No Cover Image

Journal article 392 views 32 downloads

Cortical Thickness and Surface Area Networks in Healthy Aging, Alzheimer’s Disease and Behavioral Variant Fronto-Temporal Dementia

Vesna Vuksanovic Orcid Logo, Roger T Staff, Trevor Ahearn, Alison D Murray, Claude M Wischik

International Journal of Neural Systems, Volume: 29, Issue: 06, Start page: 1850055

Swansea University Author: Vesna Vuksanovic Orcid Logo

  • IJNS_Vuksanovic_VV2019.pdf

    PDF | Version of Record

    This is an Open Access article published by World Scientific Publishing Company. It is distributed under the terms of the Creative Commons Attribution 4.0 (CC-BY) License

    Download (1.14MB)

Check full text

DOI (Published version): 10.1142/s0129065718500557

Abstract

Models of the human brain as a complex network of inter-connected sub-units are important in helping to understand the structural basis of the clinical features of neurodegenerative disorders. The aim of this study was to characterize in a systematic manner the differences in the structural correlat...

Full description

Published in: International Journal of Neural Systems
ISSN: 0129-0657 1793-6462
Published: World Scientific Pub Co Pte Lt 2019
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa60502
Tags: Add Tag
No Tags, Be the first to tag this record!
first_indexed 2022-07-21T13:23:15Z
last_indexed 2023-01-13T19:20:40Z
id cronfa60502
recordtype SURis
fullrecord <?xml version="1.0"?><rfc1807><datestamp>2022-07-21T14:23:47.0079904</datestamp><bib-version>v2</bib-version><id>60502</id><entry>2022-07-14</entry><title>Cortical Thickness and Surface Area Networks in Healthy Aging, Alzheimer&#x2019;s Disease and Behavioral Variant Fronto-Temporal Dementia</title><swanseaauthors><author><sid>a1a6e2bd0b6ee99f648abb6201dea474</sid><ORCID>0000-0003-4655-698X</ORCID><firstname>Vesna</firstname><surname>Vuksanovic</surname><name>Vesna Vuksanovic</name><active>true</active><ethesisStudent>false</ethesisStudent></author></swanseaauthors><date>2022-07-14</date><deptcode>HDAT</deptcode><abstract>Models of the human brain as a complex network of inter-connected sub-units are important in helping to understand the structural basis of the clinical features of neurodegenerative disorders. The aim of this study was to characterize in a systematic manner the differences in the structural correlation networks in cortical thickness (CT) and surface area (SA) in Alzheimer&#x2019;s disease (AD) and behavioral variant Fronto-Temporal Dementia (bvFTD). We have used the baseline magnetic resonance imaging (MRI) data available from a large population of patients from three clinical trials in mild to moderate AD and mild bvFTD and compared this to a well-characterized healthy aging cohort. The study population comprised 202 healthy elderly subjects, 213 with bvFTD and 213 with AD. We report that both CT and SA network architecture can be described in terms of highly correlated networks whose positive and inverse links map onto the intrinsic modular organization of the four cortical lobes. The topology of the disturbance in structural network is different in the two disease conditions, and both are different from normal aging. The changes from normal are global in character and are not restricted to fronto-temporal and temporo-parietal lobes, respectively, in bvFTD and AD, and indicate an increase in both global correlational strength and in particular nonhomologous inter-lobar connectivity defined by inverse correlations. These inverse correlations appear to be adaptive in character, reflecting coordinated increases in CT and SA that may compensate for corresponding impairment in functionally linked nodes. The effects were more pronounced in the cortical thickness atrophy network in bvFTD and in the surface area network in AD. Although lobar modularity is preserved in the context of neurodegenerative disease, the hub-like organization of networks differs both from normal and between the two forms of dementia. This implies that hubs may be secondary features of the connectivity adaptation to neurodegeneration and may not be an intrinsic property of the brain. However, analysis of the topological differences in hub-like organization CT and SA networks, and their underlying positive and negative correlations, may provide a basis for assisting in the differential diagnosis of bvFTD and AD.</abstract><type>Journal Article</type><journal>International Journal of Neural Systems</journal><volume>29</volume><journalNumber>06</journalNumber><paginationStart>1850055</paginationStart><paginationEnd/><publisher>World Scientific Pub Co Pte Lt</publisher><placeOfPublication/><isbnPrint/><isbnElectronic/><issnPrint>0129-0657</issnPrint><issnElectronic>1793-6462</issnElectronic><keywords>Structural correlation networks; behavioral variant frontotemporal dementia; Alzheimer&#x2019;s disease</keywords><publishedDay>8</publishedDay><publishedMonth>1</publishedMonth><publishedYear>2019</publishedYear><publishedDate>2019-01-08</publishedDate><doi>10.1142/s0129065718500557</doi><url/><notes/><college>COLLEGE NANME</college><department>Health Data Science</department><CollegeCode>COLLEGE CODE</CollegeCode><DepartmentCode>HDAT</DepartmentCode><institution>Swansea University</institution><apcterm>Another institution paid the OA fee</apcterm><funders>We would like to acknowledge the support of the Maxwell compute cluster funded by the University of Aberdeen.