Activity of large-scale cortical networks follows cyclical pattern, study finds

The human brain can concurrently support a wide range of advanced mental functions, including attention, memory and the processing of sensory stimuli. While past neuroscience studies have gathered valuable insight into the neural underpinnings of each of these processes, the mechanisms that ensure that they are performed efficiently and in a timely fashion have not yet been fully elucidated.

Researchers at the University of Oxford and other institutes recently set out to explore how the activity of large-scale cortical functional networks, interconnected brain regions in the brain’s outermost layer, changes over time. Their findings, published in Nature Neuroscience, suggest that the overall order in which these networks become active follows an inherently cyclical pattern.

“This research was inspired by observations that transitions between large-scale brain networks are asymmetric: we have seen that in many cases it is much more likely that network X follows network Y than the other way around,” Dr. Mats W.J. van Es, postdoctoral researcher at the University of Oxford and first author of the paper, told Medical Xpress.

“This indicated that there may be a preferential order in which networks activate. Our objectives were to characterize and quantify this organization.”

As part of their study, Van Es and his colleagues analyzed neuroimaging data that were collected using a technique known as magnetoencephalography (MEG). MEG is a noninvasive imaging method that can pick up tiny magnetic signals emitted from the brain, allowing neuroscientists to map the activity of different brain regions in real-time.

“Our lab has developed machine learning methods to detect activations in functional brain networks from this data,” explained Van Es.

“Looking at these networks, we started by simply visualizing them with their preferred activation pathways and moving them around to see if any type of organization stood out (such as local activation clusters, or cycles). Indeed, the networks and their pathways could be ordered in a pattern that clearly looked like a cycle.”

At first, when Van Es and his colleagues observed this cyclical pattern, they were unsure of whether it was in fact “real” and realistically reflected the organization of large-scale cortical networks. When they repeated their analysis on other publicly available MEG datasets and devised a reliable method to spot the cyclical patterns, they observed the same pattern.

“We found that the cyclical pattern is very robust, and moreover, that it is behaviorally relevant and affected by genetics,” said Van Es. “We’ve known for a long time that when we sleep, our brain goes through various sleep cycles, each of which performs different functions.

“Our study is the first to show that a similar cyclical pattern, albeit on much faster timescales, governs brain activity when we are awake. We think that this clock-like timing of brain networks might enable the brain to coordinate diverse cognitive functions, and make sure every task is completed within a reasonable time frame.”

The initial results gathered by these researchers might soon inspire other neuroscientists to probe the existence of the newly identified cyclical pattern. In the future, they could also contribute to the understanding of brain health and could inform the treatment of mental health disorders.

One of the co-authors of the paper, Dr. Cameron Higgins, recently created a new start-up called Resonait Medical Technologies, with the mission of developing technology that draws from the team’s observations. This technology could help to coordinate medical interventions for specific mental health disorders based on the cyclical pattern in the organization of cortical functional networks.

“I now want to better understand the mechanisms behind the cyclical pattern and understand where this preferred activation pattern comes from,” added Van Es.

“At the same time, I want to investigate how these cycles may shape or even constrain behavior: Does the preferred order of brain network activations constrain the order of cognitive operations we can complete (like memory, perception, movement)? As in sleep, disruption of the cycles could also be an important marker of brain disorders, and cycle-related measures could inform future clinical applications.”

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