Extracellular voltage threshold settings can be tuned for optimal encoding of movement and stimulus parameters.
Extracellular voltage threshold settings can be tuned for optimal encoding of movement and stimulus parameters.
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DOI：
10.1088/1741-2560/13/3/036009
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发表时间：
2016-06
影响因子：
4
通讯作者：
Chase SM
中科院分区：
文献类型：
--
作者：
Oby ER;Perel S;Sadtler PT;Ruff DA;Mischel JL;Montez DF;Cohen MR;Batista AP;Chase SM
利用细胞外电极进行神经记录的传统目标是分离单个神经元的动作电位波形。近年来，在脑机接口（bci）中，电压波形的阈值跨越事件也传递了丰富的信息。迄今为止，检测阈值交叉的阈值已被选择以保持单个神经元的隔离。然而，单神经元识别的最优阈值不一定是信息提取的最优阈值。在这里，我们介绍了一个程序，以确定从细胞外记录提取信息的最佳阈值。我们将这一过程应用于两种不同的情况：从初级运动皮层（M1）的神经活动中编码运动学参数，以及从初级视觉皮层（V1）的神经活动中编码视觉刺激参数。我们记录了植入猴子M1或V1的多电极阵列的细胞外情况。然后，系统地扫描电压检测阈值，并量化相应阈值交叉点所传递的信息。最佳阈值取决于所需的信息。在M1中，速度的最佳编码阈值高于速度；在这两种情况下，最佳阈值都低于BCI应用程序中通常使用的阈值。在V1中，关于视觉刺激方向的信息在比视觉对比度更高的阈值下被最佳编码。一个概念模型将这些结果解释为皮质地形的结果。神经信号的处理方式影响着从中提取的信息。阈值交叉中包含的信息的类型和质量都取决于阈值设置。在这些信号中有比通常提取的更多的可用信息。将检测阈值调整为脑机接口上下文中感兴趣的参数，可以提高我们解码运动意图的能力，从而增强脑机接口的控制。此外，通过扫描检测阈值，可以深入了解附近神经组织的地形组织。
A traditional goal of neural recording with extracellular electrodes is to isolate action potential waveforms of an individual neuron. Recently, in brain–computer interfaces (BCIs), it has been recognized that threshold crossing events of the voltage waveform also convey rich information. To date, the threshold for detecting threshold crossings has been selected to preserve single-neuron isolation. However, the optimal threshold for single-neuron identification is not necessarily the optimal threshold for information extraction. Here we introduce a procedure to determine the best threshold for extracting information from extracellular recordings. We apply this procedure in two distinct contexts: the encoding of kinematic parameters from neural activity in primary motor cortex (M1), and visual stimulus parameters from neural activity in primary visual cortex (V1). We record extracellularly from multi-electrode arrays implanted in M1 or V1 in monkeys. Then, we systematically sweep the voltage detection threshold and quantify the information conveyed by the corresponding threshold crossings. The optimal threshold depends on the desired information. In M1, velocity is optimally encoded at higher thresholds than speed; in both cases the optimal thresholds are lower than are typically used in BCI applications. In V1, information about the orientation of a visual stimulus is optimally encoded at higher thresholds than is visual contrast. A conceptual model explains these results as a consequence of cortical topography. How neural signals are processed impacts the information that can be extracted from them. Both the type and quality of information contained in threshold crossings depend on the threshold setting. There is more information available in these signals than is typically extracted. Adjusting the detection threshold to the parameter of interest in a BCI context should improve our ability to decode motor intent, and thus enhance BCI control. Further, by sweeping the detection threshold, one can gain insights into the topographic organization of the nearby neural tissue.
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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
使用标记的点过程过滤器对多单位活动的位置无聚类解码。
影响因子：
2.9
作者：
Deng X;Liu DF;Kay K;Frank LM;Eden UT
通讯作者：
Eden UT
影响因子：
2.5
作者：
Golub, Matthew D.;Yu, Byron M.;Chase, Steven M.
通讯作者：
Chase, Steven M.
影响因子：
17.1
作者：
Ifft, Peter J.;Shokur, Solaiman;Nicolelis, Miguel A. L.
通讯作者：
Nicolelis, Miguel A. L.