Video-based data acquisition system for use in eye blink classical conditioning procedures in sheep

Area of Science:

• Neuroscience
• Behavioral Science
• Animal Models

Background:

• Pavlovian eye blink conditioning (EBC) is a well-established learning model.
• EBC is crucial for translational research on cerebellar and hippocampal functions.
• Previous EBC methods were limited for sheep studies.

Purpose of the Study:

• To introduce an advanced digital video-based system for Pavlovian eye blink conditioning (EBC) in sheep.
• To automate the delivery of stimuli and the tracking of responses with high temporal resolution.
• To enhance the efficiency and accuracy of EBC data collection for translational neuroscience.

Main Methods:

• A digital video system delivering paired conditioned stimuli (CS; tone) and unconditioned stimuli (US; air puff).
• Automated tracking of eyelid distance to detect unconditioned responses (URs) and conditioned responses (CRs) with 5 ms resolution.
• A dedicated software application (Eye Blink Reviewer) for automated scoring and quality control of CRs and URs.

Main Results:

• The system accurately identifies and scores URs and CRs, enabling precise measurement of learning.
• Automated scoring with operator review ensures high accuracy and reliability of EBC data.
• Quantifiable learning curves based on CR frequency, onset latency, and peak latency were generated.

Conclusions:

• The digital video-based EBC system offers an efficient and automated approach for sheep studies.
• This technology facilitates robust, multigroup translational research, particularly for neurodevelopmental disorders.
• Sheep are a suitable model for studying the impact of gestational exposures on brain development using EBC.