Using an array of tools to understand how the brain processes social support
Researchers Marlen Gonzalez, Shize Su and Qiannan Yu analyzed large-scale brain networks involved in the social regulation of emotion, using both statistical methods and engineering tools.
Currently, the available tools in the literature can help us look at activations in individual brain areas but not offer a holistic view of the interactions between them. This project used the functional data analysis methods in statistics to estimate and evaluate the interactions between any pair of brain areas.
Using data from a social support functional neuroimaging study, Gonzalez, Su and Yin modeled the brain as a dynamic network, with nodes referring to different brain regions and lines representing the interactions between each pair of brain areas.
However, because brain networks include a large set of data points that also change over time, computation using this method alone was not feasible. Therefore, they also used effective engineering tools to help prune data to the more important interactions between nodes, cluster these interactions into functional networks, and meaningfully model the interactions between these networks as they matched with behavior.
The project not only created a new method to analyze dynamic brain networks but also contributed to our understanding of how the brain processes the receipt of social support in a holistic and dynamic manner. This important finding also helps us understand how social support confers many health benefits to individuals.
Marlen Gonzalez is a fifth-year PhD student in the Department of Psychology. Her research focuses on how development context shapes neural endophenotypes of important constructs, such as vigilance, reward sensitivity and emotion regulation.
Shize Su is a fourth-year PhD student in the Department of Electrical and Computer Engineering. His work focuses on large-scale network modeling and analysis research.
Qiannan Yin is a third-year PhD student in the Department of Statistics. She is working on the development of new statistical models and algorithms for analyzing high-dimensional human brain data.