Summary: New research finds that better cognitive performance is linked to greater similarity between brain connectivity patterns during rest and during tasks.
Source: SFN.
A brain at rest differs from a brain engaged in a task. How large that difference is appears to be related to a person’s cognitive ability. New research published August 17 in The Journal of Neuroscience reports that greater similarity between resting-state and task-related brain connectivity is associated with stronger mental performance.
Study author Michael Cole of Rutgers University suggests that general cognitive ability may result from well-tuned updates of large-scale brain networks. “The results also suggest that if we can figure out how to better tune these networks, we can possibly influence cognitive ability generally,” Cole said. This study explores how the brain’s intrinsic organization—its resting-state network—reconfigures when a person switches to performing different cognitive tasks, and whether the ease of that reconfiguration predicts task performance.
Functional magnetic resonance imaging (fMRI) has shown that different cognitive tasks activate different groups of brain regions. Regions that activate together are thought to form functional networks that support specific mental operations. Even during quiet rest the brain exhibits coherent patterns of spontaneous activity known as resting-state networks. Previous work by Cole and coauthor Douglas Schultz indicated that resting and task-evoked networks share substantial similarity, prompting the hypothesis that an intrinsic, baseline network reorganizes in relatively modest ways to meet task demands. The present study tested whether smaller changes between rest and task networks correspond to better cognitive performance.
To investigate this, the researchers analyzed fMRI data from the Human Connectome Project collected by teams at Washington University in St. Louis and the University of Minnesota. One hundred healthy adults underwent scanning both while resting quietly and while performing a battery of cognitive tests that included language, reasoning, and memory tasks. The researchers compared each participant’s resting-state connectivity pattern with the connectivity patterns observed during each task. They quantified how similar each task-specific network was to the participant’s resting-state network.
When the researchers related these similarity measures to task performance, a clear pattern emerged: individuals who performed better across the cognitive tasks tended to have task networks that were more similar to their resting-state network. The team also derived a composite, generalized task network by combining the connectivity patterns from the different cognitive tasks. Participants whose resting-state network more closely matched this generalized task pattern scored higher across the tasks. In other words, high performers appeared to have intrinsic resting-state networks that were already well-suited to switch to a variety of tasks, requiring relatively small reconfigurations to meet task demands.
John Dylan Haynes, a neuroscientist at the Bernstein Center for Computational Neuroscience in Berlin who was not involved in the study, commented on the findings: “People’s performance on various cognitive tasks is better the fewer changes they have to make to their brain connectivity. The efficiency with which a brain engages in a task might be a predictor of intelligence.” This interpretation frames cognitive efficiency not simply as the activation of specific regions, but as how readily an intrinsic network can be adapted for multiple cognitive challenges.
These results add to growing evidence that individual differences in cognitive ability can be linked to global patterns of brain organization and flexibility. If resting-state networks are already configured close to the patterns needed for many tasks, the brain can operate with smaller, more efficient shifts in connectivity. That efficiency may underlie better performance across diverse mental abilities such as reasoning, language processing, and memory.
The researchers plan to follow up with studies that investigate whether training or targeted interventions can change the intrinsic network organization and its ability to reconfigure, and whether such changes lead to measurable improvements in cognitive performance. Understanding how and when brain networks can be tuned could inform strategies for cognitive training and rehabilitation.
Source: Emily Ortman – SFN
Image Source: This NeuroscienceNews.com image is in the public domain.
Original Research: The study will appear in Journal of Neuroscience.
SFN. “General Cognitive Ability May Be Result of Well Tuned Brain Network Updates.” NeuroscienceNews. Published August 17, 2016.