Closing the loop in legged neuromechanics: an open-source computer vision controlled treadmill.

Area of Science:

• Neuroscience
• Biomechanical Engineering
• Locomotion Studies

Background:

• Legged locomotion control is highly state-dependent, with responses varying based on the locomotor cycle phase.
• Understanding the neural circuitry requires tools for precise, closed-loop perturbations during natural movement.

Purpose of the Study:

• To present a computer vision feedback-controlled treadmill enabling simultaneous neural and mechanical perturbations.
• To facilitate probing the locomotor control architecture through precise, state-dependent experimental designs.

Main Methods:

• Development of a computer vision feedback-controlled treadmill.
• Testing with freely moving insects (cockroaches) and mice (Mus musculus).
• Utilizing high-speed video (HSV) data acquisition triggered by specific running criteria.

Main Results:

• Insects and mice ran freely on the treadmill at preferred speeds.
• The system successfully gathered HSV data under defined operational criteria.
• Analysis of mouse gait confirmed a normal trotting pattern using a phase-based approach.

Conclusions:

• The developed treadmill system is effective for studying locomotion in freely moving animals.
• This platform enables precise closed-loop perturbations for dissecting the neuromechanical basis of legged locomotion.