A python based maze-running game for neuroscience closed-loop feedback behavioral experiments.

Major Features:

Packaged executable that can be easily run as a subprocess
Panda3D engine backend for optimized graphical processing and python development environment with no-boilerplate graphical API control
Loads experimental parameters from a JSON configuration file
Real-time data logging and saving
Configurable IO for implementing custom controllers (arduino-encoders, for example)
Customizable texture loading
Experimental block design implemented via configurable Finite-State-Machine logic built into Panda3D

Virtual Environment design

Single point geometry The controller input in a wheel encoder or a treadmill providing some velocity. There should be forward and backward movement based on whether the input is positive or negative, for example. The Virtual maze should be presented to a first-person camera and the hallway should be rendered from a 1 point perspective with “walls” that are textured and provide a visual flow based on movement. Build the design in such a way that data can be collected from the movement through the virtual maze. Make sure all parameters are loaded from a configuration file