[en] Mild cognitive impairment (MCI) and dementia due to Alzheimer's disease (AD) are neurological disorders that affect cognition, brain function, and memory. Magnetoencephalography (MEG) is a neuroimaging technique used to study changes in brain oscillations caused by neural pathologies. However, MEG studies often use fixed frequency bands, assuming a common frequency structure and overlooking both subject-specific variations and the potential influence of pathologies on frequency distribution. To address this issue, a novel methodology called Connectivity-based Meta-Bands (CMB) was applied to obtain a subject-specific functional connectivity-based frequency bands segmentation. Resting-state MEG activity was acquired from 161 participants: 67 healthy controls, 44 MCI patients, and 50 AD patients. The CMB algorithm was used to identify “meta-bands” (i.e., recurrent network topologies across frequencies). The meta-bands were used to extract an individualised frequency band segmentation. The network topology of the meta-bands and their sequencing were analysed to identify alterations associated with MCI and AD in the underlying frequency-dependent connectivity structure. We found that MCI and AD alter the neural network topology, leading to connectivity patterns both more widespread in the frequency spectrum and heterogeneous. Furthermore, the meta-band frequency sequencing was modified, with MCI and AD patients exhibiting sequences with increased complexity, suggesting a progressive dilution of the frequency structure. The study highlights the relevance of considering the impact of neural pathologies on the frequency-dependent connectivity structure and the potential bias introduced by using fixed frequency bands in MEG studies.
Disciplines :
Neurology
Author, co-author :
Rodríguez-González, Víctor ; Biomedical Engineering Group, University of Valladolid, Valladolid, Spain ; Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina, Instituto de Salud Carlos III (CIBER-BBN), Spain
Nunez Novo, Pablo ; Université de Liège - ULiège > GIGA > GIGA Neurosciences - Coma Science Group
Gómez, Carlos ; Biomedical Engineering Group, University of Valladolid, Valladolid, Spain ; Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina, Instituto de Salud Carlos III (CIBER-BBN), Spain
Hoshi, Hideyuki ; Hokuto Hospital, Obihiro, Japan
Shigihara, Yoshihito; Hokuto Hospital, Obihiro, Japan
Hornero, Roberto ; Biomedical Engineering Group, University of Valladolid, Valladolid, Spain ; Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina, Instituto de Salud Carlos III (CIBER-BBN), Spain ; IMUVA, Instituto de Investigación en Matemáticas, University of Valladolid, Valladolid, Spain
Poza, Jesús; Biomedical Engineering Group, University of Valladolid, Valladolid, Spain ; Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina, Instituto de Salud Carlos III (CIBER-BBN), Spain ; IMUVA, Instituto de Investigación en Matemáticas, University of Valladolid, Valladolid, Spain
Language :
English
Title :
Unveiling the alterations in the frequency-dependent connectivity structure of MEG signals in mild cognitive impairment and Alzheimer's disease
UVA - Universidad de Valladolid ERDF - European Regional Development Fund ISCIII - Instituto de Salud Carlos III
Funding text :
This research has been funded by ‘ CIBER en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN) ’ through ‘ Instituto de Salud Carlos III ’ co-funded with ERDF funds. Vıćtor Rodríguez-González was in receipt of a PIF-UVa grant from the ‘ University of Valladolid ’ and a ‘ Movilidad Doctorandos y Doctorandas UVa 2022 ’ grant. P. Núñez was funded by the ERA-Net FLAG-ERA JTC2021 project ModelDXConsciousness (Human Brain Project Partnering Project).
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