Scientists Build a Virtual Mouse With a Brain and Body

For decades, scientists have studied real animals to learn how brains and bodies work together. Now researchers have announced a new kind of lab animal that exists only inside a computer. Named Mus siliconus, this "digital mouse" combines a simulated nervous system, muscles, skeleton, and sense of touch into one unified program. Up to now, most computer models of animals treated these systems separately: a brain map here, a skeleton there. This project weaves them into a closed loop, so the virtual body moves, receives tactile feedback, and responds like a living creature.

How does it work? The team starts by scanning real mice with X-ray CT and other high-resolution imaging. Then they build a physics-based skeleton and muscles. On top of that, they run a simplified brain model that fires electrical pulses similar to real neurons, and add sensors for touch. Because every part is connected, a "sensation" on the virtual paw can change the animal's posture, and a command from the artificial brain can move its leg - just like in nature.

The potential payoff is huge. If the digital twin becomes accurate enough, scientists could use it to run experiments that are expensive, risky, or painful when done on live animals. Think drug safety tests, spinal cord injury studies, pain research, or prosthetic design. You could test whether a medicine impairs movement, or train a robotic arm by letting it practice in the virtual mouse's body. The authors call it a convergence point for neuroscience, biomechanics, artificial intelligence, and robotics.

But there's an honest catch: this is early-stage research. A real mouse brain contains tens of millions of neurons; current simulations are far simpler. The authors present this mainly as a framework, not a finished product. It also requires serious computing power. Even so, building one integrated digital animal marks a significant shift. Rather than just predicting data, such models could one day become active collaborators - suggesting hypotheses, testing interventions, and guiding real experiments on their own.