Versatile software and hardware combo enabling photon counting acquisition and real-time display for multiplexing, 2D...

Area of Science:

• * Neuroscience
• * Optics
• * Computational Biology

Background:

• * Photon counting enhances signal-to-noise ratio in photon-limited imaging applications.
• * Commercial multiphoton microscopy systems offer limited data channels and customization.
• * Researchers often need to develop custom electronics and software for advanced experiments.

Purpose of the Study:

• * To develop a flexible, open-source interface for multichannel fast digitizers.
• * To enable integration with existing imaging systems for tailored experiments.
• * To facilitate advanced photon counting applications in microscopy.

Main Methods:

• * Developed rPySight, an open-source software application using Rust and Python.
• * Integrated a multichannel digitizer capable of 70 million tags/s.
• * Utilized graphical processing unit (GPU) for real-time data stream processing.

Main Results:

• * Demonstrated rPySight for real-time 2D and 3D imaging, including varifocal lens applications.
• * Showcased improved calcium imaging and multiplexing capabilities.
• * Provided a detailed implementation protocol for hardware and software.

Conclusions:

• * Photon counting is crucial for overcoming classical multiphoton imaging speed limitations.
• * rPySight's performance facilitates capturing dynamics of large neuronal and vascular populations.
• * The platform supports advanced research in understanding the hemodynamic response.