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Title: A Graphical Model Approach to Study the Neural Network during Narrative Comprehension
Authors: Zou, Jiawei
Advisors: Liu, Han
Department: Operations Research and Financial Engineering
Class Year: 2016
Abstract: The default mode network (DMN) is a network of functionally connected regions that has been thought to activate when the brain is not focused on performing external tasks. However, some researchers have proposed that the DMN also plays an active role in the processing of external stimuli. We addressed this debate by using graphical model instead of the traditionally used pairwise correlation method to examine fMRI data collected during narrative comprehension tasks. We showed that graphical model is an effective tool for studying correlational relationships in the neural network. We also found inter-subject approaches to be better than the within-subject approach in isolating the effect of stimulus-induced neural responses in the brain. Finally, we discovered the presence of hub regions in the graphs that correspond approximately to the locations of the default mode network. We also found that scrambled audio information elicited lower levels of network-wide correlation than intact story. These findings lend support to the proposition that the DMN participates in narrative comprehension.
Extent: 83 pages
Type of Material: Princeton University Senior Theses
Language: en_US
Appears in Collections:Operations Research and Financial Engineering, 2000-2016

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