Recursive Bayesian decoding of motor cortical signals by particle filtering
Recursive Bayesian decoding of motor cortical signals by particle filtering
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DOI：
10.1152/jn.00438.2003
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发表时间：
2004-04-01
影响因子：
2.5
通讯作者：
Kass, RE
中科院分区：
文献类型：
--
作者：
Brockwell, AE;Rojas, AL;Kass, RE
群体向量（PV）算法和最优线性估计（OLE）已被用来重建运动，结合来自运动皮层中的多个神经元的信号。虽然这些线性方法是有效的，递归贝叶斯解码方案，这是非线性的，可以更强大的概率模型假设得到满足。我们已经实现了一个递归贝叶斯算法重建运动皮层神经元的手部运动。该算法使用最近开发的数值方法称为“粒子滤波”，并遵循相同的一般策略，布朗等人所使用的。从海马位置细胞重建觅食大鼠的路径。我们调查的方法，在数值模拟研究中，神经放电率被假定为是积极的，但在其他方面的运动速度的线性函数，和首选方向不均匀分布。就均方误差而言，该方法的效率比PV算法高10倍，比OLE算法高5倍。因此，使用递归贝叶斯解码可以达到PV算法（或OLE）的精度，而神经元数量减少10倍（或5倍）。该方法也被用来重建手的运动在椭圆形绘制任务从腹侧前运动皮层的258个细胞。递归贝叶斯解码再次比PV和OLE方法更有效，分别约为7倍和3倍。
The population vector (PV) algorithm and optimal linear estimation (OLE) have been used to reconstruct movement by combining signals from multiple neurons in the motor cortex. While these linear methods are effective, recursive Bayesian decoding schemes, which are nonlinear, can be more powerful when probability model assumptions are satisfied. We have implemented a recursive Bayesian algorithm for reconstructing hand movement from neurons in the motor cortex. The algorithm uses a recently developed numerical method known as "particle filtering" and follows the same general strategy as that used by Brown et al. to reconstruct the path of a foraging rat from hippocampal place cells. We investigated the method in a numerical simulation study in which neural firing rate was assumed to be positive, but otherwise a linear function of movement velocity, and preferred directions were not uniformly distributed. In terms of mean-squared error, the approach was similar to10 times more efficient than the PV algorithm and 5 times more efficient than OLE. Thus use of recursive Bayesian decoding can achieve the accuracy of the PV algorithm (or OLE) with similar to10 times (or 5 times) fewer neurons. The method was also used to reconstruct hand movement in an ellipse-drawing task from 258 cells in the ventral premotor cortex. Recursive Bayesian decoding was again more efficient than the PV and OLE methods, by factors of roughly seven and three, respectively.