Altered Domain Functional Network Connectivity Strength and Randomness in Schizophrenia
Functional connectivity is one of the most widely used tools for investigating brain changes due to schizophrenia. Previous studies have identified abnormal functional connectivity in schizophrenia patients at the resting state brain network level. This study tests the existence of functional connec...
| Main Authors: | , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2019-07-01
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| Series: | Frontiers in Psychiatry |
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| Online Access: | https://www.frontiersin.org/article/10.3389/fpsyt.2019.00499/full |
| _version_ | 1819081265084628992 |
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| author | Victor M. Vergara Victor M. Vergara Victor M. Vergara Eswar Damaraju Jessica A. Turner Jessica A. Turner Godfrey Pearlson Godfrey Pearlson Aysenil Belger Daniel H. Mathalon Daniel H. Mathalon Steven G. Potkin Adrian Preda Jatin G. Vaidya Theo G. M. van Erp Theo G. M. van Erp Sarah McEwen Vince D. Calhoun Vince D. Calhoun Vince D. Calhoun Vince D. Calhoun Vince D. Calhoun |
| author_facet | Victor M. Vergara Victor M. Vergara Victor M. Vergara Eswar Damaraju Jessica A. Turner Jessica A. Turner Godfrey Pearlson Godfrey Pearlson Aysenil Belger Daniel H. Mathalon Daniel H. Mathalon Steven G. Potkin Adrian Preda Jatin G. Vaidya Theo G. M. van Erp Theo G. M. van Erp Sarah McEwen Vince D. Calhoun Vince D. Calhoun Vince D. Calhoun Vince D. Calhoun Vince D. Calhoun |
| author_sort | Victor M. Vergara |
| collection | DOAJ |
| description | Functional connectivity is one of the most widely used tools for investigating brain changes due to schizophrenia. Previous studies have identified abnormal functional connectivity in schizophrenia patients at the resting state brain network level. This study tests the existence of functional connectivity effects at whole brain and domain levels. Domain level refers to the integration of data from several brain networks grouped by their functional relationship. Data integration provides more consistent and accurate information compared to an individual brain network. This work considers two domain level measures: functional connectivity strength and randomness. The first measure is simply an average of connectivities within the domain. The second measure assesses the unpredictability and lack of pattern of functional connectivity within the domain. Domains with less random connectivity have higher chance of exhibiting a biologically meaningful connectivity pattern. Consistent with prior observations, individuals with schizophrenia showed aberrant domain connectivity strength between subcortical, cerebellar, and sensorial brain areas. Compared to healthy volunteers, functional connectivity between cognitive and default mode domains showed less randomness, while connectivity between default mode-sensorial areas showed more randomness in schizophrenia patients. These differences in connectivity patterns suggest deleterious rewiring trade-offs among important brain networks. |
| first_indexed | 2024-12-21T19:58:01Z |
| format | Article |
| id | doaj.art-623e66a9b6b84e1fbe152af877ff19f0 |
| institution | Directory Open Access Journal |
| issn | 1664-0640 |
| language | English |
| last_indexed | 2024-12-21T19:58:01Z |
| publishDate | 2019-07-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Psychiatry |
| spelling | doaj.art-623e66a9b6b84e1fbe152af877ff19f02022-12-21T18:52:03ZengFrontiers Media S.A.Frontiers in Psychiatry1664-06402019-07-011010.3389/fpsyt.2019.00499453428Altered Domain Functional Network Connectivity Strength and Randomness in SchizophreniaVictor M. Vergara0Victor M. Vergara1Victor M. Vergara2Eswar Damaraju3Jessica A. Turner4Jessica A. Turner5Godfrey Pearlson6Godfrey Pearlson7Aysenil Belger8Daniel H. Mathalon9Daniel H. Mathalon10Steven G. Potkin11Adrian Preda12Jatin G. Vaidya13Theo G. M. van Erp14Theo G. M. van Erp15Sarah McEwen16Vince D. Calhoun17Vince D. Calhoun18Vince D. Calhoun19Vince D. Calhoun20Vince D. Calhoun21Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, United StatesThe Mind Research Network, Albuquerque, NM, United StatesPsychology Department Georgia State University, Atlanta, GA, United StatesTri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, United StatesPsychology Department Georgia State University, Atlanta, GA, United StatesNeuroscience Institute, Georgia State University, Atlanta, GA, United StatesDepartments of