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Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator

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Real-time experimental control using network-based parallel processing.

Byounghoon Kim¹, Shobha Channabasappa Kenchappa¹, Adhira Sunkara²

¹Department of Neuroscience, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, United States.

|February 8, 2019

Summary

This summary is machine-generated.

This study introduces the Real-Time Experimental Control with Graphical User Interface (REC-GUI) framework, an open-source tool simplifying complex neuroscience experiments. REC-GUI enhances experimental flexibility and temporal fidelity for behavior-contingent research across species.

Keywords:

control system experimental control human mouse network communication neuroscience neuroscience software open-source parallel processing rhesus macaque

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Area of Science:

Neuroscience
Computational Neuroscience
Experimental Design

Background:

Coordinating multiple processes in modern neuroscience research (stimulus generation, real-time control, neural/behavioral measurements) presents technical challenges.
High temporal fidelity is crucial for complex experiments, but current technical demands limit accessibility for many labs.

Purpose of the Study:

To present an open-source, network-based parallel processing framework to lower the barrier for technically demanding neuroscience research.
To introduce the Real-Time Experimental Control with Graphical User Interface (REC-GUI) framework, designed for flexibility and ease of use.

Main Methods:

Developed a modular, open-source framework (REC-GUI) agnostic to programming languages and operating systems.
Implemented simple interfacing for diverse measurement and recording devices.
Utilized parallel processing across CPUs to achieve high temporal fidelity and real-time control via a customizable GUI.

Main Results:

The REC-GUI framework demonstrated modularity, language/OS agnosticism, and straightforward device integration.
Achieved high temporal fidelity and real-time control suitable for complex experimental paradigms.
Successfully applied the framework in human, non-human primate, and rodent studies.

Conclusions:

The REC-GUI framework significantly facilitates technically demanding, behavior-contingent neuroscience research.
Its open-source nature and flexible design democratize access to advanced experimental capabilities.
The framework supports a wide range of neuroscience applications across different species.