Date of Award
Open Access Thesis
Functional magnetic resonance imaging (fMRI) is a neuroimaging technique that provides insight into brain function and activity. Network models of fMRI signals can reveal functional connectivity related to certain brain disorders, such as post-stroke aphasia. This thesis aims to identify the functional connections that distinguish anomic and Broca’s aphasia by comparing the resting-state fMRI from the patients with these two types of aphasia. The network-based statistic (NBS) approach is used to detect such connections. After the analytic pipeline is applied to the fMRI data, the NBS approach identifies a distinct subnetwork between the two types of aphasia, which involves the premotor, primary motor, and prime sensory cortex. By examining the properties of this subnetwork through complex network measures, we found that the regions in the premotor cortex and primary motor cortex play an important role in information flow and overall communication efficiency.
Zhao, X.(2020). Network-Based Statistical Analysis of Functional Magnetic Resonance Imaging Data From Aphasia Patients. (Master's thesis). Retrieved from https://scholarcommons.sc.edu/etd/5985
Available for download on Sunday, August 15, 2021