Advantages of closed-loop calibration in intracortical brain-computer interfaces for people with tetraplegia.
Advantages of closed-loop calibration in intracortical brain-computer interfaces for people with tetraplegia.
复制标题
对于四肢瘫痪患者，在心脏内脑机构界面中闭环校准的优点。
DOI：
10.1088/1741-2560/10/4/046012
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发表时间：
2013-08
影响因子：
4
通讯作者：
Hochberg LR
中科院分区：
文献类型：
--
作者：
Jarosiewicz B;Masse NY;Bacher D;Cash SS;Eskandar E;Friehs G;Donoghue JP;Hochberg LR
脑机接口（bci）旨在为患有严重运动障碍的人提供一种通过神经活动直接控制环境的方法。在用于四肢瘫痪患者的皮质内脑机接口中，当光标自动移动到计算机屏幕上的目标时，将神经活动映射到期望运动的解码器通常使用“开环”（OL）想象控制进行校准。然而，由于神经活动在不同的环境下会有所不同，使用OL数据校准的解码器可能不是“闭环”（CL）神经控制的最佳选择。在这里，我们测试了CL校准是否比OL校准创建更好的解码器，即使所有其他可能影响性能的因素保持不变，包括用于校准的数据量和校准与测试之间的经过时间。参加BrainGate2试点临床试验的两名四肢瘫痪患者使用皮质内脑机接口（BCI）执行了一项中心向外向后的任务，在根据OL和CL数据校准的解码器之间切换。即使所有其他变量保持不变，CL校准也改善了神经控制以及调谐模型的精度和强度。使用额外的和最新的数据更新CL解码器带来了进一步的改进。外语语境和外语语境之间的神经活动差异有助于外语解码器的优势，甚至在其额外的“适应性”优势之前。在不久的将来，CL解码器校准可以实现鲁棒的神经控制，而无需暂停正在进行的bci的实际使用，这是迈向临床应用的重要一步。
Brain-computer interfaces (BCIs) aim to provide a means for people with severe motor disabilities to control their environment directly with neural activity. In intracortical BCIs for people with tetraplegia, the decoder that maps neural activity to desired movements has typically been calibrated using “open-loop” (OL) imagination of control while a cursor automatically moves to targets on a computer screen. However, because neural activity can vary across contexts, a decoder calibrated using OL data may not be optimal for “closed-loop” (CL) neural control. Here, we tested whether CL calibration creates a better decoder than OL calibration even when all other factors that might influence performance are held constant, including the amount of data used for calibration and the amount of elapsed time between calibration and testing. Two people with tetraplegia enrolled in the BrainGate2 pilot clinical trial performed a center-out-back task using an intracortical BCI, switching between decoders that had been calibrated on OL vs. CL data. Even when all other variables were held constant, CL calibration improved neural control as well as the accuracy and strength of the tuning model. Updating the CL decoder using additional and more recent data resulted in further improvements. Differences in neural activity between OL and CL contexts contribute to the superiority of CL decoders, even prior to their additional “adaptive” advantage. In the near future, CL decoder calibration may enable robust neural control without needing to pause ongoing, practical use of BCIs, an important step toward clinical utility.
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影响因子：
64.8
作者：
Ethier, C.;Oby, E. R.;Bauman, M. J.;Miller, L. E.
通讯作者：
Miller, L. E.
影响因子：
4
作者：
Chestek CA;Gilja V;Nuyujukian P;Foster JD;Fan JM;Kaufman MT;Churchland MM;Rivera-Alvidrez Z;Cunningham JP;Ryu SI;Shenoy KV
通讯作者：
Shenoy KV
偏差，最佳线性估计以及基于峰值的大脑计算机界面算法的开环模拟与闭环性能之间的差异。
DOI：
10.1016/j.neunet.2009.05.005
发表时间：
2009-11
期刊：
Neural networks : the official journal of the International Neural Network Society
影响因子：
--
作者：
Chase SM;Schwartz AB;Kass RE
通讯作者：
Kass RE
DOI：
10.1073/pnas.1215092109
发表时间：
2012-10-16
影响因子：
11.1
作者：
Hauschild, Markus;Mulliken, Grant H.;Andersen, Richard A.
通讯作者：
Andersen, Richard A.
影响因子：
2
作者：
Edeline, JM
通讯作者：
Edeline, JM