Machine Learning Uncovers New Insights into Human Brain Through fMRI

Study uses non-invasive neuroimaging data to reveal cellular properties of different brain regions, providing a new avenue to examine neurological disorders.

An interdisciplinary research team led by scientists from the National University of Singapore (NUS) has successfully employed machine learning to uncover new insights into the cellular architecture of the human brain.

The team demonstrated an approach that automatically estimates parameters of the brain using data collected from functional magnetic resonance imaging (fMRI), enabling neuroscientists to infer the cellular properties of different brain regions without probing the

brain using surgical means. This approach could potentially be used to assess treatment of neurological disorders, and to develop new therapies.

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