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Brain signal complexity in adults with Down syndrome: Potential application in the detection of mild cognitive impairment

Authors :
Alberto Fernández
Federico Ramírez-Toraño
Ricardo Bruña
Pilar Zuluaga
Susanna Esteba-Castillo
Daniel Abásolo
Fernando Moldenhauer
Elizabeth Shumbayawonda
Fernando Maestú
Javier García-Alba
Source :
Frontiers in Aging Neuroscience, Vol 14 (2022)
Publication Year :
2022
Publisher :
Frontiers Media S.A., 2022.

Abstract

BackgroundDown syndrome (DS) is considered the most frequent cause of early-onset Alzheimer’s disease (AD), and the typical pathophysiological signs are present in almost all individuals with DS by the age of 40. Despite of this evidence, the investigation on the pre-dementia stages in DS is scarce. In the present study we analyzed the complexity of brain oscillatory patterns and neuropsychological performance for the characterization of mild cognitive impairment (MCI) in DS.Materials and methodsLempel-Ziv complexity (LZC) values from resting-state magnetoencephalography recordings and the neuropsychological performance in 28 patients with DS [control DS group (CN-DS) (n = 14), MCI group (MCI-DS) (n = 14)] and 14 individuals with typical neurodevelopment (CN-no-DS) were analyzed.ResultsLempel-Ziv complexity was lowest in the frontal region within the MCI-DS group, while the CN-DS group showed reduced values in parietal areas when compared with the CN-no-DS group. Also, the CN-no-DS group exhibited the expected pattern of significant increase of LZC as a function of age, while MCI-DS cases showed a decrease. The combination of reduced LZC values and a divergent trajectory of complexity evolution with age, allowed the discrimination of CN-DS vs. MCI-DS patients with a 92.9% of sensitivity and 85.7% of specificity. Finally, a pattern of mnestic and praxic impairment was significantly associated in MCI-DS cases with the significant reduction of LZC values in frontal and parietal regions (p = 0.01).ConclusionBrain signal complexity measured with LZC is reduced in DS and its development with age is also disrupted. The combination of both features might assist in the detection of MCI within this population.

Details

Language :
English
ISSN :
16634365
Volume :
14
Database :
Directory of Open Access Journals
Journal :
Frontiers in Aging Neuroscience
Publication Type :
Academic Journal
Accession number :
edsdoj.8bd9a605534144c8a81bbf44f8d4dfdb
Document Type :
article
Full Text :
https://doi.org/10.3389/fnagi.2022.988540