论文标题
在无监督的尖峰排序中具有高阶形状保存的动作电位的有效近似
Efficient Approximation of Action Potentials with High-Order Shape Preservation in Unsupervised Spike Sorting
论文作者
论文摘要
本文介绍了一个添加到常规尖峰加工链中的新颖近似单元，该单元可显着降低高硬件成本提取器的复杂性。提出了泰勒多项式的使用，并使用其级联的衍生物对每个尖峰中的基本样品进行了非均匀的衍生物进行建模，以进行可靠的特征提取和分类。包含近似单元可以在保留其形状的同时向尖峰波形提供3倍的压缩（即从66个样品到22个样品）。基于体内测量的详细尖峰波形序列已使用自定义的神经模拟器生成，以评估在六个已发表的特征提取器上测试的近似单元。对于0.05至0.3之间的噪声水平σ_n和每个通道中的3个尖峰组，所有特征提取器在近似之前和之后提供几乎相同的排序性能。包括近似单元和功能提取在内时的总体实施成本显示，在硬件昂贵且更准确的功能提取器中，大幅度减少（即高达8.7倍），从而在功能提取设计方面有了很大的改进。
This paper presents a novel approximation unit added to the conventional spike processing chain which provides an appreciable reduction of complexity of the high-hardware cost feature extractors. The use of the Taylor polynomial is proposed and modelled employing its cascaded derivatives to non-uniformly capture the essential samples in each spike for reliable feature extraction and sorting. Inclusion of the approximation unit can provide 3X compression (i.e. from 66 to 22 samples) to the spike waveforms while preserving their shapes. Detailed spike waveform sequences based on in-vivo measurements have been generated using a customized neural simulator for performance assessment of the approximation unit tested on six published feature extractors. For noise levels σ_N between 0.05 and 0.3 and groups of 3 spikes in each channel, all the feature extractors provide almost same sorting performance before and after approximation. The overall implementation cost when including the approximation unit and feature extraction shows a large reduction (i.e. up to 8.7X) in the hardware costly and more accurate feature extractors, offering a substantial improvement in feature extraction design.
