Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham NG7 2RD, UK.
Cerca Magnetics Limited, Unit 2 Castlebridge Office Village, Kirtley Drive, Nottingham NG7 1LD, UK.
Sensors (Basel). 2023 Jun 9;23(12):5454. doi: 10.3390/s23125454.
The evolution of human cognitive function is reliant on complex social interactions which form the behavioural foundation of who we are. These social capacities are subject to dramatic change in disease and injury; yet their supporting neural substrates remain poorly understood. Hyperscanning employs functional neuroimaging to simultaneously assess brain activity in two individuals and offers the best means to understand the neural basis of social interaction. However, present technologies are limited, either by poor performance (low spatial/temporal precision) or an unnatural scanning environment (claustrophobic scanners, with interactions via video). Here, we describe hyperscanning using wearable magnetoencephalography (MEG) based on optically pumped magnetometers (OPMs). We demonstrate our approach by simultaneously measuring brain activity in two subjects undertaking two separate tasks-an interactive touching task and a ball game. Despite large and unpredictable subject motion, sensorimotor brain activity was delineated clearly, and the correlation of the envelope of neuronal oscillations between the two subjects was demonstrated. Our results show that unlike existing modalities, OPM-MEG combines high-fidelity data acquisition and a naturalistic setting and thus presents significant potential to investigate neural correlates of social interaction.
人类认知功能的进化依赖于复杂的社会互动，这些互动构成了我们的行为基础。这些社交能力在疾病和伤害中会发生巨大变化，但它们的支持神经基质仍知之甚少。 磁共振成像（MRI）同步技术采用功能神经影像学来同时评估两个人的大脑活动，是了解社交互动神经基础的最佳方法。 然而，目前的技术受到限制，要么是性能差（空间/时间精度低），要么是扫描环境不自然（幽闭的扫描仪，通过视频进行互动）。 在这里，我们描述了基于光泵磁力仪（OPM）的可穿戴脑磁图（MEG）的磁共振成像（MRI）同步技术。 我们通过同时测量两个主体执行两个独立任务（互动触摸任务和球类游戏）时的大脑活动来证明我们的方法。 尽管主体有很大且不可预测的运动，但感觉运动大脑活动被清晰地描绘出来，并且两个主体之间的神经元振荡包络的相关性也得到了证明。 我们的结果表明，与现有模态不同，OPM-MEG 结合了高保真数据采集和自然环境，因此具有很大的潜力来研究社交互动的神经相关性。