Psychiatry and Neuroscience, Yale University School of Medicine, New Haven, CT, United StatesOlin Neuropsychiatry Research Center, Institute of Living, HHC, Hartford, CT, United StatesDepartment of Psychiatry, University of North Carolina, Chapel Hill, NC, United StatesDepartment of Psychiatry and Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, United StatesMental Health Service, Veterans Affairs San Francisco Healthcare System, San Francisco, CA, United States0Department of Psychiatry and Human Behavior, University of California, Irvine, Irvine, CA, United States0Department of Psychiatry and Human Behavior, University of California, Irvine, Irvine, CA, United States1Department of Psychiatry, University of Iowa, IA, United States2Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California, Irvine, Irvine, CA, United States3Center for the Neurobiology of Learning and Memory, University of California, Irvine, Irvine, CA, United States4Pacific Neuroscience Institute, Santa Monica, CA, United StatesTri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, United StatesThe Mind Research Network, Albuquerque, NM, United StatesPsychology Department Georgia State University, Atlanta, GA, United StatesNeuroscience Institute, Georgia State University, Atlanta, GA, United StatesDepartments of Psychiatry and Neuroscience, Yale University School of Medicine, New Haven, CT, United StatesFunctional connectivity is one of the most widely used tools for investigating brain changes due to schizophrenia. Previous studies have identified abnormal functional connectivity in schizophrenia patients at the resting state brain network level. This study tests the existence of functional connectivity effects at whole brain and domain levels. Domain level refers to the integration of data from several brain networks grouped by their functional relationship. Data integration provides more consistent and accurate information compared to an individual brain network. This work considers two domain level measures: functional connectivity strength and randomness. The first measure is simply an average of connectivities within the domain. The second measure assesses the unpredictability and lack of pattern of functional connectivity within the domain. Domains with less random connectivity have higher chance of exhibiting a biologically meaningful connectivity pattern. Consistent with prior observations, individuals with schizophrenia showed aberrant domain connectivity strength between subcortical, cerebellar, and sensorial brain areas. Compared to healthy volunteers, functional connectivity between cognitive and default mode domains showed less randomness, while connectivity between default mode-sensorial areas showed more randomness in schizophrenia patients. These differences in connectivity patterns suggest deleterious rewiring trade-offs among important brain networks.https://www.frontiersin.org/article/10.3389/fpsyt.2019.00499/fullfunctional MRIfunctional network connectivityrandomnessschizophreniaconnectivity strength function |
| spellingShingle | Victor M. Vergara Victor M. Vergara Victor M. Vergara Eswar Damaraju Jessica A. Turner Jessica A. Turner Godfrey Pearlson Godfrey Pearlson Aysenil Belger Daniel H. Mathalon Daniel H. Mathalon Steven G. Potkin Adrian Preda Jatin G. Vaidya Theo G. M. van Erp Theo G. M. van Erp Sarah McEwen Vince D. Calhoun Vince D. Calhoun Vince D. Calhoun Vince D. Calhoun Vince D. Calhoun Altered Domain Functional Network Connectivity Strength and Randomness in Schizophrenia Frontiers in Psychiatry functional MRI functional network connectivity randomness schizophrenia connectivity strength function |
| title | Altered Domain Functional Network Connectivity Strength and Randomness in Schizophrenia |
| title_full | Altered Domain Functional Network Connectivity Strength and Randomness in Schizophrenia |
| title_fullStr | Altered Domain Functional Network Connectivity Strength and Randomness in Schizophrenia |
| title_full_unstemmed | Altered Domain Functional Network Connectivity Strength and Randomness in Schizophrenia |
| title_short | Altered Domain Functional Network Connectivity Strength and Randomness in Schizophrenia |
| title_sort | altered domain functional network connectivity strength and randomness in schizophrenia |
| topic | functional MRI functional network connectivity randomness schizophrenia connectivity strength function |
| url | https://www.frontiersin.org/article/10.3389/fpsyt.2019.00499/full |
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