Blind Visualization of Task-Related Networks From Visual Oddball Simultaneous EEG-fMRI Data: Spectral or Spatiospectral Model?

Bibliographic Details
Title: Blind Visualization of Task-Related Networks From Visual Oddball Simultaneous EEG-fMRI Data: Spectral or Spatiospectral Model?
Authors: René Labounek, Zhuolin Wu, David A. Bridwell, Milan Brázdil, Jiří Jan, Igor Nestrašil
Source: Frontiers in Neurology, Vol 12 (2021)
Publisher Information: Frontiers Media S.A., 2021.
Publication Year: 2021
Collection: LCC:Neurology. Diseases of the nervous system
Subject Terms: simultaneous EEG-fMRI, task-related network visualization, spectral and spatiospectral models, visual oddball paradigm, general linear model, GLM, Neurology. Diseases of the nervous system, RC346-429
More Details: Various disease conditions can alter EEG event-related responses and fMRI-BOLD signals. We hypothesized that event-related responses and their clinical alterations are imprinted in the EEG spectral domain as event-related (spatio)spectral patterns (ERSPat). We tested four EEG-fMRI fusion models utilizing EEG power spectra fluctuations (i.e., absolute spectral model - ASM; relative spectral model - RSM; absolute spatiospectral model - ASSM; and relative spatiospectral model - RSSM) for fully automated and blind visualization of task-related neural networks. Two (spatio)spectral patterns (high δ4 band and low β1 band) demonstrated significant negative linear relationship (pFWE < 0.05) to the frequent stimulus and three patterns (two low δ2 and δ3 bands, and narrow θ1 band) demonstrated significant positive relationship (p < 0.05) to the target stimulus. These patterns were identified as ERSPats. EEG-fMRI F-map of each δ4 model showed strong engagement of insula, cuneus, precuneus, basal ganglia, sensory-motor, motor and dorsal part of fronto-parietal control (FPCN) networks with fast HRF peak and noticeable trough. ASM and RSSM emphasized spatial statistics, and the relative power amplified the relationship to the frequent stimulus. For the δ4 model, we detected a reduced HRF peak amplitude and a magnified HRF trough amplitude in the frontal part of the FPCN, default mode network (DMN) and in the frontal white matter. The frequent-related β1 patterns visualized less significant and distinct suprathreshold spatial associations. Each θ1 model showed strong involvement of lateralized left-sided sensory-motor and motor networks with simultaneous basal ganglia co-activations and reduced HRF peak and amplified HRF trough in the frontal part of the FPCN and DMN. The ASM θ1 model preserved target-related EEG-fMRI associations in the dorsal part of the FPCN. For δ4, β1, and θ1 bands, all models provided high local F-statistics in expected regions. The most robust EEG-fMRI associations were observed for ASM and RSSM.
Document Type: article
File Description: electronic resource
Language: English
ISSN: 1664-2295
Relation: https://www.frontiersin.org/articles/10.3389/fneur.2021.644874/full; https://doaj.org/toc/1664-2295
DOI: 10.3389/fneur.2021.644874
Access URL: https://doaj.org/article/d6126ed627c4422f936ad352d4aa6c97
Accession Number: edsdoj.6126ed627c4422f936ad352d4aa6c97
Database: Directory of Open Access Journals
More Details
ISSN:16642295
DOI:10.3389/fneur.2021.644874
Published in:Frontiers in Neurology
Language:English