Adviser: Dr. Molly Bright
Subject: Engineering
DOI: 10.21985/n2-ed9r-dt70
Jingxuan is a rising junior majoring in biomedical engineering. He has actively participated in research at NU’s Bright Lab. His research mainly focuses on BOLD-fMRI data analysis. He was awarded the joint Summer Undergraduate Research Grant (SURG) & Biomedical Engineering Department Grant in summer 2020 and was awarded the Mccormick Summer Research Grant in summer 2021.
[/et_pb_text][/et_pb_column][et_pb_column type=”3_5″ _builder_version=”3.23.3″][et_pb_text _builder_version=”3.23.3″ text_font=”Standard2|600|||||||” text_font_size=”25px”]Abstract[/et_pb_text][et_pb_text _builder_version=”3.23.3″ text_font=”Times New Roman||||||||” text_font_size=”19px” text_line_height=”1.5em”]The mapping of the human brain is one of the most challenging but important topics among the fields of research. The delicate, intertwined networks of neurons obstruct us from taking invasive measures to explore the wonders of the brain. Functional Magnetic Resonance Imaging (fMRI) is a possible non-invasive technique for studying neural activity. When neurons are activated, without an internal reserve of energy, they rely on the increased regional cerebral blood flow for increased oxygen supply which can be detected by the MRI. Therefore, instead of directly measuring neural activity, we use blood-oxygenation-level-dependent (BOLD) signals as a surrogate measure. Resting-state fMRI (rs-fMRI) utilizes the BOLD signals to study the interaction of the brain’s functional regions (functional connectivity). Studies on functional connectivity provide rich summaries of the large-scale patterns of synchronized brain activity, in other words, how different brain regions “communicate” to perform certain functions. However, variations in hemodynamic lag obscure true functional connectivity when using BOLD-fMRI. My project focuses on comparing different approaches for estimating regional hemodynamic lag for rs-fMRI scans, with breathing tasks to globally modulate BOLD signals. By comparing the different methods, I will also be able to provide further insight into the analysis of BOLD signals by accounting for the confounding hemodynamic timing differences. The analysis will allow us to have more confidence in the rs-fMRI data with respect to hemodynamic response delays and construct more accurate functional connectivity maps. The project is still ongoing.[/et_pb_text][/et_pb_column][/et_pb_row][/et_pb_section][et_pb_section fb_built=”1″ _builder_version=”3.23.3″][et_pb_row _builder_version=”3.23.3″][et_pb_column type=”4_4″ _builder_version=”3.23.3″][et_pb_code _builder_version=”3.23.3″][/et_pb_code][/et_pb_column][/et_pb_row][et_pb_row _builder_version=”3.23.3″][et_pb_column type=”4_4″ _builder_version=”3.23.3″][et_pb_code _builder_version=”3.23.3″][/et_pb_code][/et_pb_column][/et_pb_row][/et_pb_section]