Identifying brain changes related to cognitive aging using VBM and visual rating scales

dc.contributor.authorPergher V.
dc.contributor.authorDemaerel P.
dc.contributor.authorSoenen O.
dc.contributor.authorSaarela C.
dc.contributor.authorTournoy J.
dc.contributor.authorSchoenmakers B.
dc.contributor.authorKarrasch M.
dc.contributor.authorVan Hulle M.M.
dc.contributor.organizationfi=psykologia|en=Psychology|
dc.converis.publication-id39835717
dc.converis.urlhttps://research.utu.fi/converis/portal/Publication/39835717
dc.date.accessioned2022-10-28T13:47:16Z
dc.date.available2022-10-28T13:47:16Z
dc.description.abstract<p>Aging is often associated with changes in brain structures as well as in cognitive functions. Structural changes can be visualized with Magnetic Resonance Imaging (MRI) using voxel-based grey matter morphometry (VBM) and visual rating scales to assess atrophy level. Several MRI studies have shown that possible neural correlates of cognitive changes can be seen in normal aging. It is still not fully understood how cognitive function as measured by tests and demographic factors are related to brain changes in the MRI. We recruited 55 healthy elderly subjects aged 50–79 years. A battery of cognitive tests was administered to all subjects prior to MRI scanning. Our aim was to assess correlations between age, sex, education, cognitive test performance, and the said two MRI-based measures. Our results show significant differences in VBM grey matter volume for education level (≤ 12 vs. > 12 years), with a smaller amount of grey matter volume in subjects with lower educational levels, and for age in interaction with education, indicating larger grey matter volume for young, higher educated adults. Also, grey matter volume was found to be correlated with working memory function (Digit Span Backward). Furthermore, significant positive correlations were found between visual ratings and both age and education, showing larger atrophy levels with increasing age and decreasing level of education. These findings provide supportive evidence that MRI-VBM detects structural differences for education level, and correlates with educational level and age, and working memory task performance.<br /><br /></p>
dc.identifier.jour-issn2213-1582
dc.identifier.olddbid184319
dc.identifier.oldhandle10024/167413
dc.identifier.urihttps://www.utupub.fi/handle/11111/41740
dc.identifier.urlhttps://www.sciencedirect.com/science/article/pii/S2213158219300476
dc.identifier.urnURN:NBN:fi-fe2021042823502
dc.language.isoen
dc.okm.affiliatedauthorDataimport, Psykologia
dc.okm.discipline3112 Neurosciencesen_GB
dc.okm.discipline515 Psychologyen_GB
dc.okm.discipline3112 Neurotieteetfi_FI
dc.okm.discipline515 Psykologiafi_FI
dc.okm.internationalcopublicationinternational co-publication
dc.okm.internationalityInternational publication
dc.okm.typeA1 ScientificArticle
dc.publisherElsevier
dc.publisher.countryNetherlandsen_GB
dc.publisher.countryAlankomaatfi_FI
dc.publisher.country-codeNL
dc.relation.articlenumber101697
dc.relation.doi10.1016/j.nicl.2019.101697
dc.relation.ispartofjournalNeuroImage: Clinical
dc.relation.volume22
dc.source.identifierhttps://www.utupub.fi/handle/10024/167413
dc.titleIdentifying brain changes related to cognitive aging using VBM and visual rating scales
dc.year.issued2019

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