. This can make meditation difficult, frustrating and time-consuming. Through this project, we will examine whether using advanced, high-resolution, and safe brain-based technology (functional MRI neurofeedback) can solve this issue. In other words, we aim to provide precise and live feedback of the brain dynamics of beginner meditators while they are meditating. Such live feedback can teach beginners to engage the desired brain state with the correct meditation technique. Our interdisciplinary team of engineers, psychologists, cognitive neuroscientists, physicists and meditation practitioners aims to further develop understanding of the key brain mechanisms involved in meditation. We hypothesise that learning to meditate with precise live guidance from brain activity will improve the efficiency of future meditation practice, and make meditation less time-consuming and less frustrating for beginners.
University of Melbourne contributors:
- Saampras Ganesan, PhD Candidate, School of Chemical and Biomedical Engineering, Faculty of Engineering and Information Technology
- Associate Professor Andrew Zalesky, Principal Research Fellow, Department of Psychiatry and School of Chemical and Biomedical Engineering
- Bradford Moffat, Senior Research Fellow, Radiology, Faculty of Medicine, Dentistry and Health Sciences
- Associate Professor Nicholas Van Dam, Director, Contemplative Studies Centre
External collaborators:
Our team has made great progress in the first six months of receiving seed funding. Some highlights include:
- Completed establishment and feasibility testing of fMRI neurofeedback system for the first time at the 7 Tesla functional MRI scanner in the University of Melbourne.
- Concluded pilot study involving meditation without neurofeedback inside the 7 Tesla MRI scanner, to investigate and validate key brain areas subserving focused attention meditation in beginner meditators (see https://www.biorxiv.org/content/10.1101/2023.01.02.522524v1 preprint for more details on this study).
- Completed refinement of neurofeedback experimental design, which included calibration and testing of key variables, such as neurobiological source of feedback, length of paradigm, participant fatigue inside MRI scanner, participant instructions, and ordering of behavioural assessments pre- and post-MRI. This was performed through fMRI neurofeedback pilot scanning of 2 experienced meditators and 3 beginner meditators.
- Evaluated the effect of breathing changes during meditation on fMRI signals and tested various methods for controlling breathing artefacts affecting neurofeedback signal.
- Performed various fMRI phantom scans and offline simulations to identify and troubleshoot critical real-time data transmission bugs.
- Forged international collaborations with Laureate institute for Brain research, Tulsa, USA and Harvard meditation program, USA to gain technical expertise and assistance in refining the experimental design and adopting novel technical features.
Preliminary findings from pilot experiments show that beginners at meditation can indeed learn to improve their quality of meditative focus on breathing sensations with support from live fMRI neurofeedback signals.