Context-dependent PSIICOS: A novel framework for functional connectivity estimation accounting for task-related power leakage
Functional connectivity (FC) analysis using non-invasive neuroimaging methods, such as MEG and EEG, is often confounded by artifacts from spatial leakage and task-related power modulations. To address these limitations, we present Context-Dependent PSIICOS (CD-PSIICOS), a novel framework that improv...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-08-01
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| Series: | NeuroImage |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S105381192500271X |
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| author | Daria Kleeva Alexei Ossadtchi |
| author_facet | Daria Kleeva Alexei Ossadtchi |
| author_sort | Daria Kleeva |
| collection | DOAJ |
| description | Functional connectivity (FC) analysis using non-invasive neuroimaging methods, such as MEG and EEG, is often confounded by artifacts from spatial leakage and task-related power modulations. To address these limitations, we present Context-Dependent PSIICOS (CD-PSIICOS), a novel framework that improves the estimation of FC by incorporating task-specific cortical power distributions into the projection operator applied to the vectorized sensor-space cross-spectrum. Unlike the original PSIICOS (Phase Shift Invariant Imaging of Coherent Sources) approach, designed to suppress spatial leakage from all the sources, CD-PSIICOS dynamically adjusts the projection based on the active source distribution, enabling more accurate suppression of spatial leakage while preserving true zero-phase interactions. We validated CD-PSIICOS using realistic simulations and a multi-subject MEG dataset. The results demonstrate that CD-PSIICOS outperforms the original PSIICOS in suppressing artifacts at the lower projection ranks, maintaining robust detection of functional networks across theta and gamma frequency bands. By requiring lower projection ranks for optimal performance, CD-PSIICOS facilitates the reconstruction of physiologically relevant networks with improved sensitivity and stability. |
| format | Article |
| id | doaj-art-686f56b355334a03972ff6a8c2d40fc1 |
| institution | DOAJ |
| issn | 1095-9572 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | Elsevier |
| record_format | Article |
| series | NeuroImage |
| spelling | doaj-art-686f56b355334a03972ff6a8c2d40fc12025-08-20T03:22:00ZengElsevierNeuroImage1095-95722025-08-0131612126810.1016/j.neuroimage.2025.121268Context-dependent PSIICOS: A novel framework for functional connectivity estimation accounting for task-related power leakageDaria Kleeva0Alexei Ossadtchi1Center for Bioelectric Interfaces, Higher School of Economics, Moscow, RussiaCenter for Bioelectric Interfaces, Higher School of Economics, Moscow, Russia; AIRI, Artificial Intelligence Research Institute, Moscow, Russia; LLC ”Life Improvement by Future Technologies Center”, Russia; Correspondence to: Center for Bioelectric Interfaces, Higher School of Economics, Moscow, Krivokolenny pereulok 3a, room 316, Russia.Functional connectivity (FC) analysis using non-invasive neuroimaging methods, such as MEG and EEG, is often confounded by artifacts from spatial leakage and task-related power modulations. To address these limitations, we present Context-Dependent PSIICOS (CD-PSIICOS), a novel framework that improves the estimation of FC by incorporating task-specific cortical power distributions into the projection operator applied to the vectorized sensor-space cross-spectrum. Unlike the original PSIICOS (Phase Shift Invariant Imaging of Coherent Sources) approach, designed to suppress spatial leakage from all the sources, CD-PSIICOS dynamically adjusts the projection based on the active source distribution, enabling more accurate suppression of spatial leakage while preserving true zero-phase interactions. We validated CD-PSIICOS using realistic simulations and a multi-subject MEG dataset. The results demonstrate that CD-PSIICOS outperforms the original PSIICOS in suppressing artifacts at the lower projection ranks, maintaining robust detection of functional networks across theta and gamma frequency bands. By requiring lower projection ranks for optimal performance, CD-PSIICOS facilitates the reconstruction of physiologically relevant networks with improved sensitivity and stability.http://www.sciencedirect.com/science/article/pii/S105381192500271XFunctional connectivityMEGEEGSpatial leakagePhase synchronyVolume conduction |
| spellingShingle | Daria Kleeva Alexei Ossadtchi Context-dependent PSIICOS: A novel framework for functional connectivity estimation accounting for task-related power leakage NeuroImage Functional connectivity MEG EEG Spatial leakage Phase synchrony Volume conduction |
| title | Context-dependent PSIICOS: A novel framework for functional connectivity estimation accounting for task-related power leakage |
| title_full | Context-dependent PSIICOS: A novel framework for functional connectivity estimation accounting for task-related power leakage |
| title_fullStr | Context-dependent PSIICOS: A novel framework for functional connectivity estimation accounting for task-related power leakage |
| title_full_unstemmed | Context-dependent PSIICOS: A novel framework for functional connectivity estimation accounting for task-related power leakage |
| title_short | Context-dependent PSIICOS: A novel framework for functional connectivity estimation accounting for task-related power leakage |
| title_sort | context dependent psiicos a novel framework for functional connectivity estimation accounting for task related power leakage |
| topic | Functional connectivity MEG EEG Spatial leakage Phase synchrony Volume conduction |
| url | http://www.sciencedirect.com/science/article/pii/S105381192500271X |
| work_keys_str_mv | AT dariakleeva contextdependentpsiicosanovelframeworkforfunctionalconnectivityestimationaccountingfortaskrelatedpowerleakage AT alexeiossadtchi contextdependentpsiicosanovelframeworkforfunctionalconnectivityestimationaccountingfortaskrelatedpowerleakage |