Structural Angle and Power Images Reveal Interrelated Gray and White Matter Abnormalities in Schizophrenia
We present a feature extraction method to emphasize the interrelationship between gray and white matter and identify tissue distribution abnormalities in schizophrenia. This approach utilizes novel features called structural phase and magnitude images. The phase image indicates the relative contribu...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2012-01-01
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| Series: | Neurology Research International |
| Online Access: | http://dx.doi.org/10.1155/2012/735249 |
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| _version_ | 1832548712025423872 |
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| author | Lai Xu Tülay Adali David Schretlen Godfrey Pearlson Vince D. Calhoun |
| author_facet | Lai Xu Tülay Adali David Schretlen Godfrey Pearlson Vince D. Calhoun |
| author_sort | Lai Xu |
| collection | DOAJ |
| description | We present a feature extraction method to emphasize the interrelationship between gray and white matter and identify tissue distribution abnormalities in schizophrenia. This approach utilizes novel features called structural phase and magnitude images. The phase image indicates the relative contribution of gray and white matter, and the magnitude image reflects the overall tissue concentration. Three different analyses are applied to the phase and magnitude images obtained from 120 healthy controls and 120 schizophrenia patients. First, a single-subject subtraction analysis is computed for an initial evaluation. Second, we analyze the extracted features using voxel based morphometry (VBM) to detect voxelwise group differences. Third, source based morphometry (SBM) analysis was used to determine abnormalities in structural networks that co-vary in a similar way. Six networks were identified showing significantly lower white-to-gray matter in schizophrenia, including thalamus, right precentral-postcentral, left pre/post-central, parietal, right cuneus-frontal, and left cuneus-frontal sources. Interestingly, some networks look similar to functional patterns, such as sensory-motor and vision. Our findings demonstrate that structural phase and magnitude images can naturally and efficiently summarize the associated relationship between gray and white matter. Our approach has wide applicability for studying tissue distribution differences in the healthy and diseased brain. |
| format | Article |
| id | doaj-art-e956b4d9f8d540d6bb5784c409fd78ed |
| institution | Kabale University |
| issn | 2090-1852 2090-1860 |
| language | English |
| publishDate | 2012-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Neurology Research International |
| spelling | doaj-art-e956b4d9f8d540d6bb5784c409fd78ed2025-02-03T06:13:22ZengWileyNeurology Research International2090-18522090-18602012-01-01201210.1155/2012/735249735249Structural Angle and Power Images Reveal Interrelated Gray and White Matter Abnormalities in SchizophreniaLai Xu0Tülay Adali1David Schretlen2Godfrey Pearlson3Vince D. Calhoun4The Mind Research Network, Albuquerque, NM 87106, USADepartment of CSEE, University of Maryland Baltimore County, Baltimore, MD 21250, USADepartment of Psychiatry, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USAOlin Neuropsychiatry Research Center, Institute of Living, Hartford, CT 06106, USAThe Mind Research Network, Albuquerque, NM 87106, USAWe present a feature extraction method to emphasize the interrelationship between gray and white matter and identify tissue distribution abnormalities in schizophrenia. This approach utilizes novel features called structural phase and magnitude images. The phase image indicates the relative contribution of gray and white matter, and the magnitude image reflects the overall tissue concentration. Three different analyses are applied to the phase and magnitude images obtained from 120 healthy controls and 120 schizophrenia patients. First, a single-subject subtraction analysis is computed for an initial evaluation. Second, we analyze the extracted features using voxel based morphometry (VBM) to detect voxelwise group differences. Third, source based morphometry (SBM) analysis was used to determine abnormalities in structural networks that co-vary in a similar way. Six networks were identified showing significantly lower white-to-gray matter in schizophrenia, including thalamus, right precentral-postcentral, left pre/post-central, parietal, right cuneus-frontal, and left cuneus-frontal sources. Interestingly, some networks look similar to functional patterns, such as sensory-motor and vision. Our findings demonstrate that structural phase and magnitude images can naturally and efficiently summarize the associated relationship between gray and white matter. Our approach has wide applicability for studying tissue distribution differences in the healthy and diseased brain.http://dx.doi.org/10.1155/2012/735249 |
| spellingShingle | Lai Xu Tülay Adali David Schretlen Godfrey Pearlson Vince D. Calhoun Structural Angle and Power Images Reveal Interrelated Gray and White Matter Abnormalities in Schizophrenia Neurology Research International |
| title | Structural Angle and Power Images Reveal Interrelated Gray and White Matter Abnormalities in Schizophrenia |
| title_full | Structural Angle and Power Images Reveal Interrelated Gray and White Matter Abnormalities in Schizophrenia |
| title_fullStr | Structural Angle and Power Images Reveal Interrelated Gray and White Matter Abnormalities in Schizophrenia |
| title_full_unstemmed | Structural Angle and Power Images Reveal Interrelated Gray and White Matter Abnormalities in Schizophrenia |
| title_short | Structural Angle and Power Images Reveal Interrelated Gray and White Matter Abnormalities in Schizophrenia |
| title_sort | structural angle and power images reveal interrelated gray and white matter abnormalities in schizophrenia |
| url | http://dx.doi.org/10.1155/2012/735249 |
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