Loading…

Regions of interest for resting-state fMRI analysis determined by inter-voxel cross-correlation

In investigations of the brain's resting state using functional magnetic resonance imaging (fMRI), a seed-based approach is commonly used to identify brain regions that are functionally connected. The seed is typically identified based on anatomical landmarks, coordinates, or the location of br...

Full description

Saved in:
Bibliographic Details
Published in:NeuroImage (Orlando, Fla.) Fla.), 2011-05, Vol.56 (1), p.246-251
Main Authors: Golestani, Ali-Mohammad, Goodyear, Bradley G.
Format: Article
Language:English
Subjects:
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by cdi_FETCH-LOGICAL-c433t-a63fba7f8eeae8e3bc282b3043ca89e19e1279a65f68266605872aefda235e123
cites cdi_FETCH-LOGICAL-c433t-a63fba7f8eeae8e3bc282b3043ca89e19e1279a65f68266605872aefda235e123
container_end_page 251
container_issue 1
container_start_page 246
container_title NeuroImage (Orlando, Fla.)
container_volume 56
creator Golestani, Ali-Mohammad
Goodyear, Bradley G.
description In investigations of the brain's resting state using functional magnetic resonance imaging (fMRI), a seed-based approach is commonly used to identify brain regions that are functionally connected. The seed is typically identified based on anatomical landmarks, coordinates, or the location of brain activity during a separate task. However, anatomical boundaries may be difficult to discern, and designing a task to interrogate desired brain regions of interest may be difficult, especially when subject compliance is in question, as in many patient studies. In this study, a seed selection method based on inter-voxel cross-correlation of resting-state signals (i.e., a rest-based seed) is introduced. This method was used to determine resting-state connectivity between the left and right motor cortices in fifteen healthy right-handed subjects, and results were compared to seed selection based on the most significantly activated voxels during a separate task (i.e., a task-based seed). The z-coordinate of the centers of mass of the rest-based and task-based seeds within motor cortex were significantly different; task-based seeds were closer to the pial surface. Connectivity maps generated by rest-based seeds and task-based seeds were statistically equivalent; however, only 3 min of data were required to reach significance for rest-based seeds compared to an estimated 6 min for task-based seeds. Rest-based seeds also exhibited good inter-experimenter reproducibility. These findings suggest that seed regions based on inter-voxel cross-correlation of resting-state signals can be used as an alternative approach for connectivity analysis when task-related activity is not available or difficult to acquire, as in some patient studies. ► Seed regions for resting-state can be chosen based by inter-voxel cross-correlation. ► Inter-voxel cross-correlation seeds provide same maps as task-based seeds. ► Separate tasks are not required to define functional based seed regions.
doi_str_mv 10.1016/j.neuroimage.2011.02.038
format article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_862784890</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S1053811911001947</els_id><sourcerecordid>3642015421</sourcerecordid><originalsourceid>FETCH-LOGICAL-c433t-a63fba7f8eeae8e3bc282b3043ca89e19e1279a65f68266605872aefda235e123</originalsourceid><addsrcrecordid>eNqFkVtLxDAQhYMo3v-CBHzwqTWXNk0eVbyBIog-hzSdLFm6jSatuP_erOsFfBECGch3zkzmIIQpKSmh4nReDjDF4BdmBiUjlJaElYTLDbRLiaoLVTdsc1XXvJCUqh20l9KcEKJoJbfRDqOcS6HoLtKPMPNhSDg47IcRIqQRuxDxqvDDrEijGQG7-8dbbAbTL5NPuIMMLvwAHW6Xa1nxFt6hxzaGlAobYoTejNn4AG050yc4_Lr30fPV5dPFTXH3cH17cXZX2IrzsTCCu9Y0TgIYkMBbyyRrOam4NVIBzYc1yojaCcmEEKSWDTPgOsN4nd_4PjpZ-77E8Drl2fXCJwt9bwYIU9JSsEZWUpH_yVpxWvFGZfL4DzkPU8xLSJoKIUmlsl2m5Jr6_HsEp19iDiYuNSV6lZae69-09CotTZjOaWXp0VeDqV1A9yP8jicD52sA8urePESdrIfBQucj2FF3wf_f5QOhJqu9</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1668049903</pqid></control><display><type>article</type><title>Regions of interest for resting-state fMRI analysis determined by inter-voxel cross-correlation</title><source>ScienceDirect Freedom Collection</source><creator>Golestani, Ali-Mohammad ; Goodyear, Bradley G.</creator><creatorcontrib>Golestani, Ali-Mohammad ; Goodyear, Bradley G.