A wearable ‘bike helmet’ style brain scanner that allows natural movement during scanning has been trialled in children for the first time at the University of Nottingham’s Sir Peter Mansfield Imaging Centre.
The device opens up the opportunity to study both healthy brain function and neurological conditions such as epilepsy and autism in children, and can be used in adult patients too.
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The scanner was built in a research collaboration between the University of Nottingham, the University of Oxford and University College London.
Large scanners for traditional magnetoencephalography (MEG) can present difficulties for children as they require patients to stay completely still for extended periods of time. Another issue is that they can’t provide a picture of the brain operating in a natural environment, meaning the results of scans can’t always be generalised to a patient’s daily life.
The research team have solved this problem by condensing a half-ton MEG machine into a 500g helmet fitted with lightweight quantum sensors, which can adapt to any head size.
Because the new sensors can be placed very close to the head, the amount of signal that they can pick up is vastly increased compared to conventional equipment, where sensors need to be kept at a temperature of -269° and therefore far from the head.
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By GlobalDataSpecial electromagnetic coils enable accurate control of background magnetic fields, allowing individuals to be scanned while they move freely.
University of Nottingham MEG research leader Professor Matthew Brookes said: “This study is a hugely important step towards getting MEG closer to being used in a clinical setting, showing it has real potential for use in children. The challenge now is to expand this further, realising the theoretical benefits such as high sensitivity and spatial resolution, and refining the system design and fabrication, taking it away from the laboratory and towards a commercial product.”
As well as looking at children’s brain activity, the researchers used the scanner to examine the brain activity of an adult learning a musical instrument, which would not be possible inside a typical MEG scanner.
The results of the study have been published in Nature Communications.
