How does a skeleton transfer? A brand new monitoring methodology to quantify skeletal kinematics in freely transferring rodents — ScienceDaily

How can we measure the movement of a skeleton in a furry animal as it moves through its environment? Researchers at the Max Planck Institute for Neurobiology of Behavior – caesar have developed a new method to quantify skeletal movements in freely moving rodents with a new level of accuracy and detail. It is based on building a skeletal model that calculates bone joint motion using basic anatomical principles such as: B. Joint rotation limits and speeds at which bodies can move. This approach, published in Nature Methods, opens up a new way of understanding how animals interact with their environment and begins to unveil the relationship between neural activity and complex behaviors such as decision-making as the brain and spinal cord drive movement.

Have you ever thought about how your skeleton moves throughout the day? X-ray images immediately come to mind when we think of this question. But how would we measure the movement of a skeleton without X-rays in an animal running or jumping and interacting with its environment? And why would that matter? The study of the free-roaming animal provides unprecedented insights into animal behavior and decision-making, such as when avoiding predators, finding mates, and raising their young. While many studies have measured animal behavior, studies measuring the mechanics of their movement have been lacking. But since activity in the central nervous system ultimately leads to decisions that are implemented through body movements, measuring these mechanisms and how they relate to neural activity is essential to gain deep insights into brain function.

Without an X-ray machine, analyzing the movements of individual bones is extremely difficult because the occlusion of overlying fur, skin, and soft tissue makes it difficult to obtain a measurement of skeletal movement. Recently, several advanced machine learning methods have been able to accurately measure an animal’s posture and even changes in an animal’s facial expression. However, until now none of the existing techniques have been able to track the changes in bone positions and joint movement beneath the visible body surface.

Researchers from the Department of Behavior and Brain Organization at the Max Planck Institute for Neurobiology of Behavior in Bonn, led by Jason Kerr, have now developed a videography-based method for 3D skeletal tracking with the resolution of individual joints in unbound animals interacting with their environment . Their Anatomically Constrained Model (ACM) is based on an anatomically sound skeleton that maps the skeletal kinematics of an animal as it moves freely. Using this data, it was possible to measure the inner workings of a skeleton moment by moment as the animals jumped, walked, stretched and ran around. This new approach can be applied to multiple furry species such as mice and rats of different sizes and ages. To ensure the data is correct, the researchers worked with colleagues from the Max Planck Institute for Biological Cybernetics and the Max Planck Institute for Intelligent Systems in Tübingen, using MRI scans of the animals to model the ACM compared to the actual skeleton. “Our new method is relatively simple, without cables and uses overhead cameras. It solves many problems related to tracking freely moving rodents, especially those that are covered in fur and whose body covers their legs and feet,” says Jason Kerr, who ran the study together with Jakob Macke from Tübingen. One of the next steps is to combine this approach with simultaneous recordings of neurons in the brain developed by researchers at the Max Planck Institute for Behavioral Neurobiology. This would make it possible to accurately correlate neural activity with actual behavior to find out more about how the brain itself drives complex behavior.

The researchers will also apply their new method to measure movement kinematics in other animal species in more natural settings and in multiple interacting animals at the same time. “With our new method, we will gain further insights into how animals interact with their environment on the one hand, and on the other hand we hope to gain insights into how animals interact with each other,” says Jason Kerr.

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