Empirical validation of directed functional connectivity
Mapping directions of influence in the human brain connectome represents the next phase in understanding its functional architecture. However, a host of methodological uncertainties have impeded the application of directed connectivity methods, which have primarily been validated via “ground truth”...
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description | Mapping directions of influence in the human brain connectome represents the next phase in understanding its functional architecture. However, a host of methodological uncertainties have impeded the application of directed connectivity methods, which have primarily been validated via “ground truth” connectivity patterns embedded in simulated functional MRI (fMRI) and magneto-/electro-encephalography (MEG/EEG) datasets. Such simulations rely on many generative assumptions, and we hence utilized a different strategy involving empirical data in which a ground truth directed connectivity pattern could be anticipated with confidence. Specifically, we exploited the established “sensory reactivation” effect in episodic memory, in which retrieval of sensory information reactivates regions involved in perceiving that sensory modality. Subjects performed a paired associate task in separate fMRI and MEG sessions, in which a ground truth reversal in directed connectivity between auditory and visual sensory regions was instantiated across task conditions. This directed connectivity reversal was successfully recovered across different algorithms, including Granger causality and Bayes network (IMAGES) approaches, and across fMRI (“raw” and deconvolved) and source-modeled MEG. These results extend simulation studies of directed connectivity, and offer practical guidelines for the use of such methods in clarifying causal mechanisms of neural processing. |
doi_str_mv | 10.1016/j.neuroimage.2016.11.037 |
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However, a host of methodological uncertainties have impeded the application of directed connectivity methods, which have primarily been validated via “ground truth” connectivity patterns embedded in simulated functional MRI (fMRI) and magneto-/electro-encephalography (MEG/EEG) datasets. Such simulations rely on many generative assumptions, and we hence utilized a different strategy involving empirical data in which a ground truth directed connectivity pattern could be anticipated with confidence. Specifically, we exploited the established “sensory reactivation” effect in episodic memory, in which retrieval of sensory information reactivates regions involved in perceiving that sensory modality. Subjects performed a paired associate task in separate fMRI and MEG sessions, in which a ground truth reversal in directed connectivity between auditory and visual sensory regions was instantiated across task conditions. This directed connectivity reversal was successfully recovered across different algorithms, including Granger causality and Bayes network (IMAGES) approaches, and across fMRI (“raw” and deconvolved) and source-modeled MEG. These results extend simulation studies of directed connectivity, and offer practical guidelines for the use of such methods in clarifying causal mechanisms of neural processing.</description><identifier>ISSN: 1053-8119</identifier><identifier>EISSN: 1095-9572</identifier><identifier>DOI: 10.1016/j.neuroimage.2016.11.037</identifier><identifier>PMID: 27856312</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>Accuracy ; Acoustic Stimulation ; Adult ; Algorithms ; Auditory Perception - physiology ; Bayes Theorem ; Bayesian analysis ; Brain ; Brain - anatomy & histology ; Brain - physiology ; Brain architecture ; Brain mapping ; Computer Simulation ; Connectome ; Data processing ; Directed connectivity ; EEG ; Effective connectivity ; Female ; fMRI ; Fourier transforms ; Functional connectivity ; Functional magnetic resonance imaging ; Humans ; Information processing ; Magnetic Resonance Imaging ; Magnetoencephalography ; Male ; MEG ; Memory ; Memory - physiology ; Methods ; Middle Aged ; Neural networks ; Neural Pathways - anatomy & histology ; Neural Pathways - physiology ; Neurosciences ; Photic Stimulation ; Reproducibility of Results ; Sensors ; Sensory integration ; Time series ; Visual Perception - physiology ; Young Adult</subject><ispartof>NeuroImage (Orlando, Fla.), 2017-02, Vol.146, p.275-287</ispartof><rights>2016 Elsevier Inc.</rights><rights>Copyright © 2016 Elsevier Inc. All rights reserved.</rights><rights>2016. Elsevier Inc.