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 Rice and 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.

The team’s open-access paper appears in the journal eLife. The firing patterns of neurons in the hippocampus — seahorse-shaped tissues in each hemisphere of the brain — have long been seen as important to the formation and storage of memories.

Researchers detect and measure these patterns by placing electrodes into the brains to monitor them in real time. “Animals encode a memory of an environment as they run around,” said Kemere, an assistant professor of electrical and computer engineering who specializes in neuroscience. Read more from…

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