PhotoNeuro: A compact photodetector for synchronization of visual stimulus presentation during behavioural experiments in neuroscience

IF 2.1 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC

HardwareX Pub Date : 2025-07-12 DOI:10.1016/j.ohx.2025.e00677

Xavier Cano-Ferrer , Marcelo J. Moglie , George Konstantinou , Antonin Blot , Gaia Bianchini , Albane Imbert , Petr Znamenskiy , M. Florencia Iacaruso

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引用次数: 0

Abstract

Presenting visual stimuli in neuroscience experiments often requires precise temporal alignment between visual events and electrophysiological or behavioural recordings. This is typically achieved by combining analogue signals that convey timing information about the visual cue shown on liquid crystal displays (LCDs), sensed via photodetectors and recorded through analogue-to-digital converter (ADC) acquisition boards. However, most commercial photodetector systems pose limitations such as high voltage requirements, large sensor footprints that interfere with stimulus presentation, and limited compatibility with open-source platforms. Here, we present a compact, low-cost photodetector system designed for compatibility with common 3.3–5 V microcontroller-based development boards (e.g., Arduino) and the open-source visual programming language Bonsai, widely used in neuroscience for experiment control. The circuit consists of a photodiode, an amplification stage, and a low-pass filter, and can optionally incorporate an infrared filter—useful for experiments involving infrared touch displays. To facilitate reproducibility, we provide complete design files, a bill of materials and detailed building and operational instructions. We further introduce a four-channel variant, enabling the detection of four-bit binary signals for more complex synchronization needs. Validation and characterization of the device were performed through grayscale gamma correction analysis of LCD monitors using Bonsai. Additionally, we demonstrate the system’s utility in a head-fixed mouse experiment, synchronizing visual stimulus onset with neuronal recordings acquired via Neuropixels 2.0 probes. Performance comparisons with a commercial photodetector device indicate that our system achieves equivalent signal fidelity at a substantially lower cost, while maintaining a minimal footprint suitable for experimental use.

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PhotoNeuro：一种用于神经科学行为实验中视觉刺激呈现同步的紧凑型光电探测器

在神经科学实验中呈现视觉刺激通常需要在视觉事件和电生理或行为记录之间进行精确的时间对齐。这通常是通过结合模拟信号来实现的，这些模拟信号传达了液晶显示器（lcd）上显示的视觉线索的时序信息，通过光电探测器感测，并通过模数转换器（ADC）采集板记录。然而，大多数商用光电探测器系统都存在局限性，例如高电压要求，干扰刺激呈现的大传感器足迹，以及与开源平台的有限兼容性。在这里，我们提出了一个紧凑，低成本的光电探测器系统，旨在兼容常见的3.3-5 V基于微控制器的开发板（例如Arduino）和开源的可视化编程语言Bonsai，广泛用于神经科学的实验控制。该电路由一个光电二极管、一个放大级和一个低通滤波器组成，并且可以选择合并一个红外滤波器，用于涉及红外触摸显示器的实验。为了便于再现，我们提供了完整的设计文件、材料清单以及详细的建筑和操作说明。我们进一步介绍了一个四通道变体，能够检测四比特二进制信号，以满足更复杂的同步需求。通过使用Bonsai对LCD显示器进行灰度伽玛校正分析，对该器件进行了验证和表征。此外，我们在头部固定的小鼠实验中展示了该系统的实用性，通过Neuropixels 2.0探针获得的神经元记录同步视觉刺激的发生。与商用光电探测器设备的性能比较表明，我们的系统以更低的成本实现了等效的信号保真度，同时保持了适合实验使用的最小占地面积。

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来源期刊

HardwareX Engineering-Industrial and Manufacturing Engineering

CiteScore

4.10

自引率

18.20%

发文量

124

审稿时长

24 weeks

期刊介绍： HardwareX is an open access journal established to promote free and open source designing, building and customizing of scientific infrastructure (hardware). HardwareX aims to recognize researchers for the time and effort in developing scientific infrastructure while providing end-users with sufficient information to replicate and validate the advances presented. HardwareX is open to input from all scientific, technological and medical disciplines. Scientific infrastructure will be interpreted in the broadest sense. Including hardware modifications to existing infrastructure, sensors and tools that perform measurements and other functions outside of the traditional lab setting (such as wearables, air/water quality sensors, and low cost alternatives to existing tools), and the creation of wholly new tools for either standard or novel laboratory tasks. Authors are encouraged to submit hardware developments that address all aspects of science, not only the final measurement, for example, enhancements in sample preparation and handling, user safety, and quality control. The use of distributed digital manufacturing strategies (e.g. 3-D printing) is encouraged. All designs must be submitted under an open hardware license.