Date of Award
Bachelor of Science (B.S.) in Biology and University Honors
Brain -- Magnetic resonance imaging, Brain mapping, Cognitive neuroscience
Task functional MRI (fMRI) has greatly impacted our understanding of brain functioning, enabling the identification of brain areas associated with particular tasks. Current methods of fMRI analysis only display regional differences in activation. We propose that there are also dynamic functional connectivity changes occurring between systems which support the performance of a task.
A recently developed method, termed connectotyping, is able to efficiently model functional brain connectivity and has the potential to track changes in brain dynamics in individuals. Our work aims to use connectotyping to reveal the progression of temporal brain connectivity patterns in task fMRI.
Twenty-four participants (12 male, mean age 24.8 years, 2.57 std. dev) performed a widely-spaced event-related fMRI word vs. pseudoword decision task. Stimuli were presented every 20 seconds. Imaging data were processed using a modified version of the Human Connectome Project pipelines and connectivity matrices were calculated per participant across time for each stimuli type. A Repeated Measures ANOVA applied on the connectotypes was used to characterize differences across time for words and pseudowords.
We found significantly different temporal connectivity patterns between the Fronto-Parietal and Cingulo Parietal Systems. These areas are involved in cognitive task control, memory retrieval, and semantic processing. Our findings support the hypothesis that there are dynamic changes in functional connectivity secondary to task execution and that such changes can be characterized using connectotyping.
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Vazquez-Trejo, Valeria; Nardos, Binyam PhD; Schlaggar, Bradley MD, PhD; Fair, Damien PA-C, PhD; and Miranda-Dominguez, Oscar PhD, "Use of Connectotyping on Task fMRI Data Reveals Dynamic Network Level Cross Talking During Task Performance" (2019). University Honors Theses. Paper 740.