Forward Prediction in the Posterior Parietal Cortex and Dynamic Brain-Machine Interface.

Forward Prediction in the Posterior Parietal Cortex and Dynamic Brain-Machine Interface.
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后顶叶皮层和动态脑机界面的正向预测。

DOI:
10.3389/fnint.2016.00035
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发表时间:
2016
影响因子:
3.5
通讯作者:
Cui H
Cui H
中科院分区:
医学3区
文献类型:
--
作者:
Cui H

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虽然在过去的二十年中,脑机接口(BMI)已经取得了显着的进展,但仍然很难利用神经信号来驱动人工致动器以响应动态刺激而产生预测运动。与主要基于前瞻性规划的自然肢体运动相反,脑控神经假肢主要依赖于反馈,而无需预先形成轨迹。后顶叶皮层(PPC)作为整合多感觉输入和传出复制的重要感觉运动接口,可能在预测运动控制中发挥积极作用。在这里,它提出了预测PPC中的神经活动可以解码,以提供假肢控制信号,用于指导BMI系统在动态环境中。
While remarkable progress has been made in brain-machine interfaces (BMIs) over the past two decades, it is still difficult to utilize neural signals to drive artificial actuators to produce predictive movements in response to dynamic stimuli. In contrast to naturalistic limb movements largely based on forward planning, brain-controlled neuroprosthetics mainly rely on feedback without prior trajectory formation. As an important sensorimotor interface integrating multisensory inputs and efference copy, the posterior parietal cortex (PPC) might play a proactive role in predictive motor control. Here it is proposed that predictive neural activity in PPC could be decoded to provide prosthetic control signals for guiding BMI systems in dynamic environments.
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