Decoding of muscle activity from the sensorimotor cortex in freely behaving monkeys
Decoding of muscle activity from the sensorimotor cortex in freely behaving monkeys
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自由行为猴子感觉运动皮层肌肉活动的解码
DOI：
10.1016/j.neuroimage.2019.04.045
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发表时间：
2019
期刊：
影响因子：
5.7
通讯作者：
Seki Kazuhiko
中科院分区：
文献类型：
--
作者：
Umeda Tatsuya;Koizumi Masashi;Katakai Yuko;Saito Ryoichi;Seki Kazuhiko
最近，用于恢复或增强运动功能的脑机接口(BMI)技术的开发取得了显著进展。然而，这些技术的应用可能仅限于静态条件下的患者，因为这些发展主要基于对受限运动条件下的动物(例如非人类灵长类动物)的研究。BMI技术的最终目标是使个人能够在没有身体约束的情况下自然移动身体或控制外部设备。在这里，我们展示了从皮层脑电(ECoG)信号中准确解码无拘无束、行为自由的猴子的肌肉活动。我们记录了来自感觉运动皮质的ECoG信号和来自上臂多个肌肉的肌电信号，而猴子则进行了两种不受身体约束的运动：强迫前肢运动(杠杆-拉动任务)和自然全身运动(笼子内的自由运动)。就像以前使用被束缚的猴子的报告一样，我们证实，根据同时记录的ECoG数据，可以准确地预测强迫前肢运动时的肌肉活动。更重要的是，我们证明了在进行自然全身运动的猴子身上，通过ECoG数据准确预测肌肉活动是可能的。我们发现，初级运动皮质中的高伽马活动主要有助于预测自然全身运动和强迫前肢运动中的肌肉活动。相比之下，在自然的全身运动中，运动前皮质和初级体感皮质的高伽马活动的贡献要大得多。因此，在自然全身运动中，需要较大面积的感觉运动皮质的活动来预测肌肉活动。此外，强迫前肢运动获得的译码模型不能推广到自然的全身运动，这表明译码应该根据不同的行为类型单独构建。这些结果为BMI系统在自由型个体中的应用奠定了基础。
Remarkable advances have recently been made in the development of Brain-Machine Interface (BMI) technologies for restoring or enhancing motor function. However, the application of these technologies may be limited to patients in static conditions, as these developments have been largely based on studies of animals (e.g., non-human primates) in constrained movement conditions. The ultimate goal of BMI technology is to enable individuals to move their bodies naturally or control external devices without physical constraints. Here, we demonstrate accurate decoding of muscle activity from electrocorticogram (ECoG) signals in unrestrained, freely behaving monkeys. We recorded ECoG signals from the sensorimotor cortex as well as electromyogram signals from multiple muscles in the upper arm while monkeys performed two types of movements with no physical restraints, as follows: forced forelimb movement (lever-pull task) and natural whole-body movement (free movement within the cage). As in previous reports using restrained monkeys, we confirmed that muscle activity during forced forelimb movement was accurately predicted from simultaneously recorded ECoG data. More importantly, we demonstrated that accurate prediction of muscle activity from ECoG data was possible in monkeys performing natural whole-body movement. We found that high-gamma activity in the primary motor cortex primarily contributed to the prediction of muscle activity during natural whole-body movement as well as forced forelimb movement. In contrast, the contribution of high-gamma activity in the premotor and primary somatosensory cortices was significantly larger during natural whole-body movement. Thus, activity in a larger area of the sensorimotor cortex was needed to predict muscle activity during natural whole-body movement. Furthermore, decoding models obtained from forced forelimb movement could not be generalized to natural whole-body movement, which suggests that decoders should be built individually and according to different behavior types. These results contribute to the future application of BMI systems in unrestrained individuals.
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影响因子：
2.5
作者：
Tresch, MC;Cheung, VCK;d'Avella, A
通讯作者：
d'Avella, A
影响因子：
2.5
作者：
Flint, Robert D.;Ethier, Christian;Slutzky, Marc W.
通讯作者：
Slutzky, Marc W.
影响因子：
2.4
作者：
Jaman, M. Firoj;Huffman, Michael A.
通讯作者：
Huffman, Michael A.
发育中的普通狨猴的运动评估
影响因子：
5.6
作者：
Yiwen Wang;Qin Fang;Neng Gong
通讯作者：
Neng Gong
从灵长类动物原发性运动皮层中的高频局部田间电位中解码3-D覆盖范围并掌握了运动学。
DOI：
10.1109/tbme.2010.2047015
发表时间：
2010-07
期刊：
IEEE transactions on bio-medical engineering
影响因子：
--
作者：
Zhuang J;Truccolo W;Vargas-Irwin C;Donoghue JP
通讯作者：
Donoghue JP