Research in the behavioral, cognitive, neuroscience, and psychological sciences often requires multiple parallel processes operating at different time scales, including stimulus rendering and presentation, behavioral response measurements, real-time behavior-contingent experimental control, and neurophysiological recordings. The technical demands required to simultaneously manage these processes with high temporal fidelity can pose substantial technical challenges. Here we present the Real-Time Experimental Control with Graphical User Interface (REC-GUI), a novel network-based parallel processing framework that overcomes these challenges by sharing task demands between system components with different CPUs over the network. The functions of REC-GUI are broadly divided into two groups: (i) experimental control and behavioral monitoring achieved through an intuitive, highly flexible GUI, and (ii) stimulus rendering and presentation. Each group of functions is executed on separate CPUs that communicate using the internet protocols. Data acquisition of analog signals and digital events is supported by a third CPU, using event markers to precisely align information provided by the different system components in time.
The REC-GUI framework offers multiple advantages for experimental control compared to singe CPU systems. First, independent parallel processing over a network enables users to flexibly implement distinct system components using different programming languages and run on different operating systems, with the only requirement being that network interfacing is supported. This minimizes compatibility issues, maximizes the efficiency with which experimental setups are configured, and improves system performance by dividing computing demands across CPUs. Second, the use of internet protocols to interface system components allows for the use of a broad range of devices for presenting different types of stimuli (visual, vestibular, auditory, olfactory, etc.) and measuring different behaviors (e.g., button presses, eye movements, grasp configuration, spatial location in an arena, etc.). This feature broadens the range of experimental questions and animal models that REC-GUI can support. Third, a user friendly GUI allows for intuitive and flexible experimental design changes Fourth, the REC-GUI framework is agnostic to the type (if any) of neural data (e.g., electrophysiological, optical, magnetic resonance imaging) recorded. Lastly, diverse data types collected in parallel at different time scales using standard data acquisition systems are effortlessly aligned.