Researchers in Belgium have used AI, trained on human and animal data, to shed light on how different brain cells have evolved over time and how this may give clues to brain diseases.

The study, at EARA members VIB.AI and VIB-KU Leuven Center for Brain & Disease Research, used a type of AI algorithm – known as deep learning – to better understand the genetics that underpin the differences and similarities in the brain make-up of mammals and birds.

By training the AI on brain data from humans, mice and chickens, the team could compare the features of different types of brain cell across species, covering more than 300 million years of evolution (this results in some cells remaining unchanged among species, while others evolve very differently).

There were notable similarities in the so-called regulatory code in certain bird and mammal brain cells – where short DNA sequences, that switch certain genes on or off, are uniquely controlled to dictate the type of cell they become in the body.  

Lead author Stein Aerts said: “Ultimately, models that learn the genomic regulatory code hold the potential to screen genomes and investigate the presence or absence of specific cell types or cell states in any species. This would be a powerful tool to study and better understand disease.”