EthoLoop

EthoLoop enables real-time optical tracking and deep-learning behavioral analysis of freely roaming animals to study neuroethology, spatial navigation, and hippocampal place-cell-like activity in naturalistic three-dimensional or nocturnal environments.

Key Features:

• Real-time optical tracking: Performs continuous optical tracking of animals in naturalistic, three-dimensional and nocturnal environments.
• 3D tracking technology: Computes three-dimensional trajectories of subjects for spatial analyses.
• Deep-learning behavioral analysis: Applies deep-learning methods for high-resolution interpretation of behavior from continuous close-up views.
• Continuous close-up views: Captures sustained close-up imaging of tracked individuals to enable detailed behavioral monitoring.
• Remote-controlled stimulus-reward boxes: Integrates remote-controlled boxes to deliver stimuli and rewards for classical conditioning and optogenetic stimulation.
• Wirelessly controlled portable devices: Uses wirelessly controlled portable devices to trigger interactions and stimuli in the field.
• Integration with wireless neurophysiology: Combines 3D tracking data with wireless neurophysiology recordings to correlate behavior and neural activity.
• Demonstrated hippocampal place-cell-like activity: Has been used to reveal place-cell-like activity in the hippocampus of freely moving primates.

Scientific Applications:

• Neuroethology in freely roaming animals: Quantifies naturalistic behavior and interactions in three-dimensional or nocturnal settings.
• Spatial navigation and memory: Maps spatial navigation and memory-related hippocampal activity, including place-cell-like responses in primates.
• Behavior–neural correlation: Correlates three-dimensional movement trajectories with wireless neurophysiology recordings.
• Closed-loop conditioning and optogenetics: Implements behavior-contingent classical conditioning and optogenetic stimulation in naturalistic environments.

Methodology:

Real-time optical tracking and three-dimensional tracking are combined with deep-learning behavioral analysis, and tracking data are integrated with wireless neurophysiology recordings.