Investigating brain community structure abnormalities in bipolar disorder using path length associated community estimation
In this article, we present path length associated community estimation (PLACE), a comprehensive framework for studying node‐level community structure. Instead of the well‐known Q modularity metric, PLACE utilizes a novel metric, ΨPL, which measures the difference between intercommunity versus intra...
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| Published in | Human brain mapping Vol. 35; no. 5; pp. 2253 - 2264 |
|---|---|
| Main Authors | , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
New York, NY
Blackwell Publishing Ltd
01.05.2014
Wiley-Liss John Wiley & Sons, Inc John Wiley and Sons Inc |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1065-9471 1097-0193 1097-0193 |
| DOI | 10.1002/hbm.22324 |
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| Abstract | In this article, we present path length associated community estimation (PLACE), a comprehensive framework for studying node‐level community structure. Instead of the well‐known Q modularity metric, PLACE utilizes a novel metric, ΨPL, which measures the difference between intercommunity versus intracommunity path lengths. We compared community structures in human healthy brain networks generated using these two metrics and argued that ΨPL may have theoretical advantages. PLACE consists of the following: (1) extracting community structure using top‐down hierarchical binary trees, where a branch at each bifurcation denotes a collection of nodes that form a community at that level, (2) constructing and assessing mean group community structure, and (3) detecting node‐level changes in community between groups. We applied PLACE and investigated the structural brain networks obtained from a sample of 25 euthymic bipolar I subjects versus 25 gender‐ and age‐matched healthy controls. Results showed community structural differences in posterior default mode network regions, with the bipolar group exhibiting left‐right decoupling. Hum Brain Mapp 35:2253–2264, 2014. © 2013 Wiley Periodicals, Inc. |
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| AbstractList | In this article, we present path length associated community estimation (PLACE), a comprehensive framework for studying node‐level community structure. Instead of the well‐known
Q
modularity metric, PLACE utilizes a novel metric,
Ψ
PL
, which measures the difference between intercommunity versus intracommunity path lengths. We compared community structures in human healthy brain networks generated using these two metrics and argued that
Ψ
PL
may have theoretical advantages. PLACE consists of the following: (1) extracting community structure using top‐down hierarchical binary trees, where a branch at each bifurcation denotes a collection of nodes that form a community at that level, (2) constructing and assessing mean group community structure, and (3) detecting node‐level changes in community between groups. We applied PLACE and investigated the structural brain networks obtained from a sample of 25 euthymic bipolar I subjects versus 25 gender‐ and age‐matched healthy controls. Results showed community structural differences in posterior default mode network regions, with the bipolar group exhibiting left‐right decoupling.
Hum Brain Mapp 35:2253–2264, 2014
. ©
2013 Wiley Periodicals, Inc. In this article, we present path length associated community estimation (PLACE), a comprehensive framework for studying node-level community structure. Instead of the well-known Q modularity metric, PLACE utilizes a novel metric, Ψ(PL), which measures the difference between intercommunity versus intracommunity path lengths. We compared community structures in human healthy brain networks generated using these two metrics and argued that Ψ(PL) may have theoretical advantages. PLACE consists of the following: (1) extracting community structure using top-down hierarchical binary trees, where a branch at each bifurcation denotes a collection of nodes that form a community at that level, (2) constructing and assessing mean group community structure, and (3) detecting node-level changes in community between groups. We applied PLACE and investigated the structural brain networks obtained from a sample of 25 euthymic bipolar I subjects versus 25 gender- and age-matched healthy controls. Results showed community structural differences in posterior default mode network regions, with the bipolar group exhibiting left-right decoupling. In this article, we present path length associated community estimation (PLACE), a comprehensive framework for studying node-level community structure. Instead of the well-known Q modularity metric, PLACE utilizes a novel metric, ΨPL, which measures the difference between intercommunity versus intracommunity path lengths. We compared community structures in human healthy brain networks generated using these two metrics and argued that ΨPL may have theoretical advantages. PLACE consists of the following: (1) extracting community structure using top-down hierarchical binary trees, where a branch at each bifurcation denotes a collection of nodes that form a community at that level, (2) constructing and assessing mean group community structure, and (3) detecting node-level changes in community between groups. We applied PLACE and investigated the structural brain networks obtained from a sample of 25 euthymic bipolar I subjects versus 25 gender- and age-matched healthy controls. Results showed community structural differences in posterior default mode network regions, with the bipolar group exhibiting left-right decoupling. Hum Brain Mapp 35:2253-2264, 2014. © 2013 Wiley Periodicals, Inc. [PUBLICATION ABSTRACT] In this article, we present path length associated community estimation (PLACE), a comprehensive framework for studying node‐level community structure. Instead of the well‐known Q modularity metric, PLACE utilizes a novel metric, ΨPL, which measures the difference between intercommunity versus intracommunity path lengths. We compared community structures in human healthy brain networks generated using these two metrics and argued that ΨPL may have theoretical advantages. PLACE consists of the following: (1) extracting community structure using top‐down hierarchical binary trees, where a branch at each bifurcation denotes a collection of nodes that form a community at that level, (2) constructing and assessing mean group community structure, and (3) detecting node‐level changes in community