Context-dependent PSIICOS: A novel framework for functional connectivity estimation accounting for task-related power
Daria Kleeva1, Alexei Ossadtchi2
1Center for Bioelectric Interfaces, Higher School of Economics, Moscow, Russia.
Neuroimage
|May 30, 2025
Summary
Context-Dependent PSIICOS (CD-PSIICOS) enhances functional connectivity analysis by reducing spatial leakage artifacts in MEG/EEG data. This novel method improves the detection and stability of brain networks, especially in theta and gamma bands.
Area of Science:
- Neuroimaging
- Computational Neuroscience
- Signal Processing
Background:
- Functional connectivity (FC) analysis using MEG/EEG is susceptible to spatial leakage and power modulation artifacts.
- Existing methods like PSIICOS suppress leakage but may not adapt to dynamic brain activity.
Purpose of the Study:
- Introduce Context-Dependent PSIICOS (CD-PSIICOS), a novel framework to improve FC estimation.
- Enhance artifact suppression and preserve true interactions in neuroimaging data.
Main Methods:
- CD-PSIICOS incorporates task-specific cortical power distributions into the projection operator.
- Dynamically adjusts projections to suppress spatial leakage while preserving zero-phase interactions.
- Validated using realistic simulations and multi-subject MEG data.
Main Results:
- CD-PSIICOS outperforms original PSIICOS in artifact suppression at lower projection ranks.
- Achieves robust detection of functional networks in theta and gamma bands.
- Requires lower projection ranks for optimal performance, enhancing sensitivity and stability.
Conclusions:
- CD-PSIICOS offers a more accurate and stable method for functional connectivity analysis.
- Facilitates the reconstruction of physiologically relevant brain networks.
- Represents a significant advancement in non-invasive neuroimaging analysis.
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