A field-programmable gate array (FPGA)-based data acquisition system for closed-loop experiments

Area of Science:

• Neuroscience
• Electrical Engineering
• Computer Science

Background:

• Electrophysiology experiments require precise and rapid data acquisition and feedback.
• Existing systems can be complex to set up and lack modularity for diverse experimental needs.
• Real-time processing is crucial for closed-loop experiments.

Purpose of the Study:

• To develop a custom, open-source Field-Programmable Gate Array (FPGA)-based data acquisition (DAQ) system.
• To enable real-time feedback for electrophysiology and closed-loop experiments.
• To enhance experimental setup, repeatability, and modularity.

Main Methods:

• Combined FPGA acquisition and processing with high-speed analog and digital converters.
• Implemented digital signal processing (DSP) for filter generation and feedback with microsecond latency.
• Utilized I2C, SPI controllers, 1 GiB RAM, USB3 interface to Python, and modular daughtercards via HDMI connectors.

Main Results:

• Demonstrated FPGA-based DSP and analog inner-loop control for rapid voltage stepping of a capacitor.
• Achieved microsecond latency for digital infinite impulse response filters and feedback generation.
• The system allows for in situ tuning of filter bandwidths, improving experimental control.

Conclusions:

• The developed FPGA-based DAQ system offers a flexible, modular, and high-performance solution for electrophysiology and closed-loop experiments.
• The digital approach simplifies setup and enhances repeatability.
• The system's open-source nature promotes wider adoption and customization.