In a recent report, researchers from the Netherlands and Spain and scientists from Singapore have, in collaboration, successfully leveraged machine learning (ML) technologies to uncover "new insights into the human brain".
According to the research report, published on Sciences Advances, the new model has the potential to assess treatment for neurological disorders and develop individualized therapies.
The research was a collaborative effort by researchers from the Universitat Pompeu Fabra, Universitat Barcelona and University Medical Center Utrecht and scientists from the National University of Singapore (NUS), led by Thomas Yeo, assistant professor at the National University of Singapore.
"The underlying pathways of many diseases occur at the cellular level, and many pharmaceuticals operate at the microscale level," Yeo said. "To know what really happens at the innermost levels of the human brain, it is crucial for us to develop methods that can delve into the depths of the brain non-invasively."
The research involved analyzing imaging data from 452 participants of the Human Connectome Project, a five-year project sponsored by 16 components of the National Institute of Health.
Dr. Peng Wang, author and researcher of the report, said: "Our approach achieves a much better fit with real data. Furthermore, we discovered that the micro-scale model parameters estimated by the ML algorithm reflect how the brain processes information."
With the new model, the team hopes that the new model can be a step towards the development of individualized treatments and have a better understanding of how individual variations in the brain's cellular architecture may correlate to differences in cognitive abilities.