The human brain comprises hundreds of interconnected regions that drive our thoughts, emotions, and behaviours. Existing brain atlases can identify major structures in MRI scans – such as the hippocampus, which supports memory and learning – but their finer sub-regions remain hard to detect. These distinctions matter because sub-regions of areas like the hippocampus, for example, are affected differently during Alzheimer’s disease progression.
Examining the brain at the cellular level is achievable using microscopy (histology), but cannot be done in living individuals, limiting its potential for understanding how the human brain changes during development, ageing and disease.
Published in Nature, the new study introduces NextBrain, an atlas of the entire adult human brain that can be used to analyse MRI scans of living patients in a matter of minutes and at a level of detail not possible until now.
The creators of the atlas, which is freely available, hope it will ultimately help to accelerate discovery in brain science and its translation into better diagnosis and treatment of conditions such as Alzheimer’s.
How the AI-assisted brain atlas was developed
The atlas took the research team six years to build through a painstaking process akin to completing a jigsaw puzzle – albeit one made using post-mortem tissue from five human brains.
Each brain was painstakingly dissected and sectioned into 10,000 pieces, stained to help identify brain structures, photographed under a microscope, then reassembled into a 3D digital model. Before they began this process, the team conducted MRI scans of the brains so they would know how to put them back together, not unlike the picture on the front of a jigsaw box.
AI was used to help align the microscope images and the MRI scans, accounting for the differences between the two techniques and ensuring that the pieces did not overlap or have gaps in between them.
A total of 333 brain regions were then labelled on the digital 3D models of each of the five brains, a process greatly accelerated by AI. Done manually, the researchers say it would’ve taken decades.
Dr Juan Eugenio Iglesias, senior author of the study from UCL Medical Physics & Biomedical Engineering and Massachusetts General Hospital/Harvard Medical School, said: “NextBrain is the culmination of years of effort to bridge the gap between microscope imaging and MRI. By combining high-resolution tissue data with advanced AI techniques, we’ve created a tool that allows researchers to analyse brain scans in a level of detail that was previously unattainable. This opens up new possibilities for studying neurodegenerative diseases and ageing.”
The resulting atlas, which is an ‘average’ of the five brain models, is generalisable to all adult humans – meaning it can be used to automatically infer detail from MRI scans of living or deceased subjects.
Brain atlas accuracy tested on thousands of scans
NextBrain was successfully tested on thousands of MRI datasets, demonstrating the ability to reliably identify brain regions across diverse imaging conditions and scanner types.
In one experiment, the team used the atlas to automatically label brain regions in a publicly available ultra-high-resolution MRI scan, which closely matched the manually labelled regions, even for small areas such as subregions of the hippocampus.
In another experiment, the researchers applied NextBrain to over 3,000 MRI scans of living individuals to investigate age-related changes in brain volume. The atlas enabled more detailed analysis of ageing patterns than could be achieved using existing tools.
Dr Zane Jaunmuktane, an author of the study from UCL Queen Square Institute of Neurology and the Queen Square Brain Bank for Neurological Disorders, said: “Our goal by building this atlas was to enable researchers to identify hundreds of brain regions in living patients quickly and consistently, while maintaining the fine-grained anatomical accuracy of microscope data. The level of anatomical detail in NextBrain is remarkable, and its public availability means that researchers worldwide can benefit from it immediately.
“NextBrain provides an unparalleled map of the brain’s cellular architecture. The foundation built into the atlas now enables rapid, accurate and accessible analysis of brain images in living individuals, opening the door to detecting the earliest signs of neurological diseases such as Alzheimer’s, long before symptoms appear, and advancing our ability to understand, monitor and ultimately prevent these devastating diseases.”
All underlying data, tools, and annotations used in NextBrain have been released openly through the FreeSurfer neuroimaging platform, along with visualisation tools and educational resources.
The study was supported by the European Research Council, Alzheimer’s Society, the Lundbeck Foundation, and the National Institutes of Health (US).
Links
- Dr Juan Eugenio Iglesias’s academic profile
- Dr Zane Jaunmuktane’s academic profile
- UCL Medical Physics & Biomedical Engineering
- UCL Faculty of Engineering
- UCL Queen Square Institute of Neurology
- UCL Faculty of Brain Sciences
Image
- Averaged brain MRI scans of 100 subjects with Alzheimer’s disease (left) and of 100 age-matched, healthy adults (right), with brain regions identified using NextBrain. Credit: Martina Bocchetta, Dorit Kliemann and Juan Eugenio Iglesias.
Media contact
Matt Midgley
Email: m.midgley [at] ucl.ac.uk
