Studying time-resolved functional connectivity via communication theory: on the complementary nature of phase synchronization and sliding window Pearson correlation.

Time-resolved functional connectivity (trFC) assesses the time-resolved coupling between brain regions using functional magnetic resonance imaging (fMRI) data. This study aims to compare two techniques used to estimate trFC, to investigate their similarities and differences when applied to fMRI data. These techniques are the sliding window Pearson correlation (SWPC), an amplitude-based approach, and phase synchronization (PS), a phase-based technique. To accomplish our objective, we used resting-state fMRI data from the Human Connectome Project (HCP) with 827 subjects (repetition time: 0.7s) and the Function Biomedical Informatics Research Network (fBIRN) with 311 subjects (repetition time: 2s), which included 151 schizophrenia patients and 160 controls. Our simulations reveal distinct strengths in two connectivity methods: SWPC captures high-magnitude, low-frequency connectivity, while PS detects low-magnitude, high-frequency connectivity. Stronger correlations between SWPC and PS align with pronounced fMRI oscillations. For fMRI data, higher correlations between SWPC and PS occur with matched frequencies and smaller SWPC window sizes (~30s), but larger windows (~88s) sacrifice clinically relevant information. Both methods identify a schizophrenia-associated brain network state but show different patterns: SWPC highlights low anti-correlations between visual, subcortical, auditory, and sensory-motor networks, while PS shows reduced positive synchronization among these networks. In sum, our findings underscore the complementary nature of SWPC and PS, elucidating their respective strengths and limitations without implying the superiority of one over the other.

Phase and amplitude, two sides of functional connectivity.

The dynamics of the human brain can be captured by estimating time-resolved functional network connectivity (trFNC). The most used method for estimating trFNC is sliding window Pearson correlation (SWPC). Methods based on instantaneous phase synchrony, which uses phase information for estimating trFNC are being increasingly used. These two approaches are similar under specific assumptions. Prior works have focused on which of these approaches is the best. Some works argue that SWPC can capture amplitude information and therefore we believe that instantaneous phase synchrony methods and SWPC capture different aspects of connectivity since phase synchrony methods work with the phase of the signal. Here we show that these two approaches result in different time-resolved information and therefore should be viewed as complimentary views of connectivity.