Impaired long-range excitatory time scale predicts abnormal neural oscillations and cognitive deficits in Alzheimer's disease.

Parul Verma, Kamalini Ranasinghe, Janani Prasad, Chang Cai, Xihe Xie, Hannah Lerner, Danielle Mizuiri, Bruce Miller, Katherine Rankin, Keith Vossel, Steven W Cheung, Srikantan Nagarajan, Ashish Raj
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Abstract

Alzheimer's disease (AD) is the most common form of dementia, progressively impairing memory and cognition. While neuroimaging studies have revealed functional abnormalities in AD, how these relate to aberrant neuronal circuit mechanisms remains unclear. Using magnetoencephalography imaging we documented abnormal local neural synchrony patterns in patients with AD. To identify abnormal biophysical mechanisms underlying these abnormal electrophysiological patterns, we estimated the parameters of a spectral graph-theory model (SGM). SGM is an analytic model that describes how long-range fiber projections in the brain mediate the excitatory and inhibitory activity of local neuronal subpopulations. The long-range excitatory time scale was associated with greater deficits in global cognition and was able to distinguish AD patients from controls with high accuracy. These results demonstrate that long-range excitatory time scale of neuronal activity, despite being a global measure, is a key determinant in the spatiospectral signatures and cognition in AD.

Abstract Image

Abstract Image

Abstract Image

频谱图建模揭示了阿尔茨海默病神经生理学网络传播的全球放缓。
阿尔茨海默病(AD)是最常见的痴呆症,会逐渐损害记忆和认知。虽然神经影像学研究揭示了AD的功能异常,但这些异常与神经元回路机制的关系尚不清楚。我们使用频谱图理论模型(SGM)来识别AD中神经元活动的异常生物物理标志物。SGM是一个分析模型,描述了大脑中的长程纤维投射如何介导局部神经元亚群的兴奋性和抑制性活动。我们估计了SGM参数,这些参数捕捉了从AD患者和对照组的脑磁图成像中获得的区域功率谱。长期兴奋性时间常数是AD和对照组准确分类的最重要特征,并与AD的整体认知缺陷有关。这些结果表明,长期兴奋性神经元的整体损伤可能是AD神经元活动时空变化的充分因素。
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