QPPLab: A generally applicable software package for detecting, analyzing, and visualizing large-scale quasiperiodic...

Area of Science:

• Neuroscience
• Computational Neuroscience
• Brain Dynamics

Background:

• Quasi-periodic patterns (QPPs) are significant spatiotemporal dynamics in functional neuroimaging data.
• QPPs are associated with neural processes like attention, arousal, and cognitive function.
• Current QPP analysis tools are hindered by study-specific parameters and complex workflows.

Purpose of the Study:

• To introduce QPPLab, an open-source MATLAB toolbox for QPP detection, analysis, and visualization.
• To provide researchers with a user-friendly and efficient tool for studying QPPs in fMRI data.
• To overcome limitations of existing QPP analysis methods.

Main Methods:

• QPPLab utilizes correlation-based iterative algorithms for QPP detection.
• The toolbox supports customizable parameter settings and automated workflows.
• It offers different detection modes (fast and robust) with varying processing times.

Main Results:

• QPPLab generates spatiotemporal QPP templates, sliding correlation time courses, and functional connectivity maps.
• The fast detection mode is 4-6 times faster than the robust mode.
• The toolbox simplifies manual parameter adjustments for QPP analysis.

Conclusions:

• QPPLab enhances the efficiency of studying QPPs across diverse fMRI datasets and species.
• The open-source toolbox facilitates deeper understanding of intrinsic brain dynamics.
• Researchers can now more readily investigate the role of QPPs in cognitive functions.