Scientists move closer to creating a digital twin of the human brain

A digital twin of the human brain could allow scientists to conduct experiments that would be impossible or unethical on a living brain, researchers from the University of Warwick say.

The potential applications extend to medicine and artificial intelligence. A virtual version of an individual patient’s brain could help doctors select treatment, while brain-inspired systems could gain more advanced perception, adaptability and ways to interact with the world.

But the researchers stress that the challenge goes well beyond computing power. A useful digital twin would need reliable information about a living organ, with data that could be collected, verified and updated. General knowledge of how the brain works would not be enough for medical uses, which would require information about a particular patient.

“A digital twin of the brain is more than a large-scale simulation,” said Ruohan Zhang of the University of Warwick, a co-author of the study. “The key difference is that it represents a specific person and remains connected to their biological brain through data.”

“

A digital twin of the brain is more than a large-scale simulation. The key difference is that it represents a specific person and remains connected to their biological brain through data.

Zhang said the question therefore shifts from how many brain cells computers can simulate to how much of a particular living brain researchers can observe, incorporate into a model and update continuously.

The scale of the problem is illustrated by comparison with the roundworm C. elegans, whose nervous system has only 302 neurons and whose synaptic connections have been mapped. The human brain has nearly 90 billion neurons, and mapping the synapses between them remains beyond current technical capabilities.

The researchers propose combining several imperfect tools rather than waiting for a single flawless technology. These include electron microscopy for small brain regions, broader statistical mapping of cell types and neural circuits, and whole-brain magnetic resonance imaging. They also emphasize that structure alone is insufficient because the brain continually changes through learning and other processes.

“

How much of a particular living brain are we actually able to observe, incorporate into a model and update continuously in order to create a true digital twin?