Islam Md Nurul, Martin Seán K, Aggleton John P, O'Mara Shane M
Institute of Neuroscience, Trinity College Dublin, Dublin 2, Ireland.
School of Psychology, Cardiff University, Cardiff, UK.
Wellcome Open Res. 2019 Dec 9;4:196. doi: 10.12688/wellcomeopenres.15533.1. eCollection 2019.
There is a dearth of freely-available, standardised open source analysis tools available for the analysis of neuronal signals recorded in the freely-behaving animal. In response, we have developed a freely-available, open-source toolbox, NeuroChaT ( Neuron Characterisation Toolbox), specifically addressing this lacuna. Although we have particularly emphasised single unit analyses for spatial coding, NeuroChaT also characterises rhythmic properties of units and their dynamics associated with local field potential signals. NeuroChaT was developed using Python and facilitates a complete pipeline from automation of analysis to producing and managing publication-quality figures. Additionally, we have adopted a platform-independent format (Hierarchical Data Format version 5) for storing recorded and analysed data. By providing an easy-to-use software package, we aim to simplify the adoption of standardised analyses for behavioural neurophysiology and facilitate open data sharing and collaboration between laboratories.
目前缺乏可免费获取的、标准化的开源分析工具来分析在自由活动动物中记录的神经元信号。作为回应,我们开发了一个可免费获取的开源工具箱NeuroChaT(神经元特征工具箱),专门解决这一空白。尽管我们特别强调了用于空间编码的单单元分析,但NeuroChaT也能表征单元的节律特性及其与局部场电位信号相关的动态变化。NeuroChaT是使用Python开发的,它促进了从分析自动化到生成和管理高质量出版物图表的完整流程。此外,我们采用了一种与平台无关的格式(分层数据格式第5版)来存储记录和分析的数据。通过提供一个易于使用的软件包,我们旨在简化行为神经生理学标准化分析的采用,并促进实验室之间的开放数据共享与合作。