Toward a more comprehensive understanding of network centrality disruption in amnestic Mild Cognitive Impairment: a MEG multilayer approach

Abstract

AbstractAlzheimer’s Disease (AD) is the most common form of dementia. Its early stage, amnestic Mild Cognitive Impairment (aMCI), is characterized by disrupted information flow in the brain. Previous studies using electrophysiological techniques to investigate AD’s functional connectivity changes have yielded inconsistent results; contributing factors may include the specific metric employed and the separate study of brain activity in each frequency band. Our study addresses this by employing a cross-frequency approach to compare functional networks in 172 healthy subjects and 105 aMCI patients. Using magnetoencephalography, we constructed source-based multilayer graphs considering both intra- and inter-band functional connectivity across the five classical frequency bands. We assessed network changes through three centrality measures (strength, eigenvector centrality, and betweenness centrality), and combined them into a unified centrality score for a comprehensive assessment of centrality disruption in aMCI. Results revealed a notable shift in centrality distribution in aMCI patients spatially and across frequencies. Posterior brain regions decrease synchrony between high-frequency oscillations and other regions’ activity across all frequencies, while anterior regions increase synchrony between low-frequency oscillations and other regions’ activity across all bands. Thus, posterior regions reduce their relative importance in favor of anterior regions. This study demonstrates that considering the interplays between different frequency bands enhances understanding of AD network dynamics and sets a precedent for multilayer functional network studies. Our findings provide valuable insights into the intricate changes that occur in functional brain networks during the early stages of AD, offering a framework for developing interventions aimed at modifying the disease trajectory.Significance statementOver 55 million people worldwide suffer from Alzheimer’s Disease. The brain changes causing the symptoms begin around 20 years before their onset, so characterizing these changes in the early stage, mild cognitive impairment, is of utmost importance. Magnetoencephalography and electroencephalography (M/EEG) are two commonly used techniques to assess changes in functional networks; however, the existing studies yield inconsistent results. Our study applies a novel methodology for the analysis of M/EEG data that addresses two factors contributing to this effect: the metric employed to assess network changes and the use of a cross-frequency approach. Results show that posterior regions reduce their relative importance in favor of anterior regions. This study sets a precedent for the functional study of all brain disorders.