A new study published in the journal Nature suggests that pupil size is key to understanding how and when the brain forms strong, long-lasting memories. Researchers at Cornell University in the US attached electrodes to mice brains and followed the rodents with eye-tracking cameras to study memory consolidation mechanisms. The study was led by assistant professors Azahara Oliva and Antonio Fernandez-Ruiz.
The researchers taught the mice tasks such as finding water and food in a maze and tracked their brain activity and pupil size as they slept. As a mouse learned a new task and fell asleep, the electrodes captured its brain activity and the camera recorded pupil changes, allowing the researchers to parse the processes.
During non-REM sleep, the eyes tend to stay stationary, but the pupils oscillate between small and large diameters, reflecting different substages and depths of sleep. The recordings showed that the temporal structure of sleeping mice is more akin to the sleep stages in humans than previously thought. These fluctuations are not random; they are precisely distributed across stages of non-deep sleep.
"Non-REM sleep is when the actual memory consolidation happens, and these moments are very, very short periods of time undetectable by humans, like 100 milliseconds," explained Oliva, according to The Independent. Despite their short duration, these periods have an impact on how the brain handles new information.
When a mouse enters a substage of non-REM sleep, its pupil shrinks, and the brain seems to replay recently learned tasks or new memories. Conversely, when the pupil is dilated, the brain appears to replay older memories and integrate them into previous knowledge. "We are proposing that the brain has this intermediate timescale that separates the new learning from the old knowledge," said Oliva, according to Discover Magazine. "It's like new learning, old knowledge, new learning, old knowledge, and that is fluctuating slowly throughout the sleep," Oliva added.
By interrupting the mice's sleep at different moments and later testing how well they recalled their learned tasks, the researchers were able to better understand the process. The team disrupted the mice's sleep when their pupils were smaller or larger in diameter, allowing them to determine which pupil sizes were associated with the repetition of new and old memories. The findings showed that new memories were reactivated during the substage of non-REM sleep when the pupil diameters were smaller, and older memories were replayed when the pupil diameters were larger.
Understanding how the brain consolidates memories during sleep has been a long-standing question in neuroscience. Researchers have long sought to understand the mechanisms of memory consolidation, including processes that prevent "catastrophic forgetting," where the storage of a new memory wipes out an old memory. This arrangement maintains cognitive balance and prevents such forgetting, allowing the brain to separate the consolidation of new memories from older ones.
"This temporal organization allows the brain to allocate 'special time' for each type of information," reported Discover Magazine. As a result, new memories are reprocessed without interfering with old memories, providing new possibilities for memory research and informing future memory techniques and treatments for humans.
The implications of this study extend beyond neuroscience. The findings may help computer scientists train artificial neural networks to be more efficient, contributing to the development of more efficient models of artificial intelligence.
"How does the brain distribute these screenings of memory that are very fast and very short throughout the overall night? And how does that separate the new knowledge coming in, in a way that it doesn't interfere with old knowledge that we already have in our minds?" posed Oliva, according to Mirage News. The study helps researchers understand how the brain distributes its screenings of memory, which are fast and short throughout sleep.
The research was supported by the National Institutes of Health, the Sloan Foundation, the Whitehall Foundation, the Klingenstein-Simons Fellowship Program, and the Klarman Fellowships Program.
This article was written in collaboration with generative AI company Alchemiq