Moving magnetoencephalography towards real-world applications with a wearable system.
Moving magnetoencephalography towards real-world applications with a wearable system.
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DOI：
10.1038/nature26147
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发表时间：
2018-03-29
期刊：
影响因子：
64.8
通讯作者：
Brookes MJ
中科院分区：
文献类型：
--
作者：
Boto E;Holmes N;Leggett J;Roberts G;Shah V;Meyer SS;Muñoz LD;Mullinger KJ;Tierney TM;Bestmann S;Barnes GR;Bowtell R;Brookes MJ
使用诸如脑磁图（MEG）的技术对人类大脑功能进行成像通常需要受试者在他们的头部保持在限制性扫描仪内的同时执行任务。这种人工环境使得许多人无法使用这项技术，并限制了可以解决的实验问题。例如，很难将神经成像应用于婴儿和儿童认知发展的神经基质的研究，或者需要不受约束的头部运动（例如空间导航）的成人研究。在这里，我们开发了一种新型的MEG系统，可以像头盔一样佩戴，在扫描过程中允许自由和自然的运动。这是可能的，因为新的量子传感器不依赖于超导技术，与一个新的系统为零的背景磁场的集成。我们演示了毫秒分辨率的人体电生理测量，同时受试者进行自然运动，包括点头，伸展，饮酒和打球。结果与当前最先进的技术相比，即使受试者头部运动幅度很大。该系统为扫描任何受试者或患者群体开辟了新的可能性，具有无数的应用，例如神经发育连接体的表征，在虚拟环境中自然移动的成像受试者，以及理解运动障碍的病理生理学。
Imaging human brain function with techniques such as magnetoencephalography (MEG) typically requires a subject to perform tasks whilst their head remains still within a restrictive scanner. This artificial environment makes the technique inaccessible to many people, and limits the experimental questions that can be addressed. For example, it has been difficult to apply neuroimaging to investigation of the neural substrates of cognitive development in babies and children, or in adult studies that require unconstrained head movement (e.g. spatial navigation). Here, we develop a new type of MEG system that can be worn like a helmet, allowing free and natural movement during scanning. This is possible due to the integration of new quantum sensors that do not rely on superconducting technology, with a novel system for nulling background magnetic fields. We demonstrate human electrophysiological measurement at millisecond resolution whilst subjects make natural movements, including head nodding, stretching, drinking and playing a ball game. Results compare well to the current state-of-the-art, even when subjects make large head movements. The system opens up new possibilities for scanning any subject or patient group, with myriad applications such as characterisation of the neurodevelopmental connectome, imaging subjects moving naturally in a virtual environment, and understanding the pathophysiology of movement disorders.
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