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RPG: A low-cost, open-source, high-performance solution for displaying visual stimuli.

Vivian Imbriotis1, Adam Ranson2, William M Connelly3

  • 1School of Medicine, University of Tasmania, Hobart, Australia; Faculty of Medicine and Health Sciences, Universitat Internacional de Catalunya, Barcelona, Spain; Institut de Neurociènces, Universitat Autònoma de Barcelona, Bellaterra, Spain.

Journal of Neuroscience Methods
|August 31, 2021
PubMed
Summary
This summary is machine-generated.

We developed RPG, a low-cost Raspberry Pi software package for generating visual stimuli in neuroscience experiments. RPG offers precise stimulus timing and real-time feedback, overcoming limitations of existing toolkits.

Keywords:
Drifting gratingsGaborNatural stimuliRaspberry PiVisual

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Area of Science:

  • Neuroscience
  • Computational Neuroscience
  • Visual Neuroscience

Background:

  • High-throughput neuroscience tools like silicon probes and 2-photon imaging have advanced visual neuroscience.
  • Generating synchronized stimuli for these systems remains challenging and costly.
  • Existing software toolkits have limitations in hardware cost and precise triggering capabilities.

Purpose of the Study:

  • To introduce RPG (Raspberry Pi Gratings), a novel software package for visual stimulus generation.
  • To address the cost and synchronization issues associated with current stimulus delivery methods.
  • To provide an accessible and accurate solution for visual neuroscience research.

Main Methods:

  • Developed RPG, a Python package utilizing the Raspberry Pi.
  • Implemented real-time triggering and feedback mechanisms for stimulus delivery.
  • Enabled generation of drifting sine wave gratings, Gabor patches, and raw images/video.

Main Results:

  • RPG operates on a low-cost Raspberry Pi platform.
  • Stimuli are delivered at 60 frames per second with microsecond-level timing accuracy.
  • RPG provides real-time feedback on stimulus frame timings.

Conclusions:

  • RPG offers a cost-effective and accurate alternative for visual stimulus generation in neuroscience.
  • Its integrated triggering and feedback capabilities are highly beneficial for synchronized experiments.
  • The package provides a user-friendly Python interface for diverse visual stimuli.