Multifractal Dynamic Functional Connectivity in the Resting-State Brain

Assessing the functional connectivity (FC) of the brain has proven valuable in enhancing our understanding of brain function. Recent developments in the field demonstrated that FC fluctuates even in the resting state, which has not been taken into account by the widely applied static approaches introduced earlier. In a recent study using functional near-infrared spectroscopy (fNIRS) global dynamic functional connectivity (DFC) has also been found to fluctuate according to scale-free i.e., fractal dynamics evidencing the true multifractal (MF) nature of DFC in the human prefrontal cortex. Expanding on these findings, we performed electroencephalography (EEG) measurements in 14 regions over the whole cortex of 24 healthy, young adult subjects in eyes open (EO) and eyes closed (EC) states. We applied dynamic graph theoretical analysis to capture DFC by computing the pairwise time-dependent synchronization between brain regions and subsequently calculating the following dynamic graph topological measures: Density, Clustering Coefficient, and Efficiency. We characterized the dynamic nature of these global network metrics as well as local individual connections in the networks using focus-based multifractal time series analysis in all traditional EEG frequency bands. Global network topological measures were found fluctuating-albeit at different extent-according to true multifractal nature in all frequency bands. Moreover, the monofractal Hurst exponent was found higher during EC than EO in the alpha and beta bands. Individual connections showed a characteristic topology in their fractal properties, with higher autocorrelation owing to short-distance connections-especially those in the frontal and pre-frontal cortex-while long-distance connections linking the occipital to the frontal and pre-frontal areas expressed lower values. The same topology was found with connection-wise multifractality in all but delta band connections, where the very opposite pattern appeared. This resulted in a positive correlation between global autocorrelation and connection-wise multifractality in the higher frequency bands, while a strong anticorrelation in the delta band. The proposed analytical tools allow for capturing the fine details of functional connectivity dynamics that are evidently present in DFC, with the presented results implying that multifractality is indeed an inherent property of both global and local DFC

Baseline effects on resting-state functional connectivity

Correlations between spontaneous fluctuations in the blood oxygenation level dependent (BOLD) signal measured with functional MRI are finding increasing use as measures of functional connectivity in the brain, where differences can potentially predict cognitive performance and diagnose disease. However, the interpretation of resting-state functional connectivity changes can be complicated by the BOLD signal's dependence on both neural and vascular factors. For example, prior studies have shown that vasoactive agents that alter baseline cerebral blood flow (CBF), such as caffeine and carbon dioxide, can significantly alter the amplitude and dynamics of the task -related BOLD response. In addition, healthy inter-subject differences in the amplitude of the BOLD response to a visual task are highly correlated with baseline CBF. The purpose of this work was to determine whether resting- state BOLD measures were similarly modulated by inter- subject differences in baseline CBF or vasoactive substances. Since many diseases and pharmacological agents are known to alter the vasculature, this is an important potential confound to investigat