AI model to build one of the most detailed mouse brain maps
In a powerful fusion of AI and neuroscience, researchers designed an AI model that has created one of the most detailed maps of the mouse brain to date, featuring 1,300 regions/subregions. This new map includes previously uncharted subregions of the brain, opening new avenues for neuroscience exploration.
The fundings were published in Nature Communications. They offer an unprecedented level of detail and advance our understanding of the brain by allowing researchers to link specific functions, behaviors, and disease states to smaller, more precise cellular regions—providing a roadmap for new hypotheses and experiments about the roles these areas play.
“It’s like going from a map showing only continents and countries to one showing states and cities,” said one of the study authors. “This new, detailed brain parcellation solely based on data, and not human expert annotation, reveals previously uncharted subregions of the mouse brain. And based on decades of neuroscience, new regions correspond to specialized brain functions to be discovered.”
At the heart of this breakthrough is CellTransformer, a powerful AI model that can automatically identify important subregions of the brain from massive spatial transcriptomics datasets. Spatial transcriptomics reveals where certain brain cell types are positioned in the brain but does not reveal regions of the brain based on their composition. Now, CellTransformer allows scientists to define brain regions and subdivisions based on calculations of shared cellular neighborhoods, much like sketching a city’s borders based on the types of buildings within it.
“Our model is built on the same powerful technology as AI tools like ChatGPT. Both are built on a ‘transformer’ framework which excels at understanding context,” said the senior author of the study. “While transformers are often applied to analyze the relationship between words in a sentence, we use CellTransformer to analyze the relationship between cells that are nearby in space. It learns to predict a cell's molecular features based on its local neighborhood, allowing it to build up a detailed map of the overall tissue organization.”
This model successfully replicates known regions of the brain, such as the hippocampus; but more importantly, it can also discover previously uncatalogued, finer-grained subregions in poorly understood brain regions, such as the midbrain reticular nucleus, which plays a complex role in movement initiation and release.
This new brain map depicts brain regions, versus cell types; and unlike previous brain maps, CellTransformer’s is entirely data-driven, meaning its boundaries are defined by cellular and molecular data rather than human interpretation. With 1,300 regions and subregions, it also represents one of the most granular and complex data-driven brain maps of any animal to date.
https://www.nature.com/articles/s41467-025-64259-4
https://sciencemission.com/region-discovery-in-the-mouse-brain
