Analysis of electromagnetic response of cells and lipid membranes using a model-free method

Lu, Yingxian; Tang, Xiaping; Zhao, Yanyu; Jiang, Tianyu; Zhou, Jiayao; Wang, Xiaofei; Huang, Bing; Liu, Lingyu; Deng, Hang; Huang, Yujing; Shi, Yigong

doi:10.1016/j.bioelechem.2023.108444

Cited by 4 publications

(1 citation statement)

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“… 3 , 4 At the cellular level, neurons have bio-electrochemical properties that facilitate the flow of electrical ions, resulting in the production of electromagnetic fields. 5 There are five typical oscillatory brain signals in humans: delta, theta, alpha, beta and gamma. Abnormal neural physiological activities within specific frequency bands can serve as potential histopathological biomarkers for brain dysfunctions.…”

Section: Introductionmentioning

confidence: 99%

Magnetoencephalography-derived oscillatory microstate patterns across lifespan: the Cambridge centre for ageing and neuroscience cohort

Huang,

Cao,

Dai

et al. 2024

Brain Communications

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The aging brain represents the primary risk factor for many neurodegenerative disorders. Whole-brain oscillations may contribute novel early biomarkers of aging. Here, we investigated the dynamic oscillatory neural activities across lifespan (from 18 to 88 years) using resting Magnetoencephalography (MEG) in a large cohort of 624 individuals. Our aim was to examine the patterns of oscillation microstates during the aging process. By using a machine-learning algorithm, we identify four typical clusters of microstate pattern across different age groups and different frequency bands: left-to-right topographic MS1, right-to-left topographic MS2, anterior-posterior MS3 and fronto-central MS4. We observed a decreased alpha duration and an increased alpha occurrence for sensory-related microstate patterns (MS1 & MS2). Accordingly, theta and beta changes from MS1 & MS2 may be related to motor decline that increased with age. Furthermore, voluntary “top-down” saliency/attention networks may be reflected by the increased MS3 & MS4 alpha occurrence and complementary beta activities. The findings of this study advance our knowledge of how the aging brain shows dysfunctions in neural state transitions. By leveraging the identified microstate patterns, this study provides new insights in predicting healthy aging and the potential neuropsychiatric cognitive decline.

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Section: Introductionmentioning

confidence: 99%