Historically, cognitive neuroscience has mapped cognitive processes onto specific brain areas. However, it has more recently become evident that the brain processes information in a distributed manner, with networks of brain regions working together to process cognitive information. We recently published an article in Nature Communications addressing this issue, investigating how cognitive information in one brain region is transferred to another brain region through routes described by intrinsic network architecture.
Briefly, our results suggest that the human brain’s intrinsic network architecture (i.e., the network architecture extracted while a person is resting in a functional magnetic resonance imaging scanner) forms the foundation upon which distributed cognitive processing occurs. Using the brain’s intrinsic network architecture, we could predict how patterns of activity related to active cognitive processing are propagated between brain regions and networks. We first validated this principle using a computational model, where we simulated a resting brain and showed how patterns of intrinsic connectivity can predict how information is transferred during simulated cognitive tasks. We then collected empirical fMRI data while human subjects performed an array of cognitive tasks, showing that we could predict cognitive information in distributed brain areas using their intrinsic (resting) network architecture. In follow-up analyses, we found that cognitive control networks (brain networks with hub-like properties) played a disproportionate role in transferring information.
The resting brain has already been shown to be able to predict how brain regions will activate during tasks (Tavor et al., 2016; Cole et al., 2016). We built on these findings to show that patterns of connectivity between brain regions describe the channels of activity flow between those regions that carry cognitive information. This allowed us to infer that information in distributed parts of the brain are related to each other through an underlying, intrinsic network architecture. We hope these findings will spur new investigations into computational roles that intrinsic brain networks play in information communication and transformation.
Here’s a link to the article: http://rdcu.be/wQ1M
Ito, T., Kulkarni, K. R., Schultz, D. H., Mill, R. D., Chen, R. H., Solomyak, L. I., & Cole, M. W. (2017). Cognitive task information is transferred between brain regions via resting-state network topology. Nature Communications. https://doi.org/10.1038/s41467-017-01000-w
Tavor, I., Jones, O. P., Mars, R. B., Smith, S. M., Behrens, T. E., & Jbabdi, S. (2016). Task-free MRI predicts individual differences in brain activity during task performance. Science, 352(6282), 1773–1776. https://doi.org/10.1126/science.aad8127
Cole, M. W., Ito, T., Bassett, D. S., & Schultz, D. H. (2016). Activity flow over resting-state networks shapes cognitive task activations. Nature Neuroscience. https://doi.org/10.1038/nn.4406