</creatorcontrib><description>In investigations of the brain's resting state using functional magnetic resonance imaging (fMRI), a seed-based approach is commonly used to identify brain regions that are functionally connected. The seed is typically identified based on anatomical landmarks, coordinates, or the location of brain activity during a separate task. However, anatomical boundaries may be difficult to discern, and designing a task to interrogate desired brain regions of interest may be difficult, especially when subject compliance is in question, as in many patient studies. In this study, a seed selection method based on inter-voxel cross-correlation of resting-state signals (i.e., a rest-based seed) is introduced. This method was used to determine resting-state connectivity between the left and right motor cortices in fifteen healthy right-handed subjects, and results were compared to seed selection based on the most significantly activated voxels during a separate task (i.e., a task-based seed). The z-coordinate of the centers of mass of the rest-based and task-based seeds within motor cortex were significantly different; task-based seeds were closer to the pial surface. Connectivity maps generated by rest-based seeds and task-based seeds were statistically equivalent; however, only 3 min of data were required to reach significance for rest-based seeds compared to an estimated 6 min for task-based seeds. Rest-based seeds also exhibited good inter-experimenter reproducibility. These findings suggest that seed regions based on inter-voxel cross-correlation of resting-state signals can be used as an alternative approach for connectivity analysis when task-related activity is not available or difficult to acquire, as in some patient studies. ► Seed regions for resting-state can be chosen based by inter-voxel cross-correlation. ► Inter-voxel cross-correlation seeds provide same maps as task-based seeds. ► Separate tasks are not required to define functional based seed regions.</description><identifier>ISSN: 1053-8119</identifier><identifier>EISSN: 1095-9572</identifier><identifier>DOI: 10.1016/j.neuroimage.2011.02.038</identifier><identifier>PMID: 21338691</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>Brain ; Brain - anatomy &amp; histology ; Brain - physiology ; Brain mapping ; Brain Mapping - methods ; Brain research ; Correlation of data ; Functional ; Humans ; Image Interpretation, Computer-Assisted - methods ; Magnetic resonance imaging ; Magnetic Resonance Imaging - methods ; Methods ; Motor cortex ; Neural Pathways - anatomy &amp; histology ; Neural Pathways - physiology ; NMR ; Nuclear magnetic resonance ; Physiology ; Rest - physiology ; Seeds ; Studies</subject><ispartof>NeuroImage (Orlando, Fla.), 2011-05, Vol.56 (1), p.246-251</ispartof><rights>2011 Elsevier Inc.</rights><rights>Copyright © 2011 Elsevier Inc. All rights reserved.</rights><rights>Copyright Elsevier Limited May 1, 2011</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c433t-a63fba7f8eeae8e3bc282b3043ca89e19e1279a65f68266605872aefda235e123</citedby><cites>FETCH-LOGICAL-c433t-a63fba7f8eeae8e3bc282b3043ca89e19e1279a65f68266605872aefda235e123</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27901,27902</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/21338691$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Golestani, Ali-Mohammad</creatorcontrib><creatorcontrib>Goodyear, Bradley G.</creatorcontrib><title>Regions of interest for resting-state fMRI analysis determined by inter-voxel cross-correlation</title><title>NeuroImage (Orlando, Fla.)</title><addtitle>Neuroimage</addtitle><description>In investigations of the brain's resting state using functional magnetic resonance imaging (fMRI), a seed-based approach is commonly used to identify brain regions that are functionally connected. The seed is typically identified based on anatomical landmarks, coordinates, or the location of brain activity during a separate task. However, anatomical boundaries may be difficult to discern, and designing a task to interrogate desired brain regions of interest may be difficult, especially when subject compliance is in question, as in many patient studies. In this study, a seed selection method based on inter-voxel cross-correlation of resting-state signals (i.e., a rest-based seed) is introduced. This method was used to determine resting-state connectivity between the left and right motor cortices in fifteen healthy right-handed subjects, and results were compared to seed selection based on the most significantly activated voxels during a separate task (i.e., a task-based seed). The z-coordinate of the centers of mass of the rest-based and task-based seeds within motor cortex were significantly different; task-based seeds were closer to the pial surface. Connectivity maps generated by rest-based seeds and task-based