In a new study, researchers created an AI model of the mouse visual cortex that predicts neuronal responses to visual images.
Much as a pilot might practice maneuvers in a flight simulator, scientists might soon be able to perform experiments on a realistic simulation of the mouse brain. In a new study, Stanford Medicine researchers and collaborators used an artificial intelligence model to build a"digital twin" of the part of the mouse brain that processes visual information.
The new model is an example of a foundation model, a relatively new class of AI models capable of learning from large datasets, then applying that knowledge to new tasks and new types of data -- or what researchers call"generalizing outside the training distribution." Mice have low-resolution vision -- similar to our peripheral vision -- meaning they mainly see movement rather than details or color."Mice like movement, which strongly activates their visual system, so we showed them movies that have a lot of action," Tolias said.
"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., researchers used a digital twin to discover how neurons in the visual cortex choose other neurons with which to form connections.
The researchers plan to extend their modeling into other brain areas and to animals, including primates, with more advanced cognitive capabilities. The study received funding from the Intelligence Advanced Research Projects Activity, a National Science Foundation NeuroNex grant, the National Institute of Mental Health, the National Institute of Neurological Disorders and Stroke , the National Eye Institute , the European Research Council and the Deutsche Forschungsgemeinschaft.Eric Y. Wang, Paul G. Fahey, Zhuokun Ding, Stelios Papadopoulos, Kayla Ponder, Marissa A.
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