A new method to build multiplex networks using canonical correlation analysis for the characterization of the Alzheimer's disease continuum

• Published in: Journal of neural engineering 2021-04, Vol.18 (2), p.26002
• Main Authors: Ruiz-Gómez, Saúl J, Hornero, Roberto, Poza, Jesús, Santamaría-Vázquez, Eduardo, Rodríguez-González, Víctor, Maturana-Candelas, Aarón, Gómez, Carlos
• Format: Article
• Language: English
• Subjects: Alzheimer Disease - diagnosis; Brain; Canonical Correlation Analysis; Cognitive Dysfunction; Electroencephalography - methods; Humans
• ISSN: 1741-2560; 1741-2552
• DOI: 10.1088/1741-2552/abd82c

. The aim of this study was to solve one of the current limitations for the characterization of the brain network in the Alzheimer's disease (AD) continuum. Nowadays, frequency-dependent approaches have reached contradictory results depending on the frequency band under study, tangling the possible clinical interpretations. . To overcome this issue, we proposed a new method to build multiplex networks based on canonical correlation analysis (CCA). Our method determines two basis vectors using the source and electrode-level frequency-specific network parameters for a reference group, and then project the results for the rest of the groups into these hyperplanes to make them comparable. It was applied to: (i) synthetic signals generated with a Kuramoto-based model; and (ii) a resting-state electroencephalography (EEG) database formed by recordings from 51 cognitively healthy controls, 51 mild cognitive impairment subjects, 51 mild AD patients, 50 moderate AD patients, and 50 severe AD patients. . Our results using synthetic signals showed that the interpretation of the proposed CCA-based multiplex parameters (multiplex strength, multiplex characteristic path length and multiplex clustering coefficient) can be analogous to their frequency-specific counterparts, as they displayed similar behaviors in terms of average connectivity, integration, and segregation. Findings using real EEG recordings revealed that dementia due to AD is characterized by a significant increase in average connectivity, and by a loss of integration and segregation. . We can conclude that CCA can be used to build multiplex networks based from frequency-specific results, summarizing all the available information and avoiding the limitations of possible frequency-specific conflicts. Additionally, our method supposes a novel approach for the construction and analysis of multiplex networks during AD continuum.