Global cortical activity predicts shape of hand during grasping.
Global cortical activity predicts shape of hand during grasping.
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DOI：
10.3389/fnins.2015.00121
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发表时间：
2015
影响因子：
4.3
通讯作者：
Contreras-Vidal JL
中科院分区：
文献类型：
--
作者：
Agashe HA;Paek AY;Zhang Y;Contreras-Vidal JL
最近的研究表明，皮层场电位的幅度调制在时域由抓取运动学。然而，这是未知的，如果这些低频调制持续存在，并包含足够的信息来解码把握运动学在宏观尺度上的活动，通过脑电图（EEG）在头皮上测量。此外，尚不清楚关节角速度或运动协同是否是解码的最佳运动学空间。在这项离线解码研究中，我们推断从人类脑电图，手关节角速度以及协同轨迹作为主体执行自然的达到把握运动。在15个手部关节中，解码准确度（以预测运动学和实际运动学之间的相关系数（r）衡量）为r = 0.49 ± 0.02。在前三种运动协同作用中，解码精度分别为r = 0.59 ± 0.04、0.47 ± 0.06和0.32 ± 0.05。EEG通道募集的时空模式显示，对侧额中央头皮区域早期受累，随后主要感觉运动皮质区域的中央电极激活。在运动开始后250 ms，在EEG中关于抓握类型的信息含量达到峰值。本研究中的高解码准确率不仅作为宏观尺度脑活动中时域调制的证据，而且对于脑机接口领域也是重要的。我们的解码策略，利用神经的“交响乐”，而不是本地成员的神经合奏（如在颅内的方法），可以提供一种手段，提取有关电机的意图抓，而不需要穿透电极的信息，并建议它可能很快就可以开发非侵入性的神经接口控制假肢。
Recent studies show that the amplitude of cortical field potentials is modulated in the time domain by grasping kinematics. However, it is unknown if these low frequency modulations persist and contain enough information to decode grasp kinematics in macro-scale activity measured at the scalp via electroencephalography (EEG). Further, it is unclear as to whether joint angle velocities or movement synergies are the optimal kinematics spaces to decode. In this offline decoding study, we infer from human EEG, hand joint angular velocities as well as synergistic trajectories as subjects perform natural reach-to-grasp movements. Decoding accuracy, measured as the correlation coefficient (r) between the predicted and actual movement kinematics, was r = 0.49 ± 0.02 across 15 hand joints. Across the first three kinematic synergies, decoding accuracies were r = 0.59 ± 0.04, 0.47 ± 0.06, and 0.32 ± 0.05. The spatial-temporal pattern of EEG channel recruitment showed early involvement of contralateral frontal-central scalp areas followed by later activation of central electrodes over primary sensorimotor cortical areas. Information content in EEG about the grasp type peaked at 250 ms after movement onset. The high decoding accuracies in this study are significant not only as evidence for time-domain modulation in macro-scale brain activity, but for the field of brain-machine interfaces as well. Our decoding strategy, which harnesses the neural “symphony” as opposed to local members of the neural ensemble (as in intracranial approaches), may provide a means of extracting information about motor intent for grasping without the need for penetrating electrodes and suggests that it may be soon possible to develop non-invasive neural interfaces for the control of prosthetic limbs.
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影响因子：
4
作者：
Kubánek J;Miller KJ;Ojemann JG;Wolpaw JR;Schalk G
通讯作者：
Schalk G
影响因子：
16.2
作者：
Hall, Thomas M.;de Carvalho, Felipe;Jackson, Andrew
通讯作者：
Jackson, Andrew
影响因子：
4
作者：
Bradberry, Trent J.;Gentili, Rodolphe J.;Contreras-Vidal, Jose L.
通讯作者：
Contreras-Vidal, Jose L.
影响因子：
5.3
作者：
Bradberry, Trent J.;Gentili, Rodolphe J.;Contreras-Vidal, Jose L.
通讯作者：
Contreras-Vidal, Jose L.
影响因子：
120.7
作者：
Kuiken, Todd A.;Li, Guanglin;Lock, Blair A.;Lipschutz, Robert D.;Miller, Laura A.;Stubblefield, Kathy A.;Englehart, Kevin B.
通讯作者：
Englehart, Kevin B.