What is it about?

Using machine learning to study brain aging across healthy human subjects.

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Why is it important?

Atypical brain aging is often reflective of or a precursor to developmental disorders. Furthermore, abnormal trajectories in brain age have been implicated in PD, AD, as well as several other neural pathologies and even mortality.

Perspectives

Whether young brains develop properties that progressively resemble those of aged brains, and if the aging dynamics of older brains provide information about the aging trajectory in young subjects.

Siamak Sorooshyari
Stanford University

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This page is a summary of: Brain age monotonicity and functional connectivity differences of healthy subjects, PLoS ONE, May 2024, PLOS,
DOI: 10.1371/journal.pone.0300720.
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