微图:一个低成本的多通道电力生理学采购系统
João Pedro Carvalho-Moreira1, Luiz Felipe Nogueira Varandas1, Matheus Costa Passos1
1Departamento de Fisiologia e Biofísica, Instituto de Ciências Biológicas - Universidade Federal de Minas Gerais, Belo Horizonte, Brasil; Centro de Tecnologia e Pesquisa em Magneto Ressonância, Programa de Pós-Graduação em Engenharia Elétrica - Universidade Federal de Minas Gerais, Belo Horizonte, Brasil.
Journal of neuroscience methods
|January 17, 2026
概括
我们开发了一种负担得起的,开源的多通道电生理记录系统. 这个工具有助于研究神经动力学和跨区域的大脑连接.
科学领域:
- 神经科学是一个神经科学.
- 生物工程是生物工程.
- 系统神经科学 系统神经科学
背景情况:
- 研究神经动力学需要多通道电生理学记录的工具.
- 了解大脑中的远程集成需要监测多个区域的神经活动.
研究的目的:
- 创建一个可访问的,低成本的,开源的多通道电生理学记录系统.
- 为了促进神经动态和信息流在远程集成中的研究.
主要方法:
- 设计了一个数字信号采集系统,将Intan RHD和德克萨斯仪器ADS芯片组与Arduino微控制器集成在一起.
- 开发了一个定制的头台和电极放置方法,使用一个穿孔的PCB进行局部场势记录.
- 在2kHz采样频率实现了32通道的录音,采样损失最小,与黄金标准系统相比.
主要成果:
- 介绍了一种低成本的生物工程解决方案,用于分布式电生理记录.
- 通过跨区域同步的神经活动,能够对大脑动态进行详细的调查.
- 在实验和模拟条件下验证信号完整性和稳定性.
结论:
- 该开源平台允许神经科学实验室以高时间精度调查大规模的神经相互作用.
- 扩大对系统神经科学工具的访问,以了解区域间大脑连接.
- 这个系统支持对大脑复杂的功能组织的研究.
相关概念视频
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The Synchronous Machine Model is a fundamental tool in analyzing and ensuring the transient stability of power systems. This model simplifies the representation of a synchronous machine under balanced three-phase positive-sequence conditions, assuming constant excitation and ignoring losses and saturation. The model is pivotal for understanding the behavior of synchronous generators connected to a power grid, particularly during transient events.
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