Real-time supervisor system based on trinary logic to control experiments with behaving animals and humans.

Area of Science:

• Neuroscience
• Biomedical Engineering
• Computer Science

Background:

• Synchronous recording of physiological and behavioral data is crucial for understanding complex biological systems.
• Existing methods often face limitations in flexibility, real-time processing, and integration of diverse data streams.

Purpose of the Study:

• To introduce a new method based on trinary logic for synchronous data recording.
• To provide a flexible and efficient system for controlling experimental conditions and acquiring high-resolution data from behaving subjects.

Main Methods:

• The method utilizes a time-slice structure with programmable control flow (if-else, while-loop).
• Implemented using a real-time LabVIEW environment for experimental setup control.
• Synchronously records analog data (e.g., eye movements) at 500 Hz and neuronal data at 100 kHz.
• Features millisecond-level reaction times to digital input changes and eye position shifts.

Main Results:

• The system achieves high-resolution, synchronous data acquisition from multiple channels.
• Demonstrates millisecond-level responsiveness for precise experimental control.
• Relational databases facilitate experimental condition management and data analysis.
• Enables continuous recording without inter-trial gaps.

Conclusions:

• The proposed trinary logic-based system offers a robust solution for synchronous data acquisition in neuroscience and psychophysics.
• Its flexible design and real-time capabilities are suitable for advanced electrophysiological and psychophysical studies.
• Facilitates streamlined experimental design and data analysis for both animal and human research.