Personalized brain networks have been identified in children

Written by Sharon Salt, Senior Editor

Moving away from a ‘one-size-fits-all’ approach, scientists from Penn Medicine (PA, USA) have used machine-learning techniques to identify the size and shape of brain networks in individual children. The researchers anticipate that their findings may be useful in better understanding psychiatric disorders. The study, published in Neuron, analyzed the functional magnetic resonance imaging (fMRI) scans of nearly 700 children, adolescents and young adults, and revealed how brain networks unique to each child could predict cognition. This study is one of the first to demonstrate that functional neuroanatomy can vary greatly among kids and is refined during development. “The exciting part...

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