Electronic Thesis and Dissertation Repository

Degree

Master of Science

Program

Neuroscience

Supervisor

Dr. Stefan Everling

Abstract

Resting-state functional magnetic resonance imaging (rs-fMRI) is widely used to explore functional connectivity (FC) between brain regions across neurological and psychiatric diseases. However, the neural basis of spontaneous low frequency blood-oxygen level dependent (BOLD) fluctuations is poorly understood.

Here, we acquired rs-fMRI data in macaque monkeys together with simultaneous recordings of local field potentials (LFPs) in prefrontal cortex area 9/46d. We first evaluated the correlation between LFPs (1-100 Hz) and BOLD signals and found unique frequency power correlates of positive and negative FC. Anti-correlation of high and low power envelopes indicated that ongoing cross-frequency interactions are a neural correlate of FC. On the other hand, seed-based analysis of the BOLD signal from the vicinity of electrode revealed the same spatial topology when using the power envelopes of high frequency bands of LFPs in the regression analysis.

Variations of the canonical hemodynamic response function (HRF) in distinct cortical areas were also investigated to find the optimal HRF that can best fit in model analysis and estimate the BOLD response. While we found the optimal HRF that yields the highest correlation, the HRF shape was consistent within subjects and between brain regions.

Our results suggest that intrinsic connectivity networks may be specifically driven by unique LFP profiles and these profiles contribute differently to BOLD FC. This study provides insight into the neural correlates of spontaneous BOLD FC at rest.


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