Examining resting-state functional connectivity in first-episode schizophrenia with 7T fMRI and MEG
Schizophrenia is often characterized by dysconnections in the brain, which can be estimated via functional connectivity analyses. Commonly measured using resting-state functional magnetic resonance imaging (fMRI) in order to characterize the intrinsic or baseline function of the brain, fMRI function...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2019-01-01
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| Series: | NeuroImage: Clinical |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2213158219303092 |
| _version_ | 1818109834940121088 |
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| author | Kristin K. Lottman Timothy J. Gawne Nina V. Kraguljac Jeffrey F. Killen Meredith A. Reid Adrienne C. Lahti |
| author_facet | Kristin K. Lottman Timothy J. Gawne Nina V. Kraguljac Jeffrey F. Killen Meredith A. Reid Adrienne C. Lahti |
| author_sort | Kristin K. Lottman |
| collection | DOAJ |
| description | Schizophrenia is often characterized by dysconnections in the brain, which can be estimated via functional connectivity analyses. Commonly measured using resting-state functional magnetic resonance imaging (fMRI) in order to characterize the intrinsic or baseline function of the brain, fMRI functional connectivity has significantly contributed to the understanding of schizophrenia. However, these measures may not capture the full extent of functional connectivity abnormalities in schizophrenia as fMRI is temporally limited by the hemodynamic response. In order to extend fMRI functional connectivity findings, the complementary modality of magnetoencephalography (MEG) can be utilized to capture electrophysiological functional connectivity abnormalities in schizophrenia that are not obtainable with fMRI. Therefore, we implemented a multimodal functional connectivity analysis using resting-state 7 Tesla fMRI and MEG data in a sample of first-episode patients with schizophrenia (n = 19) and healthy controls (n = 24). fMRI and MEG data were decomposed into components reflecting resting state networks using a group spatial independent component analysis. Functional connectivity between resting-state networks was computed and group differences were observed. In fMRI, patients demonstrated hyperconnectivity between subcortical and auditory networks, as well as hypoconnectivity between interhemispheric homotopic sensorimotor network components. In MEG, patients demonstrated hypoconnectivity between sensorimotor and task positive networks in the delta frequency band. Results not only support the dysconnectivity hypothesis of schizophrenia, but also suggest the importance of jointly examining multimodal neuroimaging data as critical disorder-related information may not be detectable in a single modality alone. Keywords: Functional connectivity, Functional magnetic resonance imaging, Magnetoencephalography, First-episode, Schizophrenia, Independent component analysis |
| first_indexed | 2024-12-11T02:37:33Z |
| format | Article |
| id | doaj.art-ed5efaac52954965900e0e86bf830b7e |
| institution | Directory Open Access Journal |
| issn | 2213-1582 |
| language | English |
| last_indexed | 2024-12-11T02:37:33Z |
| publishDate | 2019-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | NeuroImage: Clinical |
| spelling | doaj.art-ed5efaac52954965900e0e86bf830b7e2022-12-22T01:23:41ZengElsevierNeuroImage: Clinical2213-15822019-01-0124Examining resting-state functional connectivity in first-episode schizophrenia with 7T fMRI and MEGKristin K. Lottman0Timothy J. Gawne1Nina V. Kraguljac2Jeffrey F. Killen3Meredith A. Reid4Adrienne C. Lahti5Department of Biomedical Engineering, University of Alabama at Birmingham, Birmingham, AL, USADepartment of Optometry and Vision Science, University of Alabama at Birmingham, Birmingham, AL, USADepartment of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham, Birmingham, AL, USAHealth Science Foundation Neurology, University of Alabama at Birmingham, Birmingham, AL, USADepartment of Electrical and Computer Engineering, Auburn University, Auburn, AL, USADepartment of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham, Birmingham, AL, USA; Corresponding author at: Department of Psychiatry and Behavioral Neurobiology, University of Alabama at Birmingham, SC 501, 1530 3rd Avenue South, Birmingham, AL 35294-0017, USA.Schizophrenia is often characterized by dysconnections in the brain, which can be estimated via functional connectivity analyses. Commonly measured using resting-state functional magnetic resonance imaging (fMRI) in order to characterize the intrinsic or baseline function of the brain, fMRI functional connectivity has significantly contributed to the understanding of schizophrenia. However, these measures may not capture the full extent of functional connectivity abnormalities in schizophrenia as fMRI is temporally limited by the hemodynamic response. In order to extend fMRI functional connectivity findings, the complementary modality of magnetoencephalography (MEG) can be utilized to capture electrophysiological functional connectivity abnormalities in schizophrenia that are not obtainable with fMRI. Therefore, we implemented a multimodal functional connectivity analysis using resting-state 7 Tesla fMRI and MEG data in a sample of first-episode patients with schizophrenia (n = 19) and healthy controls (n = 24). fMRI and MEG data were decomposed into components reflecting resting state networks using a group spatial independent component analysis. Functional connectivity between resting-state networks was computed and group differences were observed. In fMRI, patients demonstrated hyperconnectivity between subcortical and auditory networks, as well as hypoconnectivity between interhemispheric homotopic sensorimotor network components. In MEG, patients demonstrated hypoconnectivity between sensorimotor and task positive networks in the delta frequency band. Results not only support the dysconnectivity hypothesis of schizophrenia, but also suggest the importance of jointly examining multimodal neuroimaging data as critical disorder-related information may not be detectable in a single modality alone. Keywords: Functional connectivity, Functional magnetic resonance imaging, Magnetoencephalography, First-episode, Schizophrenia, Independent component analysishttp://www.sciencedirect.com/science/article/pii/S2213158219303092 |
| spellingShingle | Kristin K. Lottman Timothy J. Gawne Nina V. Kraguljac Jeffrey F. Killen Meredith A. Reid Adrienne C. Lahti Examining resting-state functional connectivity in first-episode schizophrenia with 7T fMRI and MEG NeuroImage: Clinical |
| title | Examining resting-state functional connectivity in first-episode schizophrenia with 7T fMRI and MEG |
| title_full | Examining resting-state functional connectivity in first-episode schizophrenia with 7T fMRI and MEG |
| title_fullStr | Examining resting-state functional connectivity in first-episode schizophrenia with 7T fMRI and MEG |
| title_full_unstemmed | Examining resting-state functional connectivity in first-episode schizophrenia with 7T fMRI and MEG |
| title_short | Examining resting-state functional connectivity in first-episode schizophrenia with 7T fMRI and MEG |
| title_sort | examining resting state functional connectivity in first episode schizophrenia with 7t fmri and meg |
| url | http://www.sciencedirect.com/science/article/pii/S2213158219303092 |
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