Summary: A new study finds that how the brain is organized into subnetworks affects performance on both simple and complex tasks.
Source: Rice University
New research from Rice University shows that the brain’s wiring — specifically how its subnetworks are organized — influences how well people perform tasks of varying complexity.
The human brain is arranged into subnetworks, or modules, each supporting particular functions such as language, memory, attention and emotion. In this study, researchers explored how the degree of modularity — that is, how strongly these modules communicate internally versus with other modules — relates to performance on simple and complex tasks.
“Think of your brain as a university,” said Simon Fischer-Baum, an assistant professor of psychology and one of the study’s authors. “Students group into dorms, clubs and teams that are densely connected inside the group but still have some connections outside. Brains are organized in similar communities: brain regions form tightly connected modules with fewer links to regions outside those modules. But people differ. Some brains show a more rigid community structure — higher modularity — while others show looser, more integrated organization — lower modularity.”
Modularity in the study was measured on a scale from 0 to 1. A value near 0 indicated low modularity, meaning brain regions were similarly likely to communicate with any other region. A value near 1 indicated high modularity, where distinct communities of regions primarily communicate within their own group.
The research team recruited 52 healthy young adults (16 men, 36 women) aged 18 to 26. Each participant underwent 21 minutes of resting-state functional magnetic resonance imaging (fMRI), a technique that detects changes in blood oxygenation tied to neural activity. The researchers identified pairs of brain areas whose activity rose and fell together during the scan — a sign those areas are functionally connected — and used that information to map each participant’s brain network and estimate its modularity.
After the imaging session, participants completed a variety of behavioral tasks. These included simple tasks, such as responding to the direction of an arrow when attention had already been cued to its location, and more complex tasks that combined working memory demands with concurrent arithmetic problems.
Results showed a clear trade-off. Participants whose brains exhibited higher modularity performed better on the simple tasks. In the cueing task that measured reaction time to arrows, individuals with higher modularity showed a larger benefit when they already knew where the target would appear: a reaction time advantage averaging 58 milliseconds, compared with a 34 millisecond advantage for those with lower modularity.
By contrast, participants with lower-modularity brains outperformed those with higher modularity on the more complex tasks. For instance, in a memory challenge embedded within a dual-task setting, low-modularity participants correctly recalled 86 percent of items on average, whereas high-modularity participants recalled 76 percent.
Fischer-Baum noted that the magnitude of this memory difference between high- and low-modularity subgroups of healthy, highly educated young adults is similar to differences typically seen with aging: roughly comparable to the decline in working memory observed between people in their 20s and those in their 70s, according to prior research.
Randi Martin, the Elma Schneider Professor of Psychology and the study’s lead faculty author, emphasized that one strength of the work is its alignment with a general theory from co-author Michael Deem, a professor of biochemical and genetic engineering and physics and astronomy at Rice. That theory predicts that highly modular biological systems excel at simpler, faster tasks, while less modular (more integrated) systems are better suited to complex tasks that require coordination across many components. The study provides empirical evidence that this general biological principle applies to human cognition.
The findings contribute to a growing perspective in cognitive neuroscience that cognitive abilities arise from interactions across brain networks rather than isolated regions. “Other groups have found correlations between network properties and task performance,” Fischer-Baum said, “but our study shows these relationships can be understood through a broader theory of modularity in biological systems.”
Qiuhai Yue, a Rice graduate student, is the study’s lead author. Co-authors include graduate student Fengdan Ye and Aurora Ramos-Nuñez, a former research scientist in the Fischer-Baum lab now teaching at the College of Coastal Georgia. The research received funding from the T.L.L. Temple Foundation, the Center for Theoretical Biological Physics and the National Science Foundation.
Original research: The study, titled “Brain Modularity Mediates the Relation Between Task Complexity and Performance,” is scheduled to appear in the journal Cognitive Neuroscience.
Please feel free to share this summary of the research. For full details, consult the original article in Cognitive Neuroscience or contact the authors at Rice University.