Neuron selection and visual training for population vector based cortical control

机译：基于人口矢量的皮层控制的神经元选择和视觉训练

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We have developed a method for training animals to control artificial devices from cortical signals. In this report we describe a series of experiments designed to parameterize a cortical control algorithm without an animal having to move its arm. Instead, a highly motivated animal observes as the computer drives a cursor move towards a set of targets once each in a center-out task. From the neuronal activity recorded in this visual following task, we compute preferred directions for the neurons. We find that the quality of fit in this early set of trials is highly predictive of each neuron's contribution to the overall cortical control.

机译：我们已经开发出一种训练动物从皮层信号控制人造装置的方法。在此报告中，我们描述了一系列实验，这些实验旨在对皮质控制算法进行参数化，而无需动物动臂。取而代之的是，一个积极进取的动物在计算机驱使光标移到一组目标中时，观察到它们朝着一组目标移动。从此视觉后续任务中记录的神经元活动中，我们计算出神经元的首选方向。我们发现在此早期试验中的拟合质量可以高度预测每个神经元对总体皮质控制的贡献。

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《Engineering in Medicine and Biology Society, 2004. IEMBS '04. 26th Annual International Conference of the IEEE》||p.4607-4610|共4页
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Wahnoun R.; Tillery S.I.H.; Jiping He;
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algorithm; cortical coding; cortical control; motor cortex; neuroprosthetics;

机译：算法;皮层编码;皮层控制;运动皮层;神经修复;

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4. Visual training for population vector based cortical control [C] . R. Wahnoun, S. I. Helms Tillery, Jiping He International Conference on Neural Interface and Control; 20050526-28; Wuhan(CN) . 2005

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8. Content Based-Grid Node Selection for Vector Field Visualization [R] . Vanwalsum, T. 1993

机译：基于内容的矢量场可视化网格节点选择

Neuron selection and visual training for population vector based cortical control

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