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Independent frequencies may explain memory recall

By gathering data from electrodes placed on the brains of patients suffering from seizures, scientists are now able to use graph theory to uncover new details about brain function during specific types of memory recall.

Intracranial electrode grid. Image courtesy Arne Ekstrom

"Previous work concentrated on only one region of the brain at a time; we didn't have enough data from different brain regions to even consider graph theory," explains Arne Ekstrom, assistant professor at the University of California Davis Center for Neuroscience, US. "The combination of multiple readings during memory retrieval and graph theory is unique."

Researchers asked volunteers to use a laptop to navigate through a virtual streetscape, taking note of their virtual surroundings and picking up and dropping off passengers at specific locations. The volunteers later had to recall the routes from memory.

"The behavioral data is collected on the laptop, and the neural recordings themselves are collected on a high-density recording system," notes Ekstrom. "The neural recordings are then transferred and analyzed on multi-core servers using Matlab, as well as customized software. Without sufficient parallel processing, the data could take several months or even years to analyze."

Frequencies and regions. Image courtesy Arne Ekstrom

The results show several brain regions involved concurrently in correct memory recall (as opposed to various brain regions activating sequentially). Analysis also reveals that two different memory types - those associated with time and those associated with space - are associated with different frequencies of brain activity. "Just like wireless devices, the brain resonates at different frequencies for spatial and temporal information. This may explain how the brain is able to recall events of time and location at the same time," concludes Ekstrom.

"This work provides us with a framework for the study of memory dysfunction in the future," says Nitin Tandon, associate professor of neurosurgery at the University of Texas Health Science Center at Houston, US. The researchers are currently collecting more data to explore encoding and how the graphs change as a function of learning.

The research is published in the journal Nature Neuroscience.

- Amber Harmon

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