New Helmet with Tiny Sensors Could Conduct Brain Scans of People in Motion

Researchers have created a pioneering helmet equipped with miniature LEGO-sized sensors capable of scanning the brain while a person is in motion. This groundbreaking development, led by the University of Nottingham (Nottingham, UK), marks a significant leap in brain scanning technology. Previously, capturing accurate magnetic fields generated by brain activity was only possible when a person remained stationary. This new lightweight helmet paves the way for easier brain scans in young children and those with neurological disorders who may find it challenging to stay still in traditional scanners. It's adaptable to various head sizes and shapes, opening new avenues for understanding brain development and the changes occurring in neurological conditions such as autism, epilepsy, stroke, concussion, and Parkinson's disease.

When neurons in the brain interact, they produce a tiny electric current that generates a magnetic field. This field is detectable and recordable through a process known as magnetoencephalography (MEG). MEG technology is capable of capturing both normal and abnormal brain signals with millisecond precision, and its results can be superimposed on an anatomical brain image to pinpoint the origins of specific brain activities. Traditional MEG systems, resembling old-fashioned hair dryers, require the subject's head to remain still and have sensors that need to be cooled to freezing temperatures or below, preventing direct contact with the scalp.

The research team at Nottingham used advanced optically pumped magnetometers (OPMs) for their helmet, which function at room temperature and can be placed close to the head, significantly enhancing data quality. The flexible design of the sensors allows for movement during scanning, addressing a major limitation of conventional MEG systems. However, OPMs require an environment free from background magnetic “noise” to ensure high-quality recordings. To tackle this, the team devised a magnetic shielding system capable of negating or compensating for these interfering magnetic fields.

They built a system with electromagnetic coils, arranged on two panels around the participant, to shield against background noise. Previous research utilized eight large coils that limited head movement due to their fixed position. The Nottingham team innovated a matrix coil system with 48 smaller coils on two panels, allowing individual control and continuous recalibration to counteract magnetic field fluctuations caused by sensor movement. This setup guarantees high-quality MEG data recording in any position, making OPM-MEG scans more comfortable and accommodating for individuals to move around.

The efficacy of this new matrix coil system was validated through four experiments. Initially, they confirmed that the helmet, when stationary and placed within the coil panels, effectively reduced background magnetic fields. A subsequent test with a healthy participant wearing the helmet demonstrated successful recording of brain function during head movement, with the coils effectively canceling out magnetic fields. Another experiment involved a wire coil attached to the helmet, which mimicked brain cell activity and confirmed the system's ability to compensate for motion-related changes. Finally, a second participant wearing the helmet illustrated the system's capability to produce high-quality brain activity recordings while walking around.

“Unconstrained movement during a scan opens a wealth of possibilities for clinical investigation and allows a fundamentally new range of neuroscientific experiments,” said Niall Holmes, Ph.D., a Mansfield Research Fellow in the School of Physics and Astronomy at the University of Nottingham, who led the research.

“By taking advantage of recent OPM-MEG technology and designing a new magnetic shielding system, this helmet represents a novel magnetoencephalography approach that could help reveal more about how the brain works,” said Shumin Wang, Ph.D., a program director in the NIBIB Division of Applied Science & Technology (Bioimaging).

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