EEG Source Imaging Guided by Spatiotemporal Specific fMRI: Toward an Understanding of Dynamic Cognitive Processes
Understanding the mechanism of neuroplasticity is the first step in treating neuromuscular system impairments with cognitive rehabilitation approaches. To characterize the dynamics of the neural networks and the underlying neuroplasticity of the central motor system, neuroimaging tools with high spa...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2016-01-01
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| Series: | Neural Plasticity |
| Online Access: | http://dx.doi.org/10.1155/2016/4182483 |
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| _version_ | 1832559251668598784 |
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| author | Thinh Nguyen Thomas Potter Trac Nguyen Christof Karmonik Robert Grossman Yingchun Zhang |
| author_facet | Thinh Nguyen Thomas Potter Trac Nguyen Christof Karmonik Robert Grossman Yingchun Zhang |
| author_sort | Thinh Nguyen |
| collection | DOAJ |
| description | Understanding the mechanism of neuroplasticity is the first step in treating neuromuscular system impairments with cognitive rehabilitation approaches. To characterize the dynamics of the neural networks and the underlying neuroplasticity of the central motor system, neuroimaging tools with high spatial and temporal accuracy are desirable. EEG and fMRI stand among the most popular noninvasive neuroimaging modalities with complementary features, yet achieving both high spatial and temporal accuracy remains a challenge. A novel multimodal EEG/fMRI integration method was developed in this study to achieve high spatiotemporal accuracy by employing the most probable fMRI spatial subsets to guide EEG source localization in a time-variant fashion. In comparison with the traditional fMRI constrained EEG source imaging method in a visual/motor activation task study, the proposed method demonstrated superior localization accuracy with lower variation and identified neural activity patterns that agreed well with previous studies. This spatiotemporal fMRI constrained source imaging method was then implemented in a “sequential multievent-related potential” paradigm where motor activation is evoked by emotion-related visual stimuli. Results demonstrate that the proposed method can be used as a powerful neuroimaging tool to unveil the dynamics and neural networks associated with the central motor system, providing insights into neuroplasticity modulation mechanism. |
| format | Article |
| id | doaj-art-ef13abb470fb4cdfb77c3d8c5ab8df13 |
| institution | Kabale University |
| issn | 2090-5904 1687-5443 |
| language | English |
| publishDate | 2016-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Neural Plasticity |
| spelling | doaj-art-ef13abb470fb4cdfb77c3d8c5ab8df132025-02-03T01:30:38ZengWileyNeural Plasticity2090-59041687-54432016-01-01201610.1155/2016/41824834182483EEG Source Imaging Guided by Spatiotemporal Specific fMRI: Toward an Understanding of Dynamic Cognitive ProcessesThinh Nguyen0Thomas Potter1Trac Nguyen2Christof Karmonik3Robert Grossman4Yingchun Zhang5Department of Biomedical Engineering, Cullen College of Engineering, University of Houston, Houston, TX 77204, USADepartment of Biomedical Engineering, Cullen College of Engineering, University of Houston, Houston, TX 77204, USADepartment of Biomedical Engineering, Cullen College of Engineering, University of Houston, Houston, TX 77204, USAMRI Core, Houston Methodist Research Institute, Houston, TX 77030, USADepartment of Neurosurgery, Houston Methodist Hospital and Research Institute, Houston, TX 77030, USADepartment of Biomedical Engineering, Cullen College of Engineering, University of Houston, Houston, TX 77204, USAUnderstanding the mechanism of neuroplasticity is the first step in treating neuromuscular system impairments with cognitive rehabilitation approaches. To characterize the dynamics of the neural networks and the underlying neuroplasticity of the central motor system, neuroimaging tools with high spatial and temporal accuracy are desirable. EEG and fMRI stand among the most popular noninvasive neuroimaging modalities with complementary features, yet achieving both high spatial and temporal accuracy remains a challenge. A novel multimodal EEG/fMRI integration method was developed in this study to achieve high spatiotemporal accuracy by employing the most probable fMRI spatial subsets to guide EEG source localization in a time-variant fashion. In comparison with the traditional fMRI constrained EEG source imaging method in a visual/motor activation task study, the proposed method demonstrated superior localization accuracy with lower variation and identified neural activity patterns that agreed well with previous studies. This spatiotemporal fMRI constrained source imaging method was then implemented in a “sequential multievent-related potential” paradigm where motor activation is evoked by emotion-related visual stimuli. Results demonstrate that the proposed method can be used as a powerful neuroimaging tool to unveil the dynamics and neural networks associated with the central motor system, providing insights into neuroplasticity modulation mechanism.http://dx.doi.org/10.1155/2016/4182483 |
| spellingShingle | Thinh Nguyen Thomas Potter Trac Nguyen Christof Karmonik Robert Grossman Yingchun Zhang EEG Source Imaging Guided by Spatiotemporal Specific fMRI: Toward an Understanding of Dynamic Cognitive Processes Neural Plasticity |
| title | EEG Source Imaging Guided by Spatiotemporal Specific fMRI: Toward an Understanding of Dynamic Cognitive Processes |
| title_full | EEG Source Imaging Guided by Spatiotemporal Specific fMRI: Toward an Understanding of Dynamic Cognitive Processes |
| title_fullStr | EEG Source Imaging Guided by Spatiotemporal Specific fMRI: Toward an Understanding of Dynamic Cognitive Processes |
| title_full_unstemmed | EEG Source Imaging Guided by Spatiotemporal Specific fMRI: Toward an Understanding of Dynamic Cognitive Processes |
| title_short | EEG Source Imaging Guided by Spatiotemporal Specific fMRI: Toward an Understanding of Dynamic Cognitive Processes |
| title_sort | eeg source imaging guided by spatiotemporal specific fmri toward an understanding of dynamic cognitive processes |
| url | http://dx.doi.org/10.1155/2016/4182483 |
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