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pyPhotometry: Open source Python based hardware and software for fiber photometry data acquisition

机译:PYPHORERY:开源基于Python基于Python的硬件和用于光纤测光数据采集的软件

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Fiber photometry is the process of recording bulk neural activity by measuring fluorescence changes in activity sensitive indicators such as GCaMP through an optical fiber. We present a system of open source hardware and software for fiber photometry data acquisition consisting of a compact, low cost, data acquisition board built around the Micropython microcontroller, and a cross platform graphical user interface (GUI) for controlling acquisition and visualising signals. The system can acquire two analog and two digital signals, and control two external LEDs via built in LED drivers. Time-division multiplexed illumination allows independent readout of fluorescence evoked by different excitation wavelengths from a single photoreceiver signal. Validation experiments indicate this approach offers better signal to noise for a given average excitation light intensity than sinusoidally-modulated illumination. pyPhotometry is substantially cheaper than commercial hardware filling the same role, and we anticipate, as an open source and comparatively simple tool, it will be easily adaptable and therefore of broad interest to a wide range of users.
机译:纤维测光术是通过通过光纤测量活性敏感指示器(例如Gcamp)的荧光变化来记录堆积神经活性的过程。我们介绍了一种开源硬件和软件系统,用于光纤测光学数据采集,包括紧凑,低成本,数据采集板,包括在Micropopton Micrococtroller周围的紧凑,低成本,数据采集板,以及用于控制采集和可视化信号的跨平台图形用户界面(GUI)。该系统可以获取两个模拟和两个数字信号,并通过内置LED驱动器控制两个外部LED。时分多路复用照明允许通过不同的激发波长从单个光致信号信号唤起荧光的独立读数。验证实验表明,对于给定的平均激发光强度,该方法比正弦调制照明提供更好的噪声信号。 PYPHORERY比填充相同角色的商业硬件,并且我们预期,作为开源和相对简单的工具,它将很容易地适应,因此对广泛的用户来说是广泛的兴趣。

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