Researchers at EPFL have developed a method to create brain-wide, biologically accurate connection maps of the mouse brain. By combining experimental data with mathematical and computational modeling, they simulate how neurons connect across the entire brain.
The study is published in the journal Nature Communications.
Nature CommunicationsUnderstanding the brain's wiring structure remains one of neuroscience's biggest challenges. While advanced imaging tools exist, creating detailed connection maps showing how billions of neurons connect—especially to distant brain regions—is difficult.
Critical for understanding both brain function and disease, these "connectomes" still offer only a partial view with traditional techniques.
Despite growing datasets, they remain too sparse to reconstruct all important connections, especially those between distant brain areas. This makes it hard to understand complex cognitive functions or identify the causes of neurological diseases.
The team at Professor Henry Markram's group in EPFL's Blue Brain Project has now produced digital yet biologically realistic brain-wide connection maps ("synthetic" in the field).
Led by Lida Kanari, they generated detailed digital models of how neurons extend their connections throughout the brain, marking a step toward creating comprehensive connectomes for research and medical applications.
Using large datasets of biological "axonal reconstructions," including new data from Professor Hanchuan Peng's team (Southeast University, China), they employed machine learning to categorize neurons based on connection patterns.
The lead author of the study, Remy Petkantchin, developed a powerful computational model that generates synthetic axons matching these patterns. This method utilized a 2022 mathematical model designed to generate digital neuron models reflecting real branching and connectivity patterns.
Synthetic axons were designed to mimic natural pathway structures so that the resulting connectomes reflect actual brain connections.
The synthetic axons closely match biological ones in appearance and connection points. When used to build network models, these connectomes resemble those from experimental data, capturing crucial long-range connections between distant brain areas.
By generating thousands of synthetic axons, the team created a digital mouse brain model with realistic wiring, allowing researchers to fill gaps in existing connectome datasets, explore neuron connectivity across the brain, and test theories that would be hard to investigate in living animals.
This research creates new opportunities for neuroscience. Digital connectomes can support large-scale brain simulations, guide experiments, and provide insights into neurological disease mechanisms.
The study focused on mouse brains, but similar principles could apply to other species as more data becomes available.