ElecFeX 是一个用户友好型工具箱,用于从单细胞电生理记录中高效提取特征。

IF 4.3 Q1 BIOCHEMICAL RESEARCH METHODS
Cell Reports Methods Pub Date : 2024-06-17 Epub Date: 2024-06-06 DOI:10.1016/j.crmeth.2024.100791
Xinyue Ma, Loïs S Miraucourt, Haoyi Qiu, Mengyi Xu, Erik P Cook, Arjun Krishnaswamy, Reza Sharif-Naeini, Anmar Khadra
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引用次数: 0

摘要

要了解行为和认知功能的神经基础,就必须通过神经元的电生理表型来确定其特征。技术的发展使我们能够收集数以百计的神经记录,这就需要能够高效进行特征提取的新工具。为了满足对功能强大且易于使用的工具的迫切需求,我们开发了基于 MATLAB 的开源工具箱 ElecFeX,该工具箱(1)具有直观的图形用户界面,(2)可对多种电生理特征进行自定义测量,(3)通过批量分析毫不费力地处理大型数据集,(4)提供格式化输出以供进一步分析。我们在一组不同的神经记录中实施了 ElecFeX,证明了它在捕捉电特征方面的功能性、通用性和效率,并确定了它在区分不同脑区和物种的神经元亚群方面的重要性。因此,ElecFeX 是一个用户友好型工具箱,可最大限度地缩短从电生理数据集中提取特征所需的时间,从而造福于神经科学界。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
ElecFeX is a user-friendly toolbox for efficient feature extraction from single-cell electrophysiological recordings.

Characterizing neurons by their electrophysiological phenotypes is essential for understanding the neural basis of behavioral and cognitive functions. Technological developments have enabled the collection of hundreds of neural recordings; this calls for new tools capable of performing feature extraction efficiently. To address the urgent need for a powerful and accessible tool, we developed ElecFeX, an open-source MATLAB-based toolbox that (1) has an intuitive graphical user interface, (2) provides customizable measurements for a wide range of electrophysiological features, (3) processes large-size datasets effortlessly via batch analysis, and (4) yields formatted output for further analysis. We implemented ElecFeX on a diverse set of neural recordings; demonstrated its functionality, versatility, and efficiency in capturing electrical features; and established its significance in distinguishing neuronal subgroups across brain regions and species. ElecFeX is thus presented as a user-friendly toolbox to benefit the neuroscience community by minimizing the time required for extracting features from their electrophysiological datasets.

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来源期刊
Cell Reports Methods
Cell Reports Methods Chemistry (General), Biochemistry, Genetics and Molecular Biology (General), Immunology and Microbiology (General)
CiteScore
3.80
自引率
0.00%
发文量
0
审稿时长
111 days
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