Connectivity Measurements for Network Imaging
Communication across the brain networks is dependent on neuronal oscillations. Detection of the synchronous activation of neurons can be used to determine the well-being of the connectivity in the human brain networks. Well-connected highly synchronous activity can be measured by MEG, EEG, fMRI, and...
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description | Communication across the brain networks is dependent on neuronal oscillations. Detection of the synchronous activation of neurons can be used to determine the well-being of the connectivity in the human brain networks. Well-connected highly synchronous activity can be measured by MEG, EEG, fMRI, and PET and then analyzed with several types of mathematical algorithms. Coherence is one mathematical method that can detect how well 2 or more sensors or brain regions have similar oscillatory activity with each other. Phase synchrony can be used to determine if these oscillatory activities are in sync or out of sync with each other. Correlation is used to determine the strength of interaction between two locations or signals. Granger causality can be used to determine the direction of the information flow in the neuronal brain networks. Statistical analysis can be performed on the connectivity results to verify evidence of normal or abnormal network activity in a patient. |
doi_str_mv | 10.1007/7854_2014_348 |
format | Book Chapter |
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Detection of the synchronous activation of neurons can be used to determine the well-being of the connectivity in the human brain networks. Well-connected highly synchronous activity can be measured by MEG, EEG, fMRI, and PET and then analyzed with several types of mathematical algorithms. Coherence is one mathematical method that can detect how well 2 or more sensors or brain regions have similar oscillatory activity with each other. Phase synchrony can be used to determine if these oscillatory activities are in sync or out of sync with each other. Correlation is used to determine the strength of interaction between two locations or signals. Granger causality can be used to determine the direction of the information flow in the neuronal brain networks. Statistical analysis can be performed on the connectivity results to verify evidence of normal or abnormal network activity in a patient.</description><identifier>ISSN: 1866-3370</identifier><identifier>ISBN: 9783319127682</identifier><identifier>ISBN: 3319127683</identifier><identifier>EISSN: 1866-3389</identifier><identifier>EISBN: 9783319127699</identifier><identifier>EISBN: 3319127691</identifier><identifier>DOI: 10.1007/7854_2014_348</identifier><identifier>OCLC: 894893530</identifier><identifier>PMID: 25129140</identifier><identifier>LCCallNum: RC321-580</identifier><language>eng</language><publisher>Switzerland: Springer International Publishing AG</publisher><subject>Coherence ; Correlation ; Granger causality ; Networks ; Neuronal oscillations ; Neurosciences ; Phase synchrony ; Psychiatry ; Psychopharmacology</subject><ispartof>Current topics in behavioral neurosciences, 2014, Vol.21, p.315-330</ispartof><rights>Springer-Verlag Berlin Heidelberg 2014</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c336t-90c882726e97dd317cae554149e7462f509c80d089ef642d1176241b7264979f3</citedby><relation>Current Topics in Behavioral Neurosciences</relation></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Uhttps://ebookcentral.proquest.com/covers/1968227-l.jpg</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/7854_2014_348$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/7854_2014_348$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>779,780,784,793,27925,38255,41442,42511</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/25129140$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Kumari, Veena</contributor><contributor>Bob, Petr</contributor><contributor>Boutros, Nash N</contributor><contributor>Kumari, Veena</contributor><contributor>Boutros, Nash N.</contributor><contributor>Bob, Petr</contributor><creatorcontrib>Bowyer, Susan M.