Biomedical Engineering and Bioengineering Commons^™

Effect Of Scan Time On Resting State Parameters, Dhruti Patel

Theses

In the past decade the interest in studying the spontaneous low-frequency fluctuations (LFF) in a resting-state brain has steadily grown. By measuring LFF (< 0.08 Hz) in blood-oxygen-level-dependent (BOLD) signals, resting-state functional magnetic resonance imaging (rs-fMRI) has proven to be a powerful tool in exploring brain network connectivity and functionality. Rs-fMRI data can be used to organize the brain into resting state networks (RSNs). In this thesis, rs-fMRI data are used to determine the minimum data acquisition time necessary to detect local intrinsic brain activity as a function of both the amplitude of low frequency fluctuations (ALFF) and the fractional amplitude of low frequency fluctuations (fALFF) in BOLD signals in healthy subjects. The data are obtained from 22 healthy subjects to use as a baseline for future rs-fMRI analysis. Voxel-wise analysis is performed on the whole brain, gray matter volume, and two previously established RSNs: the default mode network (DMN) and the visual system network, for all the subjects in this study.

Pearson’s correlation coefficients (r-values) are calculated from each subject. The entire time series for one subject is divided into 31 subsections and the r-values are calculated between each consecutive subsection in a subject. In total, there are 30 r- values. To better understand what the results mean across subjects and within subjects Fisher transformations are applied to the 30 calculated r-values for each subject to get a normal z-distribution. The mean across 22 subjects’ z-values is …