Schaechter Judith D, Stokes Christopher, Connell Brendan D, Perdue Katherine, Bonmassar Giorgio
MGH/MIT/HMS Athinoula A. Martinos Center for Biomedical Imaging, 13th Street, Building 149, Room 2301, Charlestown, MA 02129, USA.
Neuroimage. 2006 Jul 15;31(4):1549-59. doi: 10.1016/j.neuroimage.2006.02.029. Epub 2006 Apr 19.
The kinematics of motor task performance affect brain activity. However, few functional magnetic resonance imaging (fMRI) motor studies have accounted for on-line kinematics because there are currently few MRI-compatible devices to record motor performance. We built a device based on Micro-Electro-Mechanical System (MEMS) gyroscopes that measures the angular velocity of one segment of each of the 10 fingers while a subject performs a finger motor task during fMRI. Finger position, acceleration, and jerk were computed from the angular velocity measurements. The signal-to-noise ratio (SNR) of the MEMS sensors (range: 27.10-34.36 dB) allowed for clear detection of velocity of finger motion during fMRI motor task performance, and showed good stability over time. We demonstrate that use of the MEMS-based device, while negligibly increasing radiofrequency (RF) noise in the scanning environment, did not cause MR image artifacts nor alter fMRI statistical activation maps. Further, we show that signal from the MEMS sensors was not affected by the high static magnetic field (3 T). Increasing the RF power transmitted during fMRI by using a body coil, as compared to a head coil, decreased the sensor's SNR from 30.7 to 24.2 dB, though this loss in SNR did not interfere with the ability to measure velocity of finger motion. We demonstrate the utility of the MEMS-based device in fMRI motor studies through two experiments that examined the relationship between finger movement kinematics and fMRI activation in the healthy and injured brain. On-line acquisition of motor performance during fMRI, through the use of the MEMS-based device, promises to allow for a more detailed understanding of the relationship between movement kinematics and activation in the healthy and injured brain.
运动任务执行的运动学影响大脑活动。然而，很少有功能磁共振成像（fMRI）运动研究考虑在线运动学，因为目前几乎没有与MRI兼容的设备来记录运动表现。我们基于微机电系统（MEMS）陀螺仪构建了一种设备，该设备在受试者进行fMRI手指运动任务时测量10根手指中每根手指一个节段的角速度。通过角速度测量计算手指位置、加速度和加加速度。MEMS传感器的信噪比（SNR）（范围：27.10 - 34.36 dB）使得在fMRI运动任务执行期间能够清晰检测手指运动速度，并且随时间显示出良好的稳定性。我们证明，使用基于MEMS的设备虽然在扫描环境中增加的射频（RF）噪声可忽略不计，但不会导致MR图像伪影，也不会改变fMRI统计激活图。此外，我们表明MEMS传感器的信号不受高静磁场（3 T）影响。与头部线圈相比，使用体线圈在fMRI期间增加发射的RF功率会使传感器的SNR从30.7 dB降至24.2 dB，尽管SNR的这种损失并不影响测量手指运动速度的能力。我们通过两个实验证明了基于MEMS的设备在fMRI运动研究中的实用性，这两个实验研究了健康和受伤大脑中手指运动学与fMRI激活之间的关系。通过使用基于MEMS的设备在fMRI期间在线获取运动表现，有望更详细地了解健康和受伤大脑中运动学与激活之间的关系。
