Effects of quasi-periodic pattern regression on bold signals correlated with infraslow and higher frequency electrophysiology

Abstract

Functional MRI (fMRI) have provided information on networks, disorders, and cognitive performance of the brain. Recent studies have focused on fMRI during resting state (rs-fMRI) without any explicit tasks. To supplement BOLD signals, resting-state fMRI studies have been paired with simultaneous recording of electrophysiology data, a method to provide a direct measure of neural activity. Studies have focused on analyzing infraslow frequencies (<1Hz) to understand large-scale spontaneous spatial and temporal fluctuations. Dynamic analysis of infraslow frequencies has shown semi-reoccurring BOLD patterns, which have been defined as quasi-periodic patterns (QPP). This study expands on the previously acquired data using simultaneous fMRI and local field potential (LFP) recordings to understand effects of removing quasi-periodic patterns from the BOLD signal. Furthermore, this study focuses on the impact of quasi-periodic patterns regression on the relationship between BOLD and LFP at multiple frequency bands (infraslow and frequencies between 1 and 100Hz). Results show that the most significant BOLD correlation before QPP regression occurs at the infraslow LFP band. After QPP regression, the stronger BOLD correlation shifts towards the higher LFP frequencies. The reduction in BOLD correlation to LFP after QPP regression suggests that infraslow and higher frequency neural activities contribute to the coordination of large-scale networks observed through quasi-periodic patterns.