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During any sleep session, slumber cycles through non-REM and REM phases, typically commencing with non-REM. Research from U-M reveals how this sequence may be vital for maintaining the clarity of our memories.

While it’s understood that sleep is vital for our physical and mental health, it continues to be an exceptionally puzzling behavior, scientifically.

Researchers at the University of Michigan, however, may have formulated a new hypothesis addressing one of the persisting enigmas of sleep.

All organisms that slumber seem to adhere to a fundamental pattern. Starting from wakefulness, beings transition into a repetitive sleep cycle characterized by low brain activity, followed by a phase where our minds are busier, often creating vibrant dreams. During this high-activity phase, human eyes also move rapidly beneath our lids, which is why it’s termed rapid eye movement, or REM, sleep.

Despite a few striking exceptions—such as individuals with narcolepsy or those who haven’t slept for extended periods—this recurring non-REM to REM sleep cycle is remarkably widespread throughout the animal kingdom.

“From an evolutionary perspective, it’s so preserved and so prevalent across species,” stated Sara Aton, U-M professor of molecular, cellular and developmental biology. “This suggests there’s likely something highly significant about this specific order of sleep. It never reverses unless the system has been severely disrupted.”

Nonetheless, researchers have struggled to find a satisfying explanation for the biological purpose of this nearly universal occurrence. Now, the U-M team led by Aton and Michal Zochowski have developed a theory based on experimental data from mice and computer simulation of the brain’s neural circuits.

This theory suggests that, if memories were like shrubs, the non-REM phase of sleep aids their growth and resilience. The REM phase subsequently trims them, ensuring they remain distinct and preventing them from merging into one another.

“It only functions if this sequence is maintained. If REM occurs first, it trims everything away, leaving no memory intact,” Aton explained. “In the correct order, you reinforce what needs reinforcement. Then REM comes in to manage the overlapping aspects of unrelated memories.”

In studies with mice, the researchers could monitor how sleep affected their recollection of simple conditioning tasks. Concerning humans, Zochowski noted, this might have recognizable implications in our daily activities.

“Imagine you have three meetings in one day. We understand that you’ll recall these meetings more effectively after a good night’s sleep,” Zochowski remarked. “It appears that during non-REM sleep, you’re consolidating the memory of each meeting. However, it’s essential to remember who mentioned what and in which meeting. REM plays a role in keeping that distinct.”

This research is detailed in the journal PLoS Computational Biology and was funded by the National Science Foundation, a Chan Zuckerberg Initiative, and the National Institutes of Health. The project was enabled, in part, by advancements made by the broader research community over the past decade, supported by the NIH’s Brain Research Through Advancing Innovative Neurotechnologies, or BRAIN, Initiative.

Cycles and circuits

Under Aton’s leadership, the researchers’ most recent experiments tracked mouse brain activity to see which regions of the hippocampus were engaged during various sleep stages after a straightforward conditioning task.

Mice were relocated from their home cages to a new space, and after exploring for a couple of minutes, they would receive a mild shock to their paws. There was also a control group of mice that did not endure such unpleasantness. This allowed the researchers to compare brain activity in sleeping mice during REM and non-REM cycles for those that had and had not formed an association between the new environment and the shock.

However, researchers are unable to pinpoint individual neurons that encode specific memories using the current techniques, which is where the team’s modeling assists in completing the picture. This model, developed by Zochowski’s group, treats newly formed memories as variations in the neural circuit activity, influenced by the brain’s environment where a chemical called acetylcholine modulates that activity.

“We can actually simulate and identify which neurons are activated by a learning event,” Aton stated. “We can model that and analyze changes concerning acetylcholine levels as an animal transitions through different sleep stages.”

There are also two types of neurons: excitatory neurons that activate their neighbors and inhibitory neurons that suppress the activity of others. By intertwining these dynamics with empirical brain activity data and acetylcholine levels during various sleep phases, the model helped uncover conclusions that were previously unattainable.

Although the researchers are enthusiastic about the findings, they underscored that this is not the ultimate conclusion on the subject. Their circuit model is a simplified depiction of the brain, and the experiments conducted focused on relatively uncomplicated memory situations. Thus, the theory could adapt or develop as researchers put it through more complex testing and furnish it with new and varied data.

“What we have now is a study that states, ‘Look, this is what could be occurring,’” Zochowski remarked. “Now we need to validate that the model corresponds with reality.”

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