HQ Team
April 15, 2025: Using artificial intelligence Stanford researchers have developed a “digital twin” of a part of a mouse brain that processes visual information.
The digital twin was trained on large datasets of brain activity collected from the visual cortex of real mice as they watched movie clips.
It could then predict the response of tens of thousands of neurons to new videos and images.
The researchers said in the future, digital twins could make studying the inner workings of the brain easier and more efficient.
“If you build a model of the brain and it’s very accurate, that means you can do a lot more experiments,” said Andreas Tolias, PhD, Stanford Medicine professor of ophthalmology and senior author of the study.
‘Ones most promising’
“In many ways, the seed of intelligence is the ability to generalise robustly,” Tolias said. “The ultimate goal – the holy grail – is to generalize to scenarios outside your training distribution. The ones that are the most promising you can then test in the real brain.”
Unlike previous AI models of the visual cortex, which could simulate the brain’s response to only the type of stimuli they saw in the training data, the new model can predict the brain’s response to a wide range of new visual inputs.
It can even surmise the anatomical features of each neuron.
The digital twin works like a pilot practising manoeuvres in a flight simulator.
Mice watching movies
To train the new AI model, the researchers first recorded the brain activity of real mice as they watched movies – made-for-people movies. The films ideally would approximate what the mice might see in natural settings.
“It’s very hard to sample a realistic movie for mice because nobody makes Hollywood movies for mice,” Tolias said. “But action movies came close enough.
Mice have a low-resolution vision – similar to our peripheral vision – meaning they mainly see movement rather than details or colour.
“Mice like movement, which strongly activates their visual system, so we showed them movies that have a lot of action,” Tolias said.
Mad Max
Over many short viewing sessions, the researchers recorded more than 900 minutes of brain activity from eight mice watching clips of action-packed movies, such as Mad Max. Cameras monitored their eye movements and behaviour.
The Stanford researchers used the aggregated data to train a core model, which could then be customised into a digital twin of any individual mouse with a bit of additional training.
“The large quantity of aggregated training data was key to the digital twins’ success, Tolias said. “They were impressively accurate because they were trained on such large datasets.”
Though trained only on neural activity, the new models could generalize to other types of data.
Because a digital twin can function long past the lifespan of a mouse, scientists could perform a virtually unlimited number of experiments on essentially the same animal.
Speed up research
Experiments that would take years could be completed in hours, and millions of experiments could run simultaneously, speeding up research into how the brain processes information and the principles of intelligence.
“We’re trying to open the black box, so to speak, to understand the brain at the level of individual neurons or populations of neurons and how they work together to encode information,” Tolias said.
“Eventually, I believe it will be possible to build digital twins of at least parts of the human brain.
“This is just the tip of the iceberg.”