seeds were statistically equivalent; however, only 3 min of data were required to reach significance for rest-based seeds compared to an estimated 6 min for task-based seeds. Rest-based seeds also exhibited good inter-experimenter reproducibility. These findings suggest that seed regions based on inter-voxel cross-correlation of resting-state signals can be used as an alternative approach for connectivity analysis when task-related activity is not available or difficult to acquire, as in some patient studies. ► Seed regions for resting-state can be chosen based by inter-voxel cross-correlation. ► Inter-voxel cross-correlation seeds provide same maps as task-based seeds. ► Separate tasks are not required to define functional based seed regions.</description><subject>Brain</subject><subject>Brain - anatomy &amp; histology</subject><subject>Brain - physiology</subject><subject>Brain mapping</subject><subject>Brain Mapping - methods</subject><subject>Brain research</subject><subject>Correlation of data</subject><subject>Functional</subject><subject>Humans</subject><subject>Image Interpretation, Computer-Assisted - methods</subject><subject>Magnetic resonance imaging</subject><subject>Magnetic Resonance Imaging - methods</subject><subject>Methods</subject><subject>Motor cortex</subject><subject>Neural Pathways - anatomy &amp; histology</subject><subject>Neural Pathways - physiology</subject><subject>NMR</subject><subject>Nuclear magnetic resonance</subject><subject>Physiology</subject><subject>Rest - physiology</subject><subject>Seeds</subject><subject>Studies</subject><issn>1053-8119</issn><issn>1095-9572</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2011</creationdate><recordtype>article</recordtype><recordid>eNqFkVtLxDAQhYMo3v-CBHzwqTWXNk0eVbyBIog-hzSdLFm6jSatuP_erOsFfBECGch3zkzmIIQpKSmh4nReDjDF4BdmBiUjlJaElYTLDbRLiaoLVTdsc1XXvJCUqh20l9KcEKJoJbfRDqOcS6HoLtKPMPNhSDg47IcRIqQRuxDxqvDDrEijGQG7-8dbbAbTL5NPuIMMLvwAHW6Xa1nxFt6hxzaGlAobYoTejNn4AG050yc4_Lr30fPV5dPFTXH3cH17cXZX2IrzsTCCu9Y0TgIYkMBbyyRrOam4NVIBzYc1yojaCcmEEKSWDTPgOsN4nd_4PjpZ-77E8Drl2fXCJwt9bwYIU9JSsEZWUpH_yVpxWvFGZfL4DzkPU8xLSJoKIUmlsl2m5Jr6_HsEp19iDiYuNSV6lZae69-09CotTZjOaWXp0VeDqV1A9yP8jicD52sA8urePESdrIfBQucj2FF3wf_f5QOhJqu9</recordid><startdate>20110501</startdate><enddate>20110501</enddate><creator>Golestani, Ali-Mohammad</creator><creator>Goodyear, Bradley G.</creator><general>Elsevier Inc</general><general>Elsevier Limited</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7TK</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>88G</scope><scope>8AO</scope><scope>8FD</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>LK8</scope><scope>M0S</scope><scope>M1P</scope><scope>M2M</scope><scope>M7P</scope><scope>P64</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PSYQQ</scope><scope>Q9U</scope><scope>RC3</scope><scope>7X8</scope><scope>7QO</scope></search><sort><creationdate>20110501</creationdate><title>Regions of interest for resting-state fMRI analysis determined by inter-voxel cross-correlation</title><author>Golestani, Ali-Mohammad ; Goodyear, Bradley G.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c433t-a63fba7f8eeae8e3bc282b3043ca89e19e1279a65f68266605872aefda235e123</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Brain</topic><topic>Brain - anatomy &amp; histology</topic><topic>Brain - physiology</topic><topic>Brain mapping</topic><topic>Brain Mapping - methods</topic><topic>Brain research</topic><topic>Correlation of data</topic><topic>Functional</topic><topic>Humans</topic><topic>Image Interpretation, Computer-Assisted - methods</topic><topic>Magnetic resonance imaging</topic><topic>Magnetic Resonance Imaging - methods</topic><topic>Methods</topic><topic>Motor cortex</topic><topic>Neural Pathways - anatomy &amp; histology</topic><topic>Neural Pathways - physiology</topic><topic>NMR</topic><topic>Nuclear magnetic resonance</topic><topic>Physiology</topic><topic>Rest - physiology</topic><topic>Seeds</topic><topic>Studies</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Golestani, Ali-Mohammad</creatorcontrib><creatorcontrib>Goodyear, Bradley G.</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Neurosciences Abstracts</collection><collection>ProQuest Health &amp; Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Psychology Database (Alumni)</collection><collection>ProQuest Pharma Collection</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health &amp; Medical Complete (Alumni)</collection><collection>Biological Sciences</collection><collection>Health &amp; Medical Collection (Alumni Edition)</collection><collection>PML(ProQuest Medical Library)</collection><collection>Psychology Database</collection><collection>Biological Science Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest One Psychology</collection><collection>ProQuest Central Basic</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><collection>Biotechnology Research Abstracts</collection><jtitle>NeuroImage (Orlando, Fla.)