HardwareX (Sep 2025)

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

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

DOI
https://doi.org/10.1016/j.ohx.2025.e00677
Journal volume & issue
Vol. 23
p. e00677

Abstract

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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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