between groups. We applied PLACE and investigated the structural brain networks obtained from a sample of 25 euthymic bipolar I subjects versus 25 gender‐ and age‐matched healthy controls. Results showed community structural differences in posterior default mode network regions, with the bipolar group exhibiting left‐right decoupling. Hum Brain Mapp 35:2253–2264, 2014. © 2013 Wiley Periodicals, Inc. In this article, we present path length associated community estimation (PLACE), a comprehensive framework for studying node-level community structure. Instead of the well-known Q modularity metric, PLACE utilizes a novel metric, Ψ(PL), which measures the difference between intercommunity versus intracommunity path lengths. We compared community structures in human healthy brain networks generated using these two metrics and argued that Ψ(PL) may have theoretical advantages. PLACE consists of the following: (1) extracting community structure using top-down hierarchical binary trees, where a branch at each bifurcation denotes a collection of nodes that form a community at that level, (2) constructing and assessing mean group community structure, and (3) detecting node-level changes in community between groups. We applied PLACE and investigated the structural brain networks obtained from a sample of 25 euthymic bipolar I subjects versus 25 gender- and age-matched healthy controls. Results showed community structural differences in posterior default mode network regions, with the bipolar group exhibiting left-right decoupling.In this article, we present path length associated community estimation (PLACE), a comprehensive framework for studying node-level community structure. Instead of the well-known Q modularity metric, PLACE utilizes a novel metric, Ψ(PL), which measures the difference between intercommunity versus intracommunity path lengths. We compared community structures in human healthy brain networks generated using these two metrics and argued that Ψ(PL) may have theoretical advantages. PLACE consists of the following: (1) extracting community structure using top-down hierarchical binary trees, where a branch at each bifurcation denotes a collection of nodes that form a community at that level, (2) constructing and assessing mean group community structure, and (3) detecting node-level changes in community between groups. We applied PLACE and investigated the structural brain networks obtained from a sample of 25 euthymic bipolar I subjects versus 25 gender- and age-matched healthy controls. Results showed community structural differences in posterior default mode network regions, with the bipolar group exhibiting left-right decoupling. |
| Author | GadElkarim, Johnson J. Feusner, Jamie D. Zhan, Liang Schonfeld, Dan Thompson, Paul M. Kumar, Anand Altshuler, Lori L. Ajilore, Olusola Leow, Alex D. |
| AuthorAffiliation | 1 Electrical and Computer Engineering department University of Illinois at Chicago Chicago Illinois 4 Department of Psychiatry and Behavioral Sciences UCLA Los Angeles California 6 Department of Bioengineering, University of Illinois at Chicago, Chicago, Illinois 2 Department of Psychiatry University of Illinois at Chicago Chicago Illinois 3 Laboratory of Neuro Imaging UCLA Los Angeles California 5 Community Psychiatry Sacramento California |
| AuthorAffiliation_xml | – name: 1 Electrical and Computer Engineering department University of Illinois at Chicago Chicago Illinois – name: 5 Community Psychiatry Sacramento California – name: 3 Laboratory of Neuro Imaging UCLA Los Angeles California – name: 4 Department of Psychiatry and Behavioral Sciences UCLA Los Angeles California – name: 2 Department of Psychiatry University of Illinois at Chicago Chicago Illinois – name: 6 Department of Bioengineering, University of Illinois at Chicago, Chicago, Illinois |
| Author_xml | – sequence: 1 givenname: Johnson J. surname: GadElkarim fullname: GadElkarim, Johnson J. organization: Electrical and Computer Engineering department, University of Illinois at Chicago, Chicago, Illinois – sequence: 2 givenname: Olusola surname: Ajilore fullname: Ajilore, Olusola organization: Department of Psychiatry, University of Illinois at Chicago, Illinois, Chicago – sequence: 3 givenname: Dan surname: Schonfeld fullname: Schonfeld, Dan organization: Electrical and Computer Engineering department, University of Illinois at Chicago, Illinois, Chicago – sequence: 4 givenname: Liang surname: Zhan fullname: Zhan, Liang organization: Laboratory of Neuro Imaging, UCLA, California, Los Angeles – sequence: 5 givenname: Paul M. surname: Thompson fullname: Thompson, Paul M. organization: Laboratory of Neuro Imaging, UCLA, California, Los Angeles – sequence: 6 givenname: Jamie D. surname: Feusner fullname: Feusner, Jamie D. organization: Department of Psychiatry and Behavioral Sciences, UCLA, California, Los Angeles – sequence: 7 givenname: Anand surname: Kumar fullname: Kumar, Anand organization: Department of Psychiatry, University of Illinois at Chicago, Illinois, Chicago – sequence: 8 givenname: Lori L. surname: Altshuler fullname: Altshuler, Lori L. organization: Department of Psychiatry and Behavioral Sciences, UCLA, California, Los Angeles – sequence: 9 givenname: Alex D. surname: Leow fullname: Leow, Alex D. email: alexfeuillet@gmail.com organization: Department of Psychiatry, University of Illinois at Chicago, Chicago, Illinois |
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| Keywords | Mood disorder Nervous system diseases hierarchical trees Radiodiagnosis community structure Estimation Central nervous system Bipolar disorder connectome Encephalon bipolar disorder |
| Language | English |
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| SubjectTerms | Adult Biological and medical sciences bipolar disorder Bipolar Disorder - complications Bipolar Disorder - pathology Brain - pathology Brain Mapping community structure connectome Female Functional Laterality Headache. Facial pains. Syncopes. Epilepsia. Intracranial hypertension. Brain oedema. Cerebral palsy hierarchical trees Humans Investigative techniques, diagnostic techniques (general aspects) Male Medical sciences Middle Aged Models, Neurological Nerve Net - physiology Nervous system Nervous system (semeiology, syndromes) Neural Pathways - pathology Neurology Radiodiagnosis. Nmr imagery. Nmr spectrometry |
| Title | Investigating brain community structure abnormalities in bipolar disorder using path length associated community estimation |
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