Machine learning is helping researchers identify the size and shape of brain networks in individual children, which may be useful for understanding psychiatric disorders. In a new study published in the journal Neuron, a multidisciplinary team showed how brain networks unique to each child can predict cognition. The study is the first to show that functional neuroanatomy can vary greatly among kids, and is refined during development.
Machine learning identifies personalized brain networks in children
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