Deep EEG source localization via EMD-based fMRI high spatial frequency.
Brain imaging with a high-spatiotemporal resolution is crucial for accurate brain-function mapping. Electroencephalography (EEG) and functional Magnetic Resonance Imaging (fMRI) are two popular neuroimaging modalities with complementary features that record brain function with high temporal and spat...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2024-01-01
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| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0299284 |
| _version_ | 1797266364860203008 |
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| author | Narges Moradi Bradley G Goodyear Roberto C Sotero |
| author_facet | Narges Moradi Bradley G Goodyear Roberto C Sotero |
| author_sort | Narges Moradi |
| collection | DOAJ |
| description | Brain imaging with a high-spatiotemporal resolution is crucial for accurate brain-function mapping. Electroencephalography (EEG) and functional Magnetic Resonance Imaging (fMRI) are two popular neuroimaging modalities with complementary features that record brain function with high temporal and spatial resolution, respectively. One popular non-invasive way to obtain data with both high spatial and temporal resolutions is to combine the fMRI activation map and EEG data to improve the spatial resolution of the EEG source localization. However, using the whole fMRI map may cause spurious results for the EEG source localization, especially for deep brain regions. Considering the head's conductivity, deep regions' sources with low activity are unlikely to be detected by the EEG electrodes at the scalp. In this study, we use fMRI's high spatial-frequency component to identify the local high-intensity activations that are most likely to be captured by the EEG. The 3D Empirical Mode Decomposition (3D-EMD), a data-driven method, is used to decompose the fMRI map into its spatial-frequency components. Different validation measurements for EEG source localization show improved performance for the EEG inverse-modeling informed by the fMRI's high-frequency spatial component compared to the fMRI-informed EEG source-localization methods. The level of improvement varies depending on the voxels' intensity and their distribution. Our experimental results also support this conclusion. |
| first_indexed | 2024-04-25T00:59:31Z |
| format | Article |
| id | doaj.art-9ae8e3287f5b4cbd8ea9f33464832dbf |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-04-25T00:59:31Z |
| publishDate | 2024-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-9ae8e3287f5b4cbd8ea9f33464832dbf2024-03-11T05:32:11ZengPublic Library of Science (PLoS)PLoS ONE1932-62032024-01-01193e029928410.1371/journal.pone.0299284Deep EEG source localization via EMD-based fMRI high spatial frequency.Narges MoradiBradley G GoodyearRoberto C SoteroBrain imaging with a high-spatiotemporal resolution is crucial for accurate brain-function mapping. Electroencephalography (EEG) and functional Magnetic Resonance Imaging (fMRI) are two popular neuroimaging modalities with complementary features that record brain function with high temporal and spatial resolution, respectively. One popular non-invasive way to obtain data with both high spatial and temporal resolutions is to combine the fMRI activation map and EEG data to improve the spatial resolution of the EEG source localization. However, using the whole fMRI map may cause spurious results for the EEG source localization, especially for deep brain regions. Considering the head's conductivity, deep regions' sources with low activity are unlikely to be detected by the EEG electrodes at the scalp. In this study, we use fMRI's high spatial-frequency component to identify the local high-intensity activations that are most likely to be captured by the EEG. The 3D Empirical Mode Decomposition (3D-EMD), a data-driven method, is used to decompose the fMRI map into its spatial-frequency components. Different validation measurements for EEG source localization show improved performance for the EEG inverse-modeling informed by the fMRI's high-frequency spatial component compared to the fMRI-informed EEG source-localization methods. The level of improvement varies depending on the voxels' intensity and their distribution. Our experimental results also support this conclusion.https://doi.org/10.1371/journal.pone.0299284 |
| spellingShingle | Narges Moradi Bradley G Goodyear Roberto C Sotero Deep EEG source localization via EMD-based fMRI high spatial frequency. PLoS ONE |
| title | Deep EEG source localization via EMD-based fMRI high spatial frequency. |
| title_full | Deep EEG source localization via EMD-based fMRI high spatial frequency. |
| title_fullStr | Deep EEG source localization via EMD-based fMRI high spatial frequency. |
| title_full_unstemmed | Deep EEG source localization via EMD-based fMRI high spatial frequency. |
| title_short | Deep EEG source localization via EMD-based fMRI high spatial frequency. |
| title_sort | deep eeg source localization via emd based fmri high spatial frequency |
| url | https://doi.org/10.1371/journal.pone.0299284 |
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