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dc.contributor.authorTait, L
dc.contributor.authorStothart, G
dc.contributor.authorCoulthard, E
dc.contributor.authorBrown, JT
dc.contributor.authorKazanina, N
dc.contributor.authorGoodfellow, M
dc.date.accessioned2019-11-20T16:20:25Z
dc.date.issued2019-06-27
dc.description.abstractObjectives: Functional and structural disconnection of the brain is a prevailing hypothesis to explain cognitive impairment in Alzheimer's Disease (AD). We aim to understand the link between alterations to networks and cognitive impairment using functional connectivity analysis and modelling. Methods: EEG was recorded from 21 AD patients and 26 controls, mapped into source space using eLORETA, and functional connectivity was calculated using phase locking factor. The mini-mental state exam (MMSE) was used to assess cognitive impairment. A computational model was used to uncover mechanisms of altered functional connectivity. Results: Small-worldness (SW) of functional networks decreased in AD and was positively correlated with MMSE score and the language sub-score. Reduced SW was a result of increased path lengths, predominantly localized to the temporal lobes. Combining observed differences in local oscillation frequency with reduced temporal lobe effective connectivity in the model could account for observed functional network differences. Conclusions: Temporal lobe disconnection plays a key role in cognitive impairment in AD. Significance: We combine electrophysiology, neuropsychological scores, and computational modelling to provide novel insight into the relationships between the disconnection hypothesis and cognitive decline in AD.en_GB
dc.description.sponsorshipEngineering and Physical Sciences Research Council (EPSRC)en_GB
dc.description.sponsorshipWellcome Trusten_GB
dc.description.sponsorshipAlzheimer's Societyen_GB
dc.description.sponsorshipGarfield Weston Foundationen_GB
dc.description.sponsorshipUniversity of Bristolen_GB
dc.identifier.citationVol. 130 (9), pp. 1581 - 1595en_GB
dc.identifier.doi10.1016/j.clinph.2019.05.027
dc.identifier.grantnumberEP/P021417/1en_GB
dc.identifier.grantnumberEP/N014391/1en_GB
dc.identifier.grantnumberWT105618MAen_GB
dc.identifier.grantnumber231en_GB
dc.identifier.urihttp://hdl.handle.net/10871/39640
dc.language.isoenen_GB
dc.publisherElsevier for International Federation of Clinical Neurophysiologyen_GB
dc.rights© 2019 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. This is an open access article under the CC BY license (https://creativecommons.org/licenses/by/4.0/).en_GB
dc.subjectAlzheimer’s Diseaseen_GB
dc.subjectDementiaen_GB
dc.subjectElectroencephalographyen_GB
dc.subjectCognitive impairmenten_GB
dc.titleNetwork substrates of cognitive impairment in Alzheimer's Diseaseen_GB
dc.typeArticleen_GB
dc.date.available2019-11-20T16:20:25Z
dc.identifier.issn1388-2457
dc.descriptionThis is the final version. Available on open access from Elsevier via the DOI in this recorden_GB
dc.identifier.journalClinical Neurophysiologyen_GB
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_GB
dcterms.dateAccepted2019-05-17
exeter.funder::Engineering and Physical Sciences Research Council (EPSRC)en_GB
exeter.funder::Engineering and Physical Sciences Research Council (EPSRC)en_GB
rioxxterms.versionVoRen_GB
rioxxterms.licenseref.startdate2019-06-27
rioxxterms.typeJournal Article/Reviewen_GB
refterms.dateFCD2019-11-20T16:16:31Z
refterms.versionFCDVoR
refterms.dateFOA2019-11-20T16:20:29Z
refterms.panelBen_GB
refterms.depositExceptionpublishedGoldOA


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© 2019 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. This is an open
access article under the CC BY license (https://creativecommons.org/licenses/by/4.0/).
Except where otherwise noted, this item's licence is described as © 2019 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. This is an open access article under the CC BY license (https://creativecommons.org/licenses/by/4.0/).