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c606t-3d9dcd37e300a65791bb92d853487232d049ece1b0c8775c5fc2ebb425be2413</citedby><cites>FETCH-LOGICAL-c606t-3d9dcd37e300a65791bb92d853487232d049ece1b0c8775c5fc2ebb425be2413</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.proquest.com/docview/1870637929?pq-origsite=primo$$EHTML$$P50$$Gproquest$$H</linktohtml><link.rule.ids>230,314,778,782,883,3539,27907,27908,45978,64366,64368,64370,72220</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/27856312$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Mill, Ravi D.</creatorcontrib><creatorcontrib>Bagic, Anto</creatorcontrib><creatorcontrib>Bostan, Andreea</creatorcontrib><creatorcontrib>Schneider, Walter</creatorcontrib><creatorcontrib>Cole, Michael W.</creatorcontrib><title>Empirical validation of directed functional connectivity</title><title>NeuroImage (Orlando, Fla.)</title><addtitle>Neuroimage</addtitle><description>Mapping directions of influence in the human brain connectome represents the next phase in understanding its functional architecture. However, a host of methodological uncertainties have impeded the application of directed connectivity methods, which have primarily been validated via “ground truth” connectivity patterns embedded in simulated functional MRI (fMRI) and magneto-/electro-encephalography (MEG/EEG) datasets. Such simulations rely on many generative assumptions, and we hence utilized a different strategy involving empirical data in which a ground truth directed connectivity pattern could be anticipated with confidence. Specifically, we exploited the established “sensory reactivation” effect in episodic memory, in which retrieval of sensory information reactivates regions involved in perceiving that sensory modality. Subjects performed a paired associate task in separate fMRI and MEG sessions, in which a ground truth reversal in directed connectivity between auditory and visual sensory regions was instantiated across task conditions. This directed connectivity reversal was successfully recovered across different algorithms, including Granger causality and Bayes network (IMAGES) approaches, and across fMRI (“raw” and deconvolved) and source-modeled MEG. These results extend simulation studies of directed connectivity, and offer practical guidelines for the use of such methods in clarifying causal mechanisms of neural processing.</description><subject>Accuracy</subject><subject>Acoustic Stimulation</subject><subject>Adult</subject><subject>Algorithms</subject><subject>Auditory Perception - physiology</subject><subject>Bayes Theorem</subject><subject>Bayesian analysis</subject><subject>Brain</subject><subject>Brain - anatomy & histology</subject><subject>Brain - physiology</subject><subject>Brain architecture</subject><subject>Brain mapping</subject><subject>Computer Simulation</subject><subject>Connectome</subject><subject>Data processing</subject><subject>Directed connectivity</subject><subject>EEG</subject><subject>Effective connectivity</subject><subject>Female</subject><subject>fMRI</subject><subject>Fourier transforms</subject><subject>Functional connectivity</subject><subject>Functional magnetic resonance imaging</subject><subject>Humans</subject><subject>Information processing</subject><subject>Magnetic Resonance Imaging</subject><subject>Magnetoencephalography</subject><subject>Male</subject><subject>MEG</subject><subject>Memory</subject><subject>Memory - physiology</subject><subject>Methods</subject><subject>Middle Aged</subject><subject>Neural networks</subject><subject>Neural Pathways - anatomy & histology</subject><subject>Neural Pathways - physiology</subject><subject>Neurosciences</subject><subject>Photic Stimulation</subject><subject>Reproducibility of Results</subject><subject>Sensors</subject><subject>Sensory integration</subject><subject>Time series</subject><subject>Visual Perception - physiology</subject><subject>Young Adult</subject><issn>1053-8119</issn><issn>1095-9572</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNqNkUtv1TAQhS0EoqXwF1AkNmwSPH7E9gYJqvKQKrHp3nLsSfFVbnyxkyv13-NwS3lsYGVr_M05njmENEA7oNC_2XUzrjnFvbvFjtVKB9BRrh6Rc6BGtkYq9ni7S95qAHNGnpWyo5QaEPopOWNKy54DOyf6an-IOXo3NUc3xeCWmOYmjU2IGf2CoRnX2W_FSvg0z7UYj3G5e06ejG4q-OL-vCA3H65uLj-1118-fr58d936nvZLy4MJPnCFnFLXS2VgGAwLWnKhFeMsUGHQIwzUa6Wkl6NnOAyCyQGZAH5B3p5kD-uwx-BxXrKb7CHX2fOdTS7aP1_m-NXepqOVnIESpgq8vhfI6duKZbH7WDxOk5sxrcVCtdWCawP_gQpQRmkmKvrqL3SX1lx39EOQ9lwZtnnrE-VzKiXj-PBvoHYL0u7sryDtFqQFsDXI2vry97kfGn8mV4H3JwDr8o8Rsy0-4uzxFJwNKf7b5Tud9bR9</recordid><startdate>20170201</startdate><enddate>20170201</enddate><creator>Mill, Ravi D.</creator><creator>Bagic, Anto</creator><creator>Bostan, Andreea</creator><creator>Schneider, Walter</creator><creator>Cole, Michael W.</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><scope>5PM</scope></search><sort><creationdate>20170201</creationdate><title>Empirical validation of directed functional connectivity</title><author>Mill, Ravi D. ; Bagic, Anto ; Bostan, Andreea ; Schneider, Walter ; Cole, Michael W.