Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands.
Clinical Neurophysiology and MEG Center, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands.
Alzheimers Res Ther. 2022 Jul 25;14(1):101. doi: 10.1186/s13195-022-01041-4.
Neuronal hyperexcitability and inhibitory interneuron dysfunction are frequently observed in preclinical animal models of Alzheimer's disease (AD). This study investigates whether these microscale abnormalities explain characteristic large-scale magnetoencephalography (MEG) activity in human early-stage AD patients.
To simulate spontaneous electrophysiological activity, we used a whole-brain computational network model comprised of 78 neural masses coupled according to human structural brain topology. We modified relevant model parameters to simulate six literature-based cellular scenarios of AD and compare them to one healthy and six contrast (non-AD-like) scenarios. The parameters include excitability, postsynaptic potentials, and coupling strength of excitatory and inhibitory neuronal populations. Whole-brain spike density and spectral power analyses of the simulated data reveal mechanisms of neuronal hyperactivity that lead to oscillatory changes similar to those observed in MEG data of 18 human prodromal AD patients compared to 18 age-matched subjects with subjective cognitive decline.
All but one of the AD-like scenarios showed higher spike density levels, and all but one of these scenarios had a lower peak frequency, higher spectral power in slower (theta, 4-8Hz) frequencies, and greater total power. Non-AD-like scenarios showed opposite patterns mainly, including reduced spike density and faster oscillatory activity. Human AD patients showed oscillatory slowing (i.e., higher relative power in the theta band mainly), a trend for lower peak frequency and higher total power compared to controls. Combining model and human data, the findings indicate that neuronal hyperactivity can lead to oscillatory slowing, likely due to hyperexcitation (by hyperexcitability of pyramidal neurons or greater long-range excitatory coupling) and/or disinhibition (by reduced excitability of inhibitory interneurons or weaker local inhibitory coupling strength) in early AD.
Using a computational brain network model, we link findings from different scales and models and support the hypothesis of early-stage neuronal hyperactivity underlying E/I imbalance and whole-brain network dysfunction in prodromal AD.
在阿尔茨海默病（AD）的临床前动物模型中，经常观察到神经元兴奋和抑制性中间神经元功能障碍。本研究旨在探讨这些微观异常是否可以解释人类早期 AD 患者的特征性大尺度脑磁图（MEG）活动。
为了模拟自发的电生理活动，我们使用了一个全脑计算网络模型，该模型由 78 个神经团块组成，根据人类结构脑拓扑结构进行耦合。我们修改了相关模型参数，以模拟六种基于文献的 AD 细胞场景，并将其与一种健康和六种对照（非 AD 样）场景进行比较。这些参数包括兴奋性、突触后电位以及兴奋性和抑制性神经元群体的耦合强度。对模拟数据的全脑尖峰密度和频谱功率分析揭示了导致类似 MEG 数据中观察到的振荡变化的神经元过度活跃机制，与 18 名有前驱期 AD 的人类患者和 18 名年龄匹配的有主观认知下降的受试者相比。
除一种情况外，所有 AD 样情况的尖峰密度水平均较高，除一种情况外，这些情况的峰值频率均较低，较慢（θ，4-8Hz）频率的频谱功率较高，总功率较大。非 AD 样情况主要表现出相反的模式，包括尖峰密度降低和更快的振荡活动。与对照组相比，人类 AD 患者表现出振荡减慢（即主要在θ频段具有相对较高的功率），峰值频率降低和总功率增加的趋势。结合模型和人类数据，研究结果表明，神经元过度活跃可能导致振荡减慢，这可能是由于早期 AD 中兴奋性神经元过度兴奋（通过锥体神经元的过度兴奋或更强的长程兴奋性耦合）和/或抑制性神经元抑制减弱（通过抑制性中间神经元的兴奋性降低或局部抑制性耦合强度减弱）所致。
使用计算大脑网络模型，我们将来自不同尺度和模型的发现联系起来，并支持在前驱期 AD 中，早期神经元过度活跃导致 E/I 失衡和全脑网络功能障碍的假说。
