Fidelity of Spatiotemporal Patterns of Brain Activity Across Sampling Rate, Scan Duration, and Frequency Content

Area of Science:

• Neuroimaging
• Cognitive Neuroscience
• Network Science

Background:

• Intrinsic brain activity manifests as large-scale spatiotemporal patterns crucial for cognition.
• Quasi-periodic patterns (QPPs) and complex principal component analysis (cPCA) are established methods for analyzing resting-state functional magnetic resonance imaging (rs-fMRI) data.
• The reliability of QPPs and cPCA can be influenced by acquisition parameters like scan duration, repetition time (TR), and frequency band.

Purpose of the Study:

• To systematically evaluate how scan duration, TR, and frequency band selection impact the stability and reliability of QPP- and cPCA-derived functional connectivity patterns.
• To compare the performance of QPPs and cPCA under varying methodological conditions across multiple rs-fMRI datasets.
• To provide guidance on optimizing parameter choices for dynamic functional connectivity analysis.

Main Methods:

• Analysis of five independent rs-fMRI datasets.
• Systematic evaluation of scan length effects on pattern reliability.
• Exploration of repetition time (TR) effects on spatiotemporal patterns.
• Comparison of different frequency bands (Slow-5, Slow-4, infraslow) for capturing network dynamics.

Main Results:

• Both QPPs and cPCA successfully detect intrinsic network activity, with reliability varying based on acquisition parameters.
• QPPs demonstrate greater stability in shorter scans, suitable for individual analyses.
• cPCA offers a broader representation of phase-coherent fluctuations but exhibits higher between-subject variability and benefits from longer, group-level scans.
• Frequency band selection significantly alters pattern structure: Slow-5 emphasizes recurrent configurations, while Slow-4 highlights transitions between connectivity states.

Conclusions:

• Methodological choices critically influence the interpretation of dynamic functional connectivity patterns derived from QPPs and cPCA.
• QPPs offer a robust approach for individual-level analysis with shorter scan durations.
• cPCA is more suited for group-level analyses requiring longer scan times.
• Understanding the impact of acquisition parameters enhances the interpretability of spatiotemporal patterns in neuroimaging research.