Recording brain activity with OPM-MEG: the physics behind the technology and experimental insights

Abstract

Magnetoencephalography (MEG) is a technique used to measure the weak magnetic fields produced by neuronal activity in the brain with the best combination of spatial and temporal precision over other noninvasive brain imaging techniques. Traditional MEG systems employ cryogenically cooled superconducting sensors held in a helmet approximately 18mm from the scalp. These systems are able to capture the pico-Tesla (pT) neuronal activity and have cemented MEG’s importance in the study of the brain; however, the rapid spatial degradation of magnetic fields as a function of distance and the presence of numerous external noise sources hinders accurate estimation of neuronal activity from MEG data. Additionally, patients are movement-restricted inside the sensor array, creating difficulties when studying traditionally less-compliant patient populations. Newer on-scalp sensors, such as optically pumped magnetometers (OPM), have recently begun to be implemented in MEG systems with the unique ability to operate at room temperature in a wearable helmet. By resting on the scalp, OPM-MEG systems greatly reduce signal depreciation over distance, offering a potential 3-to-5-fold improvement in sensitivity, and allowing for more naturalistic neuroscience studies on broader populations. In order to utilize OPM sensors to their fullest potential, refinements and innovations in typical MEG data collection and processing methods must be made that account for the novel and unique technology specifications. First, we will contextualize neuronal magnetic field sources and MEG data collection with fundamental electromagnetism and physics. Then, we will explore how OPM sensors operate by exploiting the quantum-mechanical properties of alkali metal gas vapors. We will then discuss necessary changes to typical MEG hardware and data processing techniques as a consequence of these properties, such as my novel refinements to artifact rejection methods like Maxwell Filtering, and noise reduction methods through active compensation coils and optimization of the basic magnetic field component extraction. Finally, we will highlight the exciting capabilities of the new FieldLine OPM-MEG system here at Wu Tsai, Stanford.

Alexandria (Xan) McPherson

Alexandria (who goes by Xan) is interested in the cross-section of electromagnetism, neuroscience, and psychology with a passion for utilizing physics and mathematics to motivate and expand our understanding of the brain. She received her PhD in Applied Physics at the University of Washington where she developed novel improvements to the methodology and instrumentation of on-scalp MEG systems, with a focus on achieving reliable OPM-MEG experiments. Xan is currently a postdoctoral researcher in Psychology at Stanford, working in Dr. Laura Gwilliams' lab to utilize the new FieldLine OPM-MEG system to further the study of speech comprehension on a neuronal level, while continuing to investigate improvements to OPM-MEG data collection and processing methods on a variety of projects.

About the Center for Neural Data Science Seminar Series 

The Center for Neural Data Science Seminar Series is a platform for trainees across campus to share  insights and innovative approaches that bridge the gap between neuroscience and data science. 

As neuroscience continues to generate vast amounts of data—from intricate neural circuit maps to large-scale brain activity recordings—the need for interdisciplinary expertise in data science, statistics, and engineering has never been more critical. 

The Center for Neural Data Science mission is to advance brain research through the development of cutting-edge analytical methodologies and collaborative approaches. Stanford's affiliates are invited to join this vibrant community dedicated to transformative discoveries.

This seminar series is only offered in person. 

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