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c606t-3d9dcd37e300a65791bb92d853487232d049ece1b0c8775c5fc2ebb425be2413</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Accuracy</topic><topic>Acoustic Stimulation</topic><topic>Adult</topic><topic>Algorithms</topic><topic>Auditory Perception - physiology</topic><topic>Bayes Theorem</topic><topic>Bayesian analysis</topic><topic>Brain</topic><topic>Brain - anatomy & histology</topic><topic>Brain - physiology</topic><topic>Brain architecture</topic><topic>Brain mapping</topic><topic>Computer Simulation</topic><topic>Connectome</topic><topic>Data processing</topic><topic>Directed connectivity</topic><topic>EEG</topic><topic>Effective connectivity</topic><topic>Female</topic><topic>fMRI</topic><topic>Fourier transforms</topic><topic>Functional connectivity</topic><topic>Functional magnetic resonance imaging</topic><topic>Humans</topic><topic>Information processing</topic><topic>Magnetic Resonance Imaging</topic><topic>Magnetoencephalography</topic><topic>Male</topic><topic>MEG</topic><topic>Memory</topic><topic>Memory - physiology</topic><topic>Methods</topic><topic>Middle Aged</topic><topic>Neural networks</topic><topic>Neural Pathways - anatomy & histology</topic><topic>Neural Pathways - physiology</topic><topic>Neurosciences</topic><topic>Photic Stimulation</topic><topic>Reproducibility of Results</topic><topic>Sensors</topic><topic>Sensory integration</topic><topic>Time series</topic><topic>Visual Perception - 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Academic</collection><collection>Biotechnology Research Abstracts</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>NeuroImage (Orlando, Fla.)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Mill, Ravi D.</au><au>Bagic, Anto</au><au>Bostan, Andreea</au><au>Schneider, Walter</au><au>Cole, Michael W.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Empirical validation of directed functional connectivity</atitle><jtitle>NeuroImage (Orlando, Fla.)</jtitle><addtitle>Neuroimage</addtitle><date>2017-02-01</date><risdate>2017</risdate><volume>146</volume><spage>275</spage><epage>287</epage><pages>275-287</pages><issn>1053-8119</issn><eissn>1095-9572</eissn><abstract>Mapping directions of influence in the human brain connectome represents the next phase in understanding its functional architecture. However, a host of methodological uncertainties have impeded the application of directed connectivity methods, which have primarily been validated via “ground truth” connectivity patterns embedded in simulated functional MRI (fMRI) and magneto-/electro-encephalography (MEG/EEG) datasets. Such simulations rely on many generative assumptions, and we hence utilized a different strategy involving empirical data in which a ground truth directed connectivity pattern could be anticipated with confidence. Specifically, we exploited the established “sensory reactivation” effect in episodic memory, in which retrieval of sensory information reactivates regions involved in perceiving that sensory modality. Subjects performed a paired associate task in separate fMRI and MEG sessions, in which a ground truth reversal in directed connectivity between auditory and visual sensory regions was instantiated across task conditions. This directed connectivity reversal was successfully recovered across different algorithms, including Granger causality and Bayes network (IMAGES) approaches, and across fMRI (“raw” and deconvolved) and source-modeled MEG. These results extend simulation studies of directed connectivity, and offer practical guidelines for the use of such methods in clarifying causal mechanisms of neural processing.</abstract><cop>United States</cop><pub>Elsevier Inc</pub><pmid>27856312</pmid><doi>10.1016/j.neuroimage.2016.11.037</doi><tpages>13</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Accuracy Acoustic Stimulation Adult Algorithms Auditory Perception - physiology Bayes Theorem Bayesian analysis Brain Brain - anatomy & histology Brain - physiology Brain architecture Brain mapping Computer Simulation Connectome Data processing Directed connectivity EEG Effective connectivity Female fMRI Fourier transforms Functional connectivity Functional magnetic resonance imaging Humans Information processing Magnetic Resonance Imaging Magnetoencephalography Male MEG Memory Memory - physiology Methods Middle Aged Neural networks Neural Pathways - anatomy & histology Neural Pathways - physiology Neurosciences Photic Stimulation Reproducibility of Results Sensors Sensory integration Time series Visual Perception - physiology Young Adult |
title | Empirical validation of directed functional connectivity |
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