</funders><projectreference/><lastEdited>2022-07-21T14:23:47.0079904</lastEdited><Created>2022-07-14T10:30:49.8751484</Created><path><level id="1">Faculty of Medicine, Health and Life Sciences</level><level id="2">Swansea University Medical School - Medicine</level></path><authors><author><firstname>Vesna</firstname><surname>Vuksanovic</surname><orcid>0000-0003-4655-698X</orcid><order>1</order></author><author><firstname>Roger T</firstname><surname>Staff</surname><order>2</order></author><author><firstname>Trevor</firstname><surname>Ahearn</surname><order>3</order></author><author><firstname>Alison D</firstname><surname>Murray</surname><order>4</order></author><author><firstname>Claude M</firstname><surname>Wischik</surname><order>5</order></author></authors><documents><document><filename>60502__24654__143eb5b52fdb45d8b9b3f2d9fa088529.pdf</filename><originalFilename>IJNS_Vuksanovic_VV2019.pdf</originalFilename><uploaded>2022-07-20T08:40:25.5791004</uploaded><type>Output</type><contentLength>1193138</contentLength><contentType>application/pdf</contentType><version>Version of Record</version><cronfaStatus>true</cronfaStatus><documentNotes>This is an Open Access article published by World Scientific Publishing Company. It is distributed under the terms of the Creative Commons Attribution 4.0 (CC-BY) License</documentNotes><copyrightCorrect>true</copyrightCorrect><language>eng</language><licence>https://creativecommons.org/licenses/by/4.0/</licence></document></documents><OutputDurs/></rfc1807>
spelling 2022-07-21T14:23:47.0079904 v2 60502 2022-07-14 Cortical Thickness and Surface Area Networks in Healthy Aging, Alzheimer’s Disease and Behavioral Variant Fronto-Temporal Dementia a1a6e2bd0b6ee99f648abb6201dea474 0000-0003-4655-698X Vesna Vuksanovic Vesna Vuksanovic true false 2022-07-14 HDAT Models of the human brain as a complex network of inter-connected sub-units are important in helping to understand the structural basis of the clinical features of neurodegenerative disorders. The aim of this study was to characterize in a systematic manner the differences in the structural correlation networks in cortical thickness (CT) and surface area (SA) in Alzheimer’s disease (AD) and behavioral variant Fronto-Temporal Dementia (bvFTD). We have used the baseline magnetic resonance imaging (MRI) data available from a large population of patients from three clinical trials in mild to moderate AD and mild bvFTD and compared this to a well-characterized healthy aging cohort. The study population comprised 202 healthy elderly subjects, 213 with bvFTD and 213 with AD. We report that both CT and SA network architecture can be described in terms of highly correlated networks whose positive and inverse links map onto the intrinsic modular organization of the four cortical lobes. The topology of the disturbance in structural network is different in the two disease conditions, and both are different from normal aging. The changes from normal are global in character and are not restricted to fronto-temporal and temporo-parietal lobes, respectively, in bvFTD and AD, and indicate an increase in both global correlational strength and in particular nonhomologous inter-lobar connectivity defined by inverse correlations. These inverse correlations appear to be adaptive in character, reflecting coordinated increases in CT and SA that may compensate for corresponding impairment in functionally linked nodes. The effects were more pronounced in the cortical thickness atrophy network in bvFTD and in the surface area network in AD. Although lobar modularity is preserved in the context of neurodegenerative disease, the hub-like organization of networks differs both from normal and between the two forms of dementia. This implies that hubs may be secondary features of the connectivity adaptation to neurodegeneration and may not be an intrinsic property of the brain. However, analysis of the topological differences in hub-like organization CT and SA networks, and their underlying positive and negative correlations, may provide a basis for assisting in the differential diagnosis of bvFTD and AD. Journal Article International Journal of Neural Systems 29 06 1850055 World Scientific Pub Co Pte Lt 0129-0657 1793-6462 Structural correlation networks; behavioral variant frontotemporal dementia; Alzheimer’s disease 8 1 2019 2019-01-08 10.1142/s0129065718500557 COLLEGE NANME Health Data Science COLLEGE CODE HDAT Swansea University Another institution paid the OA fee We would like to acknowledge the support of the Maxwell compute cluster funded by the University of Aberdeen. 2022-07-21T14:23:47.0079904 2022-07-14T10:30:49.8751484 Faculty of Medicine, Health and Life Sciences Swansea University Medical School - Medicine Vesna Vuksanovic 0000-0003-4655-698X 1 Roger T Staff 2 Trevor Ahearn 3 Alison D Murray 4 Claude M Wischik 5 60502__24654__143eb5b52fdb45d8b9b3f2d9fa088529.pdf IJNS_Vuksanovic_VV2019.pdf 2022-07-20T08:40:25.5791004 Output 1193138 application/pdf Version of Record true This is an Open Access article published by World Scientific Publishing Company. It is distributed under the terms of the Creative Commons Attribution 4.0 (CC-BY) License true eng https://creativecommons.org/licenses/by/4.0/
