Memories resonate in the mind even when it's not aware
of processing them. New research from Rice University and Michigan Medicine
takes a step toward understanding why these ripples hint at the bigger picture
of how brains sort and store information. Researchers led by Caleb Kemere of
Riceand Kamran Diba of Michigan Medicine have developed a tool to form
quantitative models of memory. Their strategy analyzes waves of firing neurons
that race in an instant across the hippocampus and beyond in animals while they're
active and, significantly, while they rest. The researchers' work employs
hidden Markov models commonly used in machine learning to study sequential
patterns. Their models demonstrated that minimal data harvested from the brain
during periods of rest can be used to explore big ideas about how memories form
and are retained.
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