Page 90 - MEGIN Book Of Abstracts - 2023
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(UNMC), Omaha, NE, USA; Memory Disorders and Behavioral   Detection of Mild Cognitive Impairment with MEG
            Neurology Program, UNMC, Omaha, NE, USA            Functional Connectivity Using Wavelet-Based
                                                               Neuromarkers (2021)
            BACKGROUND Alzheimer's disease (AD) is generally
            thought to spare primary sensory function; however,                 Yang, Su; Bornot, Jose Miguel Sanchez; Fernandez,
            such interpretations have drawn from a literature that   Ricardo Bruña; Deravi, Farzin; Hoque, Sanaul; Wong-Lin,
            has rarely taken into account the variable cognitive   KongFatt; Prasad, Girijesh
            declines seen in patients with AD. As these cognitive
            domains are now known to modulate cortical somato-  Department of Computer Science, Swansea University, Swan-
            sensory processing, it remains possible that abnormali-  sea SA1 8EN, UK; Intelligent Systems Research Centre, School
            ties in somatosensory function in patients with AD   of Computing, Engineering and Intelligent Systems, Ulster
            have been suppressed by neuropsychological variabil-  University, Londonderry BT48 7JL, UK; Centre for Biomedical
            ity in previous research.                          Technology, Technical University of Madrid, 28223 Madrid,
                                                               Spain; School of Engineering, University of Kent, Canterbury
            METHODS In this study, we combine magnetoenceph-   CT2 7NZ, UK
            alographic (MEG) brain imaging during a paired-pulse
            somatosensory gating task with an extensive battery   ABSTRACT Studies on developing effective neuro-
            of neuropsychological tests to investigate the influence   markers based on magnetoencephalographic (MEG)
            of cognitive variability on estimated differences in so-  signals have been drawing increasing attention in the
            matosensory function between biomarker-confirmed   neuroscience community. This study explores the idea
            patients on the AD spectrum and cognitively-normal   of using source-based magnitude-squared spectral
            older adults.                                      coherence as a spatial indicator for effective regions of
                                                               interest (ROIs) localization, subsequently discriminating
            FINDINGS We show that patients on the AD spectrum   the participants with mild cognitive impairment (MCI)
            exhibit largely non-significant differences in somato-  from a group of age-matched healthy control (HC)
            sensory function when cognitive variability is not   elderly participants. We found that the cortical regions
            considered (p-value range: .020-.842). However, once   could be divided into two distinctive groups based
            attention and processing speed abilities are considered,   on their coherence indices. Compared to HC, some
            robust differences in gamma-frequency somatosensory   ROIs showed increased connectivity (hyper-connected
            response amplitude (p < .001) and gating (p = .004)   ROIs) for MCI participants, whereas the remaining ROIs
            emerge, accompanied by significant statistical suppres-  demonstrated reduced connectivity (hypo-connected
            sion effects.                                      ROIs). Based on these findings, a series of wavelet-
                                                               based source-level neuromarkers for MCI detection are
            INTERPRETATION These findings suggest that patients   proposed and explored, with respect to the two distinc-
            with AD exhibit insults to functional somatosensory   tive ROI groups. It was found that the neuromarkers
            processing in primary sensory cortices, but these   extracted from the hyper-connected ROIs performed
            effects are masked by variability in cognitive decline   significantly better for MCI detection than those from
            across individuals.                                the hypo-connected ROIs. The neuromarkers were clas-
                                                               sified using support vector machine (SVM) and k-NN
            FUNDING National Institutes of Health, USA; Fremont   classifiers and evaluated through Monte Carlo cross-
            Area Alzheimer's Fund, USA.                        validation. An average recognition rate of 93.83% was
                                                               obtained using source-reconstructed signals from the
            Keywords: Amyloid-β, Gamma oscillations, Magnetoen-  hyper-connected ROI group. To better conform to clini-
            cephalography, Neuropsychology, Sensory gating     cal practice settings, a leave-one-out cross-validation
                                                               (LOOCV) approach was also employed to ensure that
            EBioMedicine (2021), Vol. 73 (34689085) (5 citations)  the data for testing was from a participant that the clas-







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