Marchesotti Silvia, Martuzzi Roberto, Schurger Aaron, Blefari Maria Laura, Del Millán José R, Bleuler Hannes, Blanke Olaf
Laboratory of Cognitive Neuroscience, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, Geneva, Switzerland.
Center for Neuroprosthetics, Ecole Polytechnique Fédérale de Lausanne, Geneva, Switzerland.
Hum Brain Mapp. 2017 Jun;38(6):2971-2989. doi: 10.1002/hbm.23566. Epub 2017 Mar 21.
Technical advances in the field of Brain-Machine Interfaces (BMIs) enable users to control a variety of external devices such as robotic arms, wheelchairs, virtual entities and communication systems through the decoding of brain signals in real time. Most BMI systems sample activity from restricted brain regions, typically the motor and premotor cortex, with limited spatial resolution. Despite the growing number of applications, the cortical and subcortical systems involved in BMI control are currently unknown at the whole-brain level. Here, we provide a comprehensive and detailed report of the areas active during on-line BMI control. We recorded functional magnetic resonance imaging (fMRI) data while participants controlled an EEG-based BMI inside the scanner. We identified the regions activated during BMI control and how they overlap with those involved in motor imagery (without any BMI control). In addition, we investigated which regions reflect the subjective sense of controlling a BMI, the sense of agency for BMI-actions. Our data revealed an extended cortical-subcortical network involved in operating a motor-imagery BMI. This includes not only sensorimotor regions but also the posterior parietal cortex, the insula and the lateral occipital cortex. Interestingly, the basal ganglia and the anterior cingulate cortex were involved in the subjective sense of controlling the BMI. These results inform basic neuroscience by showing that the mechanisms of BMI control extend beyond sensorimotor cortices. This knowledge may be useful for the development of BMIs that offer a more natural and embodied feeling of control for the user. Hum Brain Mapp 38:2971-2989, 2017. © 2017 Wiley Periodicals, Inc.
脑机接口(BMI)领域的技术进步使用户能够通过实时解码脑信号来控制各种外部设备,如机械臂、轮椅、虚拟实体和通信系统。大多数BMI系统从有限的脑区(通常是运动和运动前皮层)采样活动,空间分辨率有限。尽管应用数量不断增加,但在全脑水平上,参与BMI控制的皮层和皮层下系统目前尚不清楚。在此,我们提供了一份关于在线BMI控制期间活跃区域的全面而详细的报告。我们在参与者在扫描仪内控制基于脑电图的BMI时记录了功能磁共振成像(fMRI)数据。我们确定了BMI控制期间激活的区域,以及它们与参与运动想象(无任何BMI控制)的区域如何重叠。此外,我们研究了哪些区域反映了控制BMI的主观感觉,即BMI动作的能动感。我们的数据揭示了一个参与操作运动想象BMI的扩展皮层-皮层下网络。这不仅包括感觉运动区域,还包括顶叶后皮质、脑岛和枕叶外侧皮质。有趣的是,基底神经节和前扣带回皮质参与了控制BMI的主观感觉。这些结果通过表明BMI控制机制超出感觉运动皮层,为基础神经科学提供了信息。这些知识可能有助于开发能为用户提供更自然和具身控制感的BMI。《人类大脑图谱》38:2971 - 2989,2017年。© 2017威利期刊公司。