Sorting and tracking neuronal spikes via simple thresholding.
Sorting and tracking neuronal spikes via simple thresholding.
复制标题
通过简单的阈值处理对神经元尖峰进行排序和跟踪。
DOI：
10.1109/tnsre.2013.2289918
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发表时间：
2014
期刊：
影响因子：
--
通讯作者：
Oweiss,KarimG
中科院分区：
文献类型：
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作者：
Aghagolzadeh,Mehdi;Mohebi,Ali;Oweiss,KarimG
系统神经科学的一个基本目标是评估单个神经元在记录的集合中与观察到的行为相关时的个体和协同作用。实现这一目标的一个强制性步骤是通过特征提取和聚类技术对细胞外记录的混合物中属于单个神经元的棘波进行分类。在这里，我们提出了一种基于一种简单但最优的阈值机制来近似尖峰特征类之间经常是非线性和时变的决策边界的方法。由于阈值是一个二进制分类器，我们证明了通过充分融合一组弱的二进制分类器，可以实现尖峰分类识别所需的复杂的非线性决策边界。通过最大化稀疏表示类之间的可分离性的学习算法，自适应地估计这些二进制分类器的阈值。基于我们以前的工作，该方法大大降低了在数据流早期提取、对齐和排序多个单一单元活动的计算复杂性。在这里，我们还展示了它在较长时间内跟踪棘波特征变化的能力，使其非常适合于基础神经科学研究以及在脑机接口应用中的微型化、完全可植入的电子设备中的实施。
A fundamental goal in systems neuroscience is to assess the individual as well as the synergistic roles of single neurons in a recorded ensemble as they relate to an observed behavior. A mandatory step to achieve this goal is to sort spikes in an extracellularly recorded mixture that belong to individual neurons through feature extraction and clustering techniques. Here, we propose an approach for approximating the often nonlinear and time varying decision boundaries between spike-derived feature classes based on a simple, yet optimal thresholding mechanism. Because thresholding is a binary classifier, we show that the complex nonlinear decision boundaries required for spike class discrimination can be achieved by adequately fusing a set of weak binary classifiers. The thresholds for these binary classifiers are adaptively estimated through a learning algorithm that maximizes the separability between the sparsely represented classes. Based on our previous work, the approach substantially reduces the computational complexity of extracting, aligning and sorting multiple single unit activity early in the data stream. Here, we also show its ability to track changes in spike features over extended periods of time, making it highly suitable for basic neuroscience studies as well as for implementation in miniaturized, fully implantable electronics in brain-machine interface applications.