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Tuesday, 30 October 2018
The study used 99 healthy adults and compared patterns of fatty acid nutrients found in blood samples, functional MRI data that measured the efficiency of brain networks, and results of a general intelligence test. Their goal was to “understand how nutrition might be used to support cognitive performance and to study the ways in which nutrition may influence the functional organisation of the human brain. This is important because if we want to develop nutritional interventions that are effective at enhancing cognitive performance, we need to understand the ways that these nutrients influence brain function."- Marta Zamroziewicz, a recent Ph.D. graduate of the neuroscience program at Illinois and lead author of the study.
The researchers found that general intelligence was associated with the brain's dorsal attention network, which plays a central role in attention-demanding tasks and everyday problem solving. In particular, the researchers found that general intelligence was associated with how efficiently the dorsal attention network is functionally organized used a measure called small-world propensity, which describes how well the neural network is connected within locally clustered regions as well as across globally integrated systems.
In turn, they found that those with higher levels of MUFAs in their blood had greater small-world propensity in their dorsal attention network. Taken together with an observed correlation between higher levels of MUFAs and greater general intelligence, these findings suggest a pathway by which MUFAs affect cognition.
Researchers from the project hope these findings will guide further research into how nutrition affects cognition and intelligence. In particular, the next step is to run an interventional study over time to see whether long-term MUFA intake influences brain network organization and intelligence.
Source: Marta K. Zamroziewicz, M. Tanveer Talukdar, Chris E. Zwilling, Aron K. Barbey. Nutritional status, brain network organization, and general intelligence. NeuroImage, 2017; 161: 241 DOI: 10.1016/j.neuroimage.2017.08.043