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Golestani, Ali-Mohammad</au><au>Goodyear, Bradley G.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Regions of interest for resting-state fMRI analysis determined by inter-voxel cross-correlation</atitle><jtitle>NeuroImage (Orlando, Fla.)</jtitle><addtitle>Neuroimage</addtitle><date>2011-05-01</date><risdate>2011</risdate><volume>56</volume><issue>1</issue><spage>246</spage><epage>251</epage><pages>246-251</pages><issn>1053-8119</issn><eissn>1095-9572</eissn><abstract>In investigations of the brain's resting state using functional magnetic resonance imaging (fMRI), a seed-based approach is commonly used to identify brain regions that are functionally connected. The seed is typically identified based on anatomical landmarks, coordinates, or the location of brain activity during a separate task. However, anatomical boundaries may be difficult to discern, and designing a task to interrogate desired brain regions of interest may be difficult, especially when subject compliance is in question, as in many patient studies. In this study, a seed selection method based on inter-voxel cross-correlation of resting-state signals (i.e., a rest-based seed) is introduced. This method was used to determine resting-state connectivity between the left and right motor cortices in fifteen healthy right-handed subjects, and results were compared to seed selection based on the most significantly activated voxels during a separate task (i.e., a task-based seed). The z-coordinate of the centers of mass of the rest-based and task-based seeds within motor cortex were significantly different; task-based seeds were closer to the pial surface. Connectivity maps generated by rest-based seeds and task-based seeds were statistically equivalent; however, only 3 min of data were required to reach significance for rest-based seeds compared to an estimated 6 min for task-based seeds. Rest-based seeds also exhibited good inter-experimenter reproducibility. These findings suggest that seed regions based on inter-voxel cross-correlation of resting-state signals can be used as an alternative approach for connectivity analysis when task-related activity is not available or difficult to acquire, as in some patient studies. ► Seed regions for resting-state can be chosen based by inter-voxel cross-correlation. ► Inter-voxel cross-correlation seeds provide same maps as task-based seeds. ► Separate tasks are not required to define functional based seed regions.</abstract><cop>United States</cop><pub>Elsevier Inc</pub><pmid>21338691</pmid><doi>10.1016/j.neuroimage.2011.02.038</doi><tpages>6</tpages></addata></record>
fulltext fulltext
identifier ISSN: 1053-8119
ispartof NeuroImage (Orlando, Fla.), 2011-05, Vol.56 (1), p.246-251
issn 1053-8119
1095-9572
language eng
recordid cdi_proquest_miscellaneous_862784890
source ScienceDirect Freedom Collection
subjects Brain
Brain - anatomy & histology
Brain - physiology
Brain mapping
Brain Mapping - methods
Brain research
Correlation of data
Functional
Humans
Image Interpretation, Computer-Assisted - methods
Magnetic resonance imaging
Magnetic Resonance Imaging - methods
Methods
Motor cortex
Neural Pathways - anatomy & histology
Neural Pathways - physiology
NMR
Nuclear magnetic resonance
Physiology
Rest - physiology
Seeds
Studies
title Regions of interest for resting-state fMRI analysis determined by inter-voxel cross-correlation
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-31T22%3A06%3A37IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Regions%20of%20interest%20for%20resting-state%20fMRI%20analysis%20determined%20by%20inter-voxel%20cross-correlation&rft.jtitle=NeuroImage%20(Orlando,%20Fla.)&rft.au=Golestani,%20Ali-Mohammad&rft.date=2011-05-01&rft.volume=56&rft.issue=1&rft.spage=246&rft.epage=251&rft.pages=246-251&rft.issn=1053-8119&rft.eissn=1095-9572&rft_id=info:doi/10.1016/j.neuroimage.2011.02.038&rft_dat=%3Cproquest_cross%3E3642015421%3C/proquest_cross%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c433t-a63fba7f8eeae8e3bc282b3043ca89e19e1279a65f68266605872aefda235e123%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=1668049903&rft_id=info:pmid/21338691&rfr_iscdi=true