title Cortical Thickness and Surface Area Networks in Healthy Aging, Alzheimer’s Disease and Behavioral Variant Fronto-Temporal Dementia
spellingShingle Cortical Thickness and Surface Area Networks in Healthy Aging, Alzheimer’s Disease and Behavioral Variant Fronto-Temporal Dementia
Vesna Vuksanovic
title_short Cortical Thickness and Surface Area Networks in Healthy Aging, Alzheimer’s Disease and Behavioral Variant Fronto-Temporal Dementia
title_full Cortical Thickness and Surface Area Networks in Healthy Aging, Alzheimer’s Disease and Behavioral Variant Fronto-Temporal Dementia
title_fullStr Cortical Thickness and Surface Area Networks in Healthy Aging, Alzheimer’s Disease and Behavioral Variant Fronto-Temporal Dementia
title_full_unstemmed Cortical Thickness and Surface Area Networks in Healthy Aging, Alzheimer’s Disease and Behavioral Variant Fronto-Temporal Dementia
title_sort Cortical Thickness and Surface Area Networks in Healthy Aging, Alzheimer’s Disease and Behavioral Variant Fronto-Temporal Dementia
author_id_str_mv a1a6e2bd0b6ee99f648abb6201dea474
author_id_fullname_str_mv a1a6e2bd0b6ee99f648abb6201dea474_***_Vesna Vuksanovic
author Vesna Vuksanovic
author2 Vesna Vuksanovic
Roger T Staff
Trevor Ahearn
Alison D Murray
Claude M Wischik
format Journal article
container_title International Journal of Neural Systems
container_volume 29
container_issue 06
container_start_page 1850055
publishDate 2019
institution Swansea University
issn 0129-0657
1793-6462
doi_str_mv 10.1142/s0129065718500557
publisher World Scientific Pub Co Pte Lt
college_str Faculty of Medicine, Health and Life Sciences
hierarchytype
hierarchy_top_id facultyofmedicinehealthandlifesciences
hierarchy_top_title Faculty of Medicine, Health and Life Sciences
hierarchy_parent_id facultyofmedicinehealthandlifesciences
hierarchy_parent_title Faculty of Medicine, Health and Life Sciences
department_str Swansea University Medical School - Medicine{{{_:::_}}}Faculty of Medicine, Health and Life Sciences{{{_:::_}}}Swansea University Medical School - Medicine
document_store_str 1
active_str 0
description Models of the human brain as a complex network of inter-connected sub-units are important in helping to understand the structural basis of the clinical features of neurodegenerative disorders. The aim of this study was to characterize in a systematic manner the differences in the structural correlation networks in cortical thickness (CT) and surface area (SA) in Alzheimer’s disease (AD) and behavioral variant Fronto-Temporal Dementia (bvFTD). We have used the baseline magnetic resonance imaging (MRI) data available from a large population of patients from three clinical trials in mild to moderate AD and mild bvFTD and compared this to a well-characterized healthy aging cohort. The study population comprised 202 healthy elderly subjects, 213 with bvFTD and 213 with AD. We report that both CT and SA network architecture can be described in terms of highly correlated networks whose positive and inverse links map onto the intrinsic modular organization of the four cortical lobes. The topology of the disturbance in structural network is different in the two disease conditions, and both are different from normal aging. The changes from normal are global in character and are not restricted to fronto-temporal and temporo-parietal lobes, respectively, in bvFTD and AD, and indicate an increase in both global correlational strength and in particular nonhomologous inter-lobar connectivity defined by inverse correlations. These inverse correlations appear to be adaptive in character, reflecting coordinated increases in CT and SA that may compensate for corresponding impairment in functionally linked nodes. The effects were more pronounced in the cortical thickness atrophy network in bvFTD and in the surface area network in AD. Although lobar modularity is preserved in the context of neurodegenerative disease, the hub-like organization of networks differs both from normal and between the two forms of dementia. This implies that hubs may be secondary features of the connectivity adaptation to neurodegeneration and may not be an intrinsic property of the brain. However, analysis of the topological differences in hub-like organization CT and SA networks, and their underlying positive and negative correlations, may provide a basis for assisting in the differential diagnosis of bvFTD and AD.
published_date 2019-01-08T04:18:40Z
_version_ 1763754240981860352
score 11.013148

Similar Items