</creatorcontrib><title>Connectivity Measurements for Network Imaging</title><title>Current topics in behavioral neurosciences</title><addtitle>Curr Top Behav Neurosci</addtitle><description>Communication across the brain networks is dependent on neuronal oscillations. Detection of the synchronous activation of neurons can be used to determine the well-being of the connectivity in the human brain networks. Well-connected highly synchronous activity can be measured by MEG, EEG, fMRI, and PET and then analyzed with several types of mathematical algorithms. Coherence is one mathematical method that can detect how well 2 or more sensors or brain regions have similar oscillatory activity with each other. Phase synchrony can be used to determine if these oscillatory activities are in sync or out of sync with each other. Correlation is used to determine the strength of interaction between two locations or signals. Granger causality can be used to determine the direction of the information flow in the neuronal brain networks. Statistical analysis can be performed on the connectivity results to verify evidence of normal or abnormal network activity in a patient.</description><subject>Coherence</subject><subject>Correlation</subject><subject>Granger causality</subject><subject>Networks</subject><subject>Neuronal oscillations</subject><subject>Neurosciences</subject><subject>Phase synchrony</subject><subject>Psychiatry</subject><subject>Psychopharmacology</subject><issn>1866-3370</issn><issn>1866-3389</issn><isbn>9783319127682</isbn><isbn>3319127683</isbn><isbn>9783319127699</isbn><isbn>3319127691</isbn><fulltext>true</fulltext><rsrctype>book_chapter</rsrctype><creationdate>2014</creationdate><recordtype>book_chapter</recordtype><recordid>eNpVkEtPwzAQhM27VemRK8odBby2Y-8eUcWjUoELnK00cUpokxQ7peq_J1ULUk97mG9Gs8PYFfBb4NzcGUyUFRyUlQqP2JAMSgkEwmiiY9YH1DqWEunkQENx-q8Zfs76SApJJpL32DCEL845SExQyAvWEwkIAsX7LB41de2ytvwp20304tKw8q5ydRuiovHRq2vXjZ9H4yqdlfXskp0V6SK44f4O2Mfjw_voOZ68PY1H95M4k1K3MfEMURihHZk8l2Cy1CWJAkXOKC2KhFOGPOdIrtBK5ABGCwXTzqHIUCEH7HqXu1xNK5fbpS-r1G_sX-8OuNkBoZPqmfN22jTzYIHb7Yj2YMSOVvs433yvXGit2-JZ96ZPF9lnumyd78zUrSiMBUQrAeUv-eppyw</recordid><startdate>20140101</startdate><enddate>20140101</enddate><creator>Bowyer, Susan M.</creator><general>Springer International Publishing AG</general><general>Springer International Publishing</general><scope>FFUUA</scope><scope>NPM</scope></search><sort><creationdate>20140101</creationdate><title>Connectivity Measurements for Network Imaging</title><author>Bowyer, Susan M.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c336t-90c882726e97dd317cae554149e7462f509c80d089ef642d1176241b7264979f3</frbrgroupid><rsrctype>book_chapters</rsrctype><prefilter>book_chapters</prefilter><language>eng</language><creationdate>2014</creationdate><topic>Coherence</topic><topic>Correlation</topic><topic>Granger causality</topic><topic>Networks</topic><topic>Neuronal oscillations</topic><topic>Neurosciences</topic><topic>Phase synchrony</topic><topic>Psychiatry</topic><topic>Psychopharmacology</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Bowyer, Susan M.</creatorcontrib><collection>ProQuest Ebook Central - Book Chapters - Demo use only</collection><collection>PubMed</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Bowyer, Susan M.</au><au>Kumari, Veena</au><au>Bob, Petr</au><au>Boutros, Nash N</au><au>Kumari, Veena</au><au>Boutros, Nash N.</au><au>Bob, Petr</au><format>book</format><genre>bookitem</genre><ristype>CHAP</ristype><atitle>Connectivity Measurements for Network Imaging</atitle><btitle>Current topics in behavioral neurosciences</btitle><addtitle>Curr Top Behav Neurosci</addtitle><seriestitle>Current Topics in Behavioral Neurosciences</seriestitle><date>2014-01-01</date><risdate>2014</risdate><volume>21</volume><spage>315</spage><epage>330</epage><pages>315-330</pages><issn>1866-3370</issn><eissn>1866-3389</eissn><isbn>9783319127682</isbn><isbn>3319127683</isbn><eisbn>9783319127699</eisbn><eisbn>3319127691</eisbn><abstract>Communication across the brain networks is dependent on neuronal oscillations. 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identifier | ISSN: 1866-3370 |
ispartof | Current topics in behavioral neurosciences, 2014, Vol.21, p.315-330 |
issn | 1866-3370 1866-3389 |
language | eng |
recordid | cdi_springer_books_10_1007_7854_2014_348 |
source | Springer Books |
subjects | Coherence Correlation Granger causality Networks Neuronal oscillations Neurosciences Phase synchrony Psychiatry Psychopharmacology |
title | Connectivity Measurements for Network Imaging |
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