AUTHOR=Thompson Garth J. , Pan Wen-Ju , Billings Jacob C. W. , Grooms Joshua K. , Shakil Sadia , Jaeger Dieter , Keilholz Shella D. TITLE=Phase-amplitude coupling and infraslow (<1 Hz) frequencies in the rat brain: relationship to resting state fMRI JOURNAL=Frontiers in Integrative Neuroscience VOLUME=8 YEAR=2014 URL=https://www.frontiersin.org/journals/integrative-neuroscience/articles/10.3389/fnint.2014.00041 DOI=10.3389/fnint.2014.00041 ISSN=1662-5145 ABSTRACT=

Resting state functional magnetic resonance imaging (fMRI) can identify network alterations that occur in complex psychiatric diseases and behaviors, but its interpretation is difficult because the neural basis of the infraslow BOLD fluctuations is poorly understood. Previous results link dynamic activity during the resting state to both infraslow frequencies in local field potentials (LFP) (<1 Hz) and band-limited power in higher frequency LFP (>1 Hz). To investigate the relationship between these frequencies, LFPs were recorded from rats under two anesthetics: isoflurane and dexmedetomidine. Signal phases were calculated from low-frequency LFP and compared to signal amplitudes from high-frequency LFP to determine if modulation existed between the two frequency bands (phase-amplitude coupling). Isoflurane showed significant, consistent phase-amplitude coupling at nearly all pairs of frequencies, likely due to the burst-suppression pattern of activity that it induces. However, no consistent phase-amplitude coupling was observed in rats that were anesthetized with dexmedetomidine. fMRI-LFP correlations under isoflurane using high frequency LFP were reduced when the low frequency LFP's influence was accounted for, but not vice-versa, or in any condition under dexmedetomidine. The lack of consistent phase-amplitude coupling under dexmedetomidine and lack of shared variance between high frequency and low frequency LFP as it relates to fMRI suggests that high and low frequency neural electrical signals may contribute differently, possibly even independently, to resting state fMRI. This finding suggests that researchers take care in interpreting the neural basis of resting state fMRI, as multiple dynamic factors in the underlying electrophysiology could be driving any particular observation.