Determination of Dominant Frequency of Resting-State Brain Interaction within One Functional System

Abstract

Accumulating evidence has revealed that the resting-state functional connectivity (RSFC) is frequency specific and functional system dependent. Determination of dominant frequency of RSFC (RSFCdf) within a functional system, therefore, is of importance for further understanding the brain interaction and accurately assessing the RSFC within the system. Given the unique advantages over other imaging techniques, functional near-infrared spectroscopy (fNIRS) holds distinct merits for RSFCdf determination. However, an obstacle that hinders fNIRS from potential RSFCdf investigation is the interference of various global noises in fNIRS data which could bring spurious connectivity at the frequencies unrelated to spontaneous neural activity. In this study, we first quantitatively evaluated the interferences of multiple systemic physiological noises and the motion artifact by using simulated data. We then proposed a functional system dependent and frequency specific analysis method to solve the problem by introducing anatomical priori information on the functional system of interest. Both the simulated and real resting-state fNIRS experiments showed that the proposed method outperforms the traditional one by effectively eliminating the negative effects of the global noises and significantly improving the accuracy of the RSFCdf estimation. The present study thus provides an effective approach to RSFCdf determination for its further potential applications in basic and clinical neurosciences.

Functional connectivity arises from a slow rhythmic mechanism

“…This bias is surprisingly strong, yet few studies remove or otherwise compensate for it (32,35). In addition, Zhang et al (40) show that artifacts, such as head motion and systemic physiological fluctuations in pulsation, can mask the frequency structure of the "true" correlation. To address these issues, we use oxygen polarography, which is less susceptible to artifactual correlations (Figs.…”

“…Indeed, three studies report that BOLD correlations vary inversely with frequency (1/f), much like local oxygen (32)(33)(34). However, Sasai et al (35), Achard et al (36), and Cordes et al (37) report instead that oxygen correlation peaks around 0.04-0.06 Hz, with less correlation at lower frequencies-a band-limited pattern that is distinctly different from 1/f (38)(39)(40). Finally, other studies report that BOLD correlations reach a plateau at low frequencies, a result that is intermediate between 1/f and band-limited dynamics (41,42).…”

Effects of Preterm Birth on Intrinsic Fluctuations in Neonatal Cerebral Activity Examined Using Optical Imaging

“…The Δ[oxy-Hb] data were analyzed using the plug-in-based analysis software Platform for Optical Topography Analysis Tools (freely available at http://goo.gl/4Nqgo, in Japanese) based on Matlab (The MathWorks, Inc., Natick, MA, USA). We passed the data through a bandpass filter set between 0.01 and 0.08 Hz, a widely used range in fMRI-based RSFC studies although there are differences between in frequencies of RSFC used in fMRI studies and in that of NIRS studies and differences in frequencies of RSFC between different functional systems in human adult [40], [41]. We removed data corrupted by artifacts, sudden jumps and slowly-varied U- or inverted-U-shaped spikes, that originated from rapid movements, such as Moro reflexes and spontaneous smiles, which was confirmed by the automated detection based on positive correlation between Δ[oxy-Hb] and relative changes in the concentration of deoxygenated hemoglobin [42] and visual inspection.…”

Cerebral functional connectivity and Mayer waves in mice: Phenomena and separability

“…14,15 As RSFC analysis becomes an increasingly popular technique in functional neuroimaging studies in mice and humans, it is essential to determine how vasomotion and/or Mayer waves affect the low-frequency hemodynamic fluctuations used in RSFC calculations.…”