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Neural Oscillation Disorder in the Hippocampal CA1 Region of Different Alzheimer's Disease Mice

BACKGROUND: Alzheimer's disease (AD) is a well-known neurodegenerative disease that gradually induces neural network dysfunction and progressive memory deficits. Neural network activity is represented by rhythmic oscillations that influence local field potentials (LFPs). However, changes in hip...

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Detalles Bibliográficos
Autores principales: Yuan, Weiming, Zhi, Weijia, Ma, Lizhen, Hu, Xiangjun, Wang, Qian, Zou, Yong, Wang, Lifeng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Bentham Science Publishers 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10661967/
https://www.ncbi.nlm.nih.gov/pubmed/37559542
http://dx.doi.org/10.2174/1567205020666230808122643
Descripción
Sumario:BACKGROUND: Alzheimer's disease (AD) is a well-known neurodegenerative disease that gradually induces neural network dysfunction and progressive memory deficits. Neural network activity is represented by rhythmic oscillations that influence local field potentials (LFPs). However, changes in hippocampal neural rhythmic oscillations in the early stage of AD remain largely unexplored. OBJECTIVE: This study investigated neural rhythmic oscillations in 3-month-old APP/PS1 and 5xFAD mice to assess early neural connectivity in AD. METHODS: LFPs were recorded from the hippocampal CA1 region with implanted microelectrode arrays while the mice were in the awake resting stage. Welch fast Fourier transforms, continuous wavelet transforms, and phase-amplitude coupling analyses were used to compute the power density of different frequency bands and phase-amplitude modulation indices in the LFPs. RESULTS: Our results showed impaired theta, low gamma, and high gamma frequency band power in APP/PS1 and 5xFAD mice during the awake resting stage. AD mice also showed decreased delta, alpha, and beta frequency band power. Impaired theta-low gamma and theta-high gamma phase-amplitude coupling were observed in 5xFAD mice. CONCLUSION: This study revealed neural network activity differences in oscillation power and cross-frequency coupling in the early stage of AD, providing a new perspective for developing biomarkers for early AD diagnosis.