Metcalfe Benjamin, Hunter Alan, Graham-Harper-Cater Jonathan, Taylor John
Department of Electronic and Electrical Engineering, University of Bath, England.
Department of Mechanical Engineering, University of Bath, England.
Data Brief. 2020 Nov 21;33:106561. doi: 10.1016/j.dib.2020.106561. eCollection 2020 Dec.
This article describes a dataset of action potentials collected from a neural recording experiment conducted on an adult female Sprague Dawley rat. A teased fascicle from the 5 Lumbar dorsal rootlet (L5) was fitted to a custom-made electrode array (10 wire hooks connected as isolated dipoles, with an effective inter-channel spacing of 1 mm) and neural signals were recorded both with and without manual stimulation of the corresponding dermatome. The dataset contains 20 recordings in total, 10 were made with the animal at rest and 10 were made during stimulation. Each recording contains 5 channels of raw voltage data obtained after amplification and digitisation. In [1], a new method was proposed for analysing such multi-channel data in order to automatically identify and classify the action potentials that correspond to dermal afferents. This dataset is of exceptionally high quality for a neural recording and will be useful in both the development and testing of new signal processing methods.
本文描述了一个动作电位数据集，该数据集取自对一只成年雌性斯普拉格-道利大鼠进行的神经记录实验。从第5腰神经根小束（L5）分离出的一束神经纤维被安装到一个定制的电极阵列上（10个线钩连接成隔离偶极，有效通道间距为1毫米），在手动刺激相应皮节和不刺激的情况下都记录了神经信号。该数据集总共包含20次记录，其中10次是在动物休息时进行的，10次是在刺激过程中进行的。每次记录包含5个通道的经放大和数字化处理后的原始电压数据。在[1]中，提出了一种分析此类多通道数据的新方法，以便自动识别和分类与皮肤传入神经相对应的动作电位。该神经记录数据集的质量极高，将对新信号处理方法的开发和测试都很有用。
