How Brain Networks Sustain Attention

Summary: A new study investigates the brain mechanisms behind deep focus. The research uses fMRI to explore low-frequency fluctuations in brain networks during focused and less focused states.

The team discovered that certain brain networks synchronize and desynchronize, affecting an individual’s ability to sustain attention. This understanding of the dynamic nature of brain activity could lead to better strategies for improving focus and attention in various cognitive tasks.


  1. The study examines the relationship between quasi-periodic brain network fluctuations and sustained attention, finding a pattern that recurs approximately every 20 seconds.
  2. The main brain networks involved include the frontoparietal control network (FPCN) and the default mode network (DMN), which play roles in on-task focus and internal thought, respectively.
  3. Results indicate that synchronization between these networks can predict changes in attention levels, providing a potential framework for improving cognitive function.

Source: Georgia Institute of Technology

Whether it was solving puzzles, playing music, reading, or exercising, Dolly Seeburger loved activities that demanded her full attention. “It was in those moments that I felt the happiest, like I was in the zone,” she recalls. “Hours would pass, but it would feel like minutes.”

Although this state of deep concentration is essential for highly effective work, it is still not fully understood. Now, a new study led by Seeburger, a graduate student in the School of Psychology, alongside her advisor, Eric Schumacher, a professor in the School of Psychology, uncovers the mechanisms behind this.

“I think this answers a really fundamental question about the relationship between behavior and brain activity,” he adds. Credit: Neuroscience News

The Georgia Tech interdisciplinary team also includes Nan Xu, Sam Larson and Shella Keilholz (Coulter Department of Biomedical Engineering), alongside Marcus Ma (College of Computer Science) and Christine Godwin (School of Psychology).

The researchers’ study, “Time-varying functional connectivity predicts fluctuations in sustained attention in a serial tapping task,” published in Cognitive, affective and behavioral neurosciencestudies brain activity via fMRI during periods of deep concentration and less focused work.

This work is the first to study low-frequency fluctuations between different brain networks during concentration and could serve as a springboard for studying more complex behaviors and concentration states.

“Your brain is dynamic. Nothing is just on or off,” says Seeburger.

“This is the phenomenon we wanted to study. How to enter the zone? Why are some people better at maintaining attention than others? Is this something that can be trained? If so, can we help people improve? »

The dynamic brain

The team’s work is also the first to study the relationship between fluctuations in attention and brain network patterns within these 20-second low-frequency cycles.

“For some time, studies of neuronal oscillations have focused on faster temporal frequencies, and the appreciation of these very low-frequency oscillations is relatively new,” says Seeburger.

“But these low-frequency fluctuations may play a key role in regulating higher cognitive functions, such as sustained attention.”

“One of the things we found in previous research is that there is a natural fluctuation in the activity of certain brain networks. When a subject is not performing a specific task while in the MRI scanner, we find that this fluctuation occurs approximately every 20 seconds,” adds co-author Schumacher, explaining that the team was interested in this pattern because it is quasi-periodic, meaning it does not repeat exactly every 20 seconds and it varies across different trials and subjects.

By studying these quasi-periodic cycles, the team hoped to measure the relationship between brain fluctuation in these networks and behavioral fluctuation associated with shifts in attention.

Your attention is needed

To measure attention, participants tapped a metronome while in an fMRI scanner. The team was able to gauge how “in the zone” participants were by measuring the degree of variability in each participant’s tapping: greater variability suggested the participant was less focused, while precise tapping suggested the participant was “in the zone”.

The researchers found that when a subject’s concentration level changed, different regions of the brain synchronized and desynchronized, specifically the frontoparietal control network (FPCN) and the default mode network (DMN).

The FPCN is engaged when a person is trying to stay focused on their task, while the DMN is correlated with inward-directed thoughts (which a participant may have when less focused).

“When you’re out of the area, these two networks synchronize and are in phase at low frequencies,” Seeburger explains. “When we are in the zone, these networks become desynchronized.”

The results suggest that 20-second patterns could help predict whether or not a person maintains attention, and could provide key insights to researchers developing tools and techniques that help us focus deeply.

The big picture

Although the direct relationship between behavior and brain activity is still unknown, these 20-second brain fluctuation patterns are observed universally and across species.

“If you put someone in a scanner and their mind wanders, you see these fluctuations. You can find these quasi-periodic patterns in rodents. You can find it in primates,” says Schumacher. “There is something fundamental about this brain network activity.”

“I think this answers a really fundamental question about the relationship between behavior and brain activity,” he adds.

“Understanding how these brain networks work together and influence behavior could lead to new therapies to help people organize their brain networks in the most effective way.”

And while this simple task doesn’t allow for the study of complex behaviors, the study could serve as a springboard to move on to more complex behaviors and states of focus.

“Next, I would like to study sustained attention in a more naturalistic way,” says Seeburger. “I hope we can deepen the understanding of attention and help people better manage their ability to control, maintain and increase it.”

About this attention and current research in neuroscience

Author: Jess Hunt-Ralston
Source: Georgia Institute of Technology
Contact: Jess Hunt-Ralston – Georgia Institute of Technology
Picture: Image is credited to Neuroscience News

Original research: Free access.
“Time-varying functional connectivity predicts fluctuations in sustained attention during a serial tapping task” by Dolly T. Seeburger et al. Cognitive, affective and behavioral neuroscience


Time-varying functional connectivity predicts fluctuations in sustained attention during a serial tapping task

The mechanisms by which large-scale brain networks contribute to sustained attention are unknown. Attention fluctuates from moment to moment, and this continuous change is consistent with dynamic changes in functional connectivity between brain networks involved in the internal and external distribution of attention.

In this study, we investigated how brain network activity varied across different levels of attentional focus (i.e., “zones”).

Participants performed a finger tapping task and, guided by previous research, in-zone performance or state was identified by low variability in reaction time and out-of-zone as the reverse. In-zone sessions tend to occur earlier in the session than out-of-zone blocks. This is not surprising given how attention fluctuates over time.

Using a novel time-varying functional connectivity method called quasi-periodic pattern analysis (i.e., reliable low-frequency fluctuations at the network level), we found that activity between the network in default mode (DMN) and the task positive network (TPN) is significantly more anti-correlated in in-zone states than in out-of-zone states.

Furthermore, it is the frontoparietal control network (FPCN) switch that differentiates the two zone states. Activity in the dorsal attention network (DAN) and DMN was desynchronized in the two area states.

During out-of-area periods, the FPCN synchronized with the DMN, while during in-area periods, the FPCN shifted to synchronization with the DAN. In contrast, the ventral attention network (VAN) synchronized more closely with the DMN during in-zone periods than during out-of-zone periods.

These results demonstrate that time-varying functional connectivity of low-frequency fluctuations across different brain networks varies with fluctuations in sustained attention or other processes that change over time.

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