Neural networks reveal how experience shapes learning in both brains and machines
A study published in Nature Neuroscience demonstrates that neural networks and human brains share similar learning patterns when exposed to structured training. The research suggests that learning simple tasks before complex ones is a fundamental requirement for both biological and artificial intelligence.
Why it matters
This provides a deeper understanding of how machine learning models can serve as effective proxies for studying human cognitive development.
edited by Gaby Clark , reviewed by Robert Egan
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Add as preferred source Credit: Pixabay/CC0 Public Domain A new study has used a type of machine learning called a neural network to reveal how different kinds of training can change how learning happens—both in machines and in living brains.
"We can use these complex models to make specific predictions about the functions of the brain regions we're interested in," says Jack Bowler, Ph.D., a postdoctoral fellow in neurobiology at University of Utah Health and first author of the study. "If you get at the most abstract level, it's a fairly good analogy for how we think the brain has to work."
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