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P300, grey matter volume and individual characteristics correlates in healthy elderly

Journal Contribution - Journal Article

We investigated whether P300-ERP and cognitive test performance differ for age, sex, and education in two groups of healthy elderly, and verified whether any correlations exist between P300 amplitude and latency and gray matter volume using whole brain voxel-by-voxel-based mapping, controlling for age, education, sex and Total Intracranial Volume (TIV). We used 32 channel electroencephalograms (EEG) to record the P300 responses and 3T Magnetic Resonance Imaging (MRI) to determine gray matter volume. We recruited 36 native-Dutch speaking healthy older subjects, equally divided in two sub-groups of 52–64 and 65–76 years old, administered a battery of cognitive tests and recorded their demographics, EEGs and task performance; additionally, 16 adults from the second sub-group underwent an MRI scan. We found significant differences between age groups in their cognitive tests performance, P300 amplitudes for the frontal and parietal electrodes for the most difficult task, and P300 latencies for frontal, central and parietal electrodes for all three tasks difficulty levels. Interesting, sex and education affected cognitive and P300 results. Higher education was related to higher accuracy, and P300 amplitudes and shorter latencies. Moreover, females exhibited higher P300 amplitudes and shorter latencies, and better cognitive tasks performance compared to males. Additionally, for the 16 adults underwent to MRI scan, we found positive correlations between P300 characteristics in frontal, central and parietal areas and gray matter volume, controlling for demographic variables and TIV, but also showing that age, sex, and education correlate with gray matter volume. These findings provide support that age, sex, and education affect an individual’s cognitive, neurophysiological and structural characteristics, and therefore motivate the need to further investigate these in relation to P300 responses and gray matter volume in healthy elderly.
Journal: Frontiers in Aging Neuroscience
ISSN: 1663-4365
Issue: 104
Volume: 11
Pages: 1 - 13
Publication year:2019
BOF-keylabel:yes
IOF-keylabel:yes
BOF-publication weight:6
CSS-citation score:1
Authors from:Higher Education
Accessibility:Open