2026-04-30T00:40:39Zhttps://uvadoc.uva.es/oai/request

oai:uvadoc.uva.es:10324/625632023-11-02T20:01:11Zcom_10324_23459com_10324_954com_10324_894col_10324_23460

Unveiling the alterations in the frequency-dependent connectivity structure of MEG signals in mild cognitive impairment and Alzheimer’s disease Rodríguez González, Víctor Núñez Novo, Pablo Gómez Peña, Carlos Hoshi, Hideyuki Shigihara, Yoshihito Hornero Sánchez, Roberto Poza Crespo, Jesús Neurology Alzheimer Producción Científica 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. 2023-11-02T09:45:58Z 2023-11-02T09:45:58Z 2024 info:eu-repo/semantics/article Biomedical Signal Processing and Control, 2024, vol. 87, Part A, 105512 1746-8094 https://uvadoc.uva.es/handle/10324/62563 10.1016/j.bspc.2023.105512 105512 Biomedical Signal Processing and Control 87 eng https://www.sciencedirect.com/science/article/pii/S174680942300945X?via%3Dihub info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by-nc-nd/4.0/ © 2023 The Authors Attribution-NonCommercial-NoDerivatives 4.0 Internacional Elsevier SI