Individual slow wave events give rise to macroscopic fMRI signatures and drive the strength of the BOLD signal in human resting-state EEG-fMRI recordings. (30th January 2022)

• Record Type: Journal Article
• Authors: Ilhan-Bayrakcı, Merve; Cabral-Calderin, Yuranny; Bergmann, Til Ole; Tüscher, Oliver; Stroh, Albrecht
• Is Part Of: Cerebral cortex. Volume 32:Number 21(2022)
• Page Start: 4782
• Page End: 4796
• Publication Date: 2022-01-30
• Subjects: brain states -- EEG-fMRI -- slow oscillations -- slow wave events -- thalamocortical networks; Cerebral cortex -- Periodicals; Brain -- Periodicals; 612.825
• DOI: 10.1093/cercor/bhab516
• Languages: English
• ISSNs: 1047-3211

Abstract

Abstract: The slow wave state is a general state of quiescence interrupted by sudden bursts of activity or so-called slow wave events (SWEs). Recently, the relationship between SWEs and blood oxygen level–dependent (BOLD) functional magnetic resonance imaging (fMRI) signals was assessed in rodent models which revealed cortex-wide BOLD activation. However, it remains unclear which macroscopic signature corresponds to these specific neurophysiological events in the human brain. Therefore, we analyzed simultaneous electroencephalographic (EEG)-fMRI data during human non-REM sleep. SWEs individually detected in the EEG data were used as predictors in event-related fMRI analyses to examine the relationship between SWEs and fMRI signals. For all 10 subjects we identified significant changes in BOLD activity associated with SWEs covering substantial parts of the gray matter. As demonstrated in rodents, we observed a direct relation of a neurophysiological event to specific BOLD activation patterns. We found a correlation between the number of SWEs and the spatial extent of these BOLD activation patterns and discovered that the amplitude of the BOLD response strongly depends on the SWE amplitude. As altered SWE propagation has recently been found in neuropsychiatric diseases, it is critical to reveal the brain's physiological slow wave state networks to potentially establish early imaging biomarkers for various diseases long before disease onset.