Surprising link between brain connectivity and sleep duration revealed in new neuroscience research

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Scientists have discovered a significant link between the patterns of brain connectivity and the amount of sleep individuals get. Utilizing advanced imaging techniques, the research shows that the way different regions of the brain communicate can predict how long a person typically sleeps. This finding, published in Human Brain Mapping, opens new avenues in understanding the relationship between sleep and brain function.

Previous research has extensively documented how sleep bolsters memory, attention, and overall cognitive performance. However, what remained less explored was how sleep is related to the functional organization of the brain and impacts behavior. Recognizing this gap, researchers embarked on this study to investigate how sleep patterns are reflected in the brain’s functional connectivity – essentially how different regions of the brain communicate and coordinate with each other.

The research was conducted using two major datasets: the Human Connectome Project and the Adolescent Brain Cognitive Development Study. These datasets included brain imaging and sleep data from over 11,000 participants, ranging from children to young adults.

“I’ve had a long-standing interest in sleep and in the brain networks that might influence how much we sleep. The Human Connectome Project and Adolescent Brain Cognitive Development Study datasets offered substantial sleep data alongside functional magnetic resonance imaging (fMRI) data that enabled us to better understand those networks,” explained study author Anurima Mummaneni, an undergraduate student at the University of Chicago and member of Monica D. Rosenberg’s Cognition, Attention, & Brain Lab.

The Human Connectome Project provided data from 1,206 young adults, aged 22 to 35, focusing on their self-reported sleep quality assessed through a questionnaire. The Adolescent Brain Cognitive Development Study involved 11,875 individuals from age 9–10 to age 19–20, with a focus on their sleep duration measured objectively using Fitbit devices.

For both datasets, the researchers analyzed functional Magnetic Resonance Imaging (fMRI) data, which provides a map of brain activity by detecting changes associated with blood flow. This enabled the researchers to examine functional connectivity patterns.

The researchers successfully identified specific patterns of brain connectivity that could predict an individual’s sleep duration. This predictive ability held true across different datasets and age groups, indicating a universal link between brain function and sleep duration.

The findings indicate “that the same or similar brain networks predict sleep duration in different people of different ages,” Mummaneni told PsyPost. “Sleep can be pretty variable across individuals, with different people needing to sleep less or more to function optimally. So it is really interesting to note that despite those idiosyncrasies, we’re able to see consistency in the brain networks that underlie longer and shorter durations of sleep, and general patterns emerge across fairly large participant samples.”

More specifically, the researchers found two distinct networks in the brain. These networks spanned various brain regions, including the cerebellum, motor cortices, and subcortical areas. The networks predictive of more sleep, or the ‘high-duration’ networks, included connections between the cerebellum and motor cortices. Conversely, the ‘low-duration’ networks, associated with less sleep, were more widespread and involved connections between the occipital lobes, motor cortices, and parietal regions.

Interestingly, the study also revealed that resting-state brain activity – the brain’s default mode when not engaged in specific tasks – was a better predictor of sleep duration than task-based brain activity. This finding challenges some preconceived notions about brain function, indicating that the brain’s resting state might hold more clues about our sleep patterns than previously thought.

Additionally, the study made an intriguing connection between predicted sleep duration and cognitive performance. The brain connectivity patterns associated with sleep also seemed to correlate with how well individuals performed on cognitive tasks, hinting at a deeper link between quality of sleep and cognitive abilities.

“I was surprised that sleep durations predicted by our models were correlated with participants’ actual working memory task accuracies in some datasets, even with the most conservative training parameters,” Mummaneni said. “In other words, in some cases when our brain-based models predicted that a person tended to get more sleep, that person also performed better on a working memory test. The connection between sleep and memory has been well-established in the field, but it was particularly interesting that our predictive models seemed to reflect those connections even when they were not trained to do so.”

Despite these significant findings, the study does have its limitations. Notably, the correlations between the predicted sleep duration and the actual sleep duration, while statistically significant, were modest. This indicates that while the models are theoretically meaningful, they do not provide highly precise predictions of individual sleep patterns.

Furthermore, the research is correlational in nature, meaning it does not establish a cause-and-effect relationship between brain connectivity and sleep duration. It’s unclear whether certain sleep patterns influence brain connectivity or vice versa, or if both are influenced by another factor such as stress or aging.

“Open questions remain about the causal associations between sleep and the functional brain networks we identified,” Mummaneni explained. “Does the amount of sleep someone gets impact these brain networks and/or do these networks affect sleep duration and quality? Do other factors, such as stress, influence both? I’m interested in exploring these questions in the future.”

“In the future, it would also be interesting to ask whether brain networks that predict whether people tend to get more or less sleep remain consistent within individuals. For example, if you’re someone who tends to get and need 8 hours of sleep per night, do your sleep-related brain networks change when you pull an all-nighter, or are these brain network configurations relatively stable, reflecting your average amount of sleep over longer periods of time? That sleep duration could be predicted across demographically distinct datasets would suggest this would be the case, that sleep-related networks are consistent at least from late childhood through young adulthood.”

The study, “Functional brain connectivity predicts sleep duration in youth and adults“, was authored by Anurima Mummaneni, Omid Kardan, Andrew J. Stier, Taylor A. Chamberlain, Alfred F. Chao, Marc G. Berman, and Monica D. Rosenberg.

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