Estimation of static and dynamic functional connectivity in resting-state fMRI using zero-frequency resonator.

Resting-state functional magnetic resonance imaging (rs-fMRI) is increasingly being used to infer the functional organization of the brain. Blood oxygen level-dependent (BOLD) features related to spontaneous neuronal activity, are yet to be clearly understood. Prior studies have hypothesized that rs-fMRI is spontaneous event-related and these events convey crucial information about the neuronal activity in estimating resting state functional connectivity (FC). Attempts have been made to extract these temporal events using a predetermined threshold. However, the thresholding methods in addition to being very sensitive to noise, may consider redundant events or exclude the low-valued inflection points. Here, we extract the event-related temporal onsets from the rs-fMRI time courses using a zero-frequency resonator (ZFR). The ZFR reflects the transient behavior of the BOLD events at its output. The conditional rate (CR) of the BOLD events occurring in a time course with respect to a seed time course is used to derive static FC. The temporal activity around the estimated events called high signal-to-noise ratio (SNR) segments are also obtained in the rs-fMRI time course and are then used to compute static and dynamic FCs during rest. Coactivation pattern (CAP) is the dynamic FC obtained using the high SNR segments driven by the ZFR. The static FC demonstrates that the ZFR-based CR distinguishes the coactivation and non-coactivation scores well in the distribution. CAP analysis demonstrated the stable and longer dwell time dominant resting state functional networks with high SNR segments driven by the ZFR. Static and dynamic FC analysis underpins that the ZFR-driven temporal onsets of BOLD events derive reliable and consistent FCs in the resting brain using a subset of the time points.

Network-wise analysis of movie-specific information in dynamic functional connectivity using COBE.

Movie watching during functional magnetic resonance imaging has emerged as a promising tool to measure the complex behavior of the brain in response to a stimulus similar to real-life situations. It has been observed that presenting a movie (sequence of events) as a stimulus will lead to a unique time course of dynamic functional connectivity related to movie stimuli that can be compared across the participants. We assume that the observed dynamic functional connectivity across subjects can be divided into following 2 components: (i) specific to a movie stimulus (depicting group-level behavior in functional connectivity) and (ii) individual-specific behavior (not necessarily common across the subjects). In this work, using the dynamic time warping distance measure, we have shown the extent of similarity between the temporal sequences of functional connectivity while the underlying movie stimuli were same and different. Further, the temporal sequence of functional connectivity patterns related to a movie is enhanced by suppressing the subject-specific components of dynamic functional connectivity using common and orthogonal basis extraction. Quantitative analysis using the F-ratio measure reveals significant differences in dynamic functional connectivity within the somatomotor network and default mode network, as well as between the occipital network and somatomotor networks.