Automated, Stress-Free, and Precise Measurement of Songbird Weight in Neuroscience Experiments

Monitoring the health and well-being of research animals is essential for both ethical and scientific purposes. In songbirds, body weight is one of the main indicators for their overall condition, yet traditional weighing methods can be intrusive and stress-inducing, which could decrease their song rate. We developed a novel, automated system designed to continuously monitor the weight of untethered and tethered birds without disrupting their natural behavior in neuroscience experiments. We used the system to track weight fluctuations in six canaries over several weeks, revealing physiological patterns such as overnight weight loss, with one bird losing approximately 5.17% of its body weight during a 9.5-hour period of inactivity. Our system’s high sensitivity detected weight changes below 1% of body mass, validating its reliability for long-term studies. Control experiments confirmed that weight fluctuations observed were physiological rather than due to equipment deviations. By eliminating the need for manual handling, this system offers a non-invasive, hands-free approach that reduces stress and improves the accuracy of health assessments. This study demonstrates the system’s potential for expanding research on how environmental factors, diet, and other variables influence bird physiology and behavior. Future applications could integrate additional health metrics, providing a more comprehensive understanding of animal welfare in neuroscience and behavioral studies.