实验室流媒体层用于同步多模式录制
bioRxiv : the preprint server for biology
|February 26, 2024
概括
实验室流媒体层 (LSL) 使用软件同步来自多个仪器的数据,确保神经科学和其他应用程序的精确记录. 它提供可靠的,零配置的数据流跨网络,即使有中断.
科学领域:
- 神经科学是一个神经科学.
- 计算机科学 计算机科学
- 数据采集数据采集
背景情况:
- 从多个仪器同步记录数据对于理解复杂的相互作用至关重要.
- 基于硬件的同步解决方案通常是昂贵的,并且对于各种系统来说不切实际.
- 独立的仪表表钟导致数据不对齐和记录不准确.
研究的目的:
- 引入实验室流媒体层 (LSL) 作为一种基于软件的解决方案,用于同步数据流.
- 为了在异质输入系统中实现精确,连续的数据记录.
- 为多式模式神经行为数据采集提供可靠和多功能平台.
主要方法:
- LSL使用每个样本的时间和通过局域网 (LAN) 的网络时间同步.
- 它实现了零配置功能,自动连接恢复,偏移校正和动补偿.
- 该系统支持多种编程语言 (C/C++,Python,MATLAB等) 的客户端软件的互操作性. ) 的情况.
主要成果:
- LSL支持超过150个数据采集设备类别,证明了广泛的兼容性.
- 它确保精确的数据同步,即使在网络中断或延迟期间.
- 该平台与主要的神经科学软件包集成,包括刺激呈现和BCI工具.
结论:
- LSL提供了一种弹性和多功能软件解决方案,用于实时同步多式联网数据流.
- 它处理网络复杂性的能力使得它非常适合要求神经行为研究.
- 通过LSL,可以在一个共同的时间基础上准确地捕捉生物的动态和环境变化.
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