Phase and amplitude, two sides of functional connectivity

Area of Science:

• Neuroscience
• Computational Neuroscience
• Brain Network Analysis

Background:

• Estimating time-resolved functional network connectivity (trFNC) is crucial for understanding human brain dynamics.
• Sliding window Pearson correlation (SWPC) is the predominant method for trFNC estimation.
• Instantaneous phase synchrony methods are emerging as an alternative approach for trFNC analysis.

Purpose of the Study:

• To investigate the relationship between SWPC and instantaneous phase synchrony methods for trFNC estimation.
• To determine if these methods capture distinct aspects of brain connectivity.
• To highlight the complementary nature of these two approaches.

Main Methods:

• Comparison of sliding window Pearson correlation (SWPC) with instantaneous phase synchrony methods.
• Analysis of time-resolved functional network connectivity (trFNC) using both approaches.
• Evaluation of the information captured by phase synchrony versus amplitude-based methods.

Main Results:

• SWPC and instantaneous phase synchrony methods yield different time-resolved connectivity information.
• While similar under specific assumptions, these methods capture distinct aspects of brain network dynamics.
• Phase synchrony methods focus on signal phase, whereas SWPC incorporates amplitude information.

Conclusions:

• Time-resolved functional network connectivity (trFNC) can be effectively estimated using both SWPC and instantaneous phase synchrony.
• These methods are not mutually exclusive but rather provide complementary insights into brain connectivity.
• Viewing these approaches as complementary enhances our understanding of dynamic brain networks.