Heart Evoked Brain Synchronization Predicts Progression to Alzheimer's Disease
Received Date: Aug 31, 2021 / Accepted Date: Sep 14, 2021 / Published Date: Sep 21, 2021
Abstract
A promising question in neuroscience is enlightening the interaction between heart and brain electrophysiological activities and its relationship with the cognitive status. Our aim here is to study the Heart-Brain Interplay (HBI) and assess whether HBI alterations can be biomarkers for Alzheimer’s disease progression. To this end, we recorded resting state Magnetoencephalography (MEG) for healthy controls and two groups of Mild Cognitive Impairment (MCI) patients without cardiovascular alteration symptoms: stable and progressive to Alzheimer’s disease. Our results demonstrated that MCI patients showed alterations in the HBI that can be summarized as follows: (i) heart evoked responses were interrupted in MCI and this lack of interaction correlate with cognitive performance; (ii) the influence of the heart activity onto brain networks fluctuates along cardiac cycle, being less responsive the MCI networks, and (iii) including HBI-MEG signatures in a machine learning procedure to predict AD progression outperform the results obtained using standard resting state MEG signatures. Our results highlight the role of heart in cognitive neuroscience by showing that basal brain networks are interrelated with the cardiac dynamics and propose the use of heart reference as a biomarker. The ignorance of the cardiac dynamic could be resulting in wastage of relevant information otherwise critical to understand disease as dementia.
Keywords: Heart-brain connection; Resting state connectivity; Heart evoked brain response (HER); Heart evoked brain connectivity (HEC); Progression to alzheimer disease; Mild cognitive impairment
Citation: Castellanos N, Diez GG, Pereda E, López ME, Bruña R, et al. (2021) Heart Evoked Brain Synchronization Predicts Progression to Alzheimer's Disease. J Card Pulm Rehabil 5:145. Doi: 10.4172/jcpr.1000145
Copyright: © 2021 Castellanos N, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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