PDF(Pubmed)
Abstract：
UNASSIGNED: There is increasing evidence from animal and clinical studies that network hyperexcitability (NH) may be an important pathophysiological process and potential target for treatment in early Alzheimer\'s disease (AD). Measures of functional connectivity (FC) have been proposed as promising biomarkers for NH, but it is unknown which measure has the highest sensitivity for early-stage changes in the excitation/inhibition balance.
UNASSIGNED: We aim to test the performance of different FC measures in detecting NH at the earliest stage using a computational approach.
UNASSIGNED: We use a whole brain computational model of activity dependent degeneration to simulate progressive AD pathology and NH. We investigate if and at what stage four measures of FC (amplitude envelope correlation corrected [AECc], phase lag index [PLI], joint permutation entropy [JPE] and a new measure: phase lag time [PLT]) can detect early-stage AD pathophysiology.
UNASSIGNED: The activity dependent degeneration model replicates spectral changes in line with clinical data and demonstrates increasing NH. Compared to relative theta power as a gold standard the AECc and PLI are shown to be less sensitive in detecting early-stage NH and AD-related neurophysiological abnormalities, while the JPE and the PLT show more sensitivity with excellent test characteristics.
UNASSIGNED: Novel FC measures, which are better in detecting rapid fluctuations in neural activity and connectivity, may be superior to well-known measures such as the AECc and PLI in detecting early phase neurophysiological abnormalities and in particular NH in AD. These markers could improve early diagnosis and treatment target identification.
UNASSIGNED: We aim to test the performance of different FC measures in detecting NH at the earliest stage using a computational approach.
UNASSIGNED: We use a whole brain computational model of activity dependent degeneration to simulate progressive AD pathology and NH. We investigate if and at what stage four measures of FC (amplitude envelope correlation corrected [AECc], phase lag index [PLI], joint permutation entropy [JPE] and a new measure: phase lag time [PLT]) can detect early-stage AD pathophysiology.
UNASSIGNED: The activity dependent degeneration model replicates spectral changes in line with clinical data and demonstrates increasing NH. Compared to relative theta power as a gold standard the AECc and PLI are shown to be less sensitive in detecting early-stage NH and AD-related neurophysiological abnormalities, while the JPE and the PLT show more sensitivity with excellent test characteristics.
UNASSIGNED: Novel FC measures, which are better in detecting rapid fluctuations in neural activity and connectivity, may be superior to well-known measures such as the AECc and PLI in detecting early phase neurophysiological abnormalities and in particular NH in AD. These markers could improve early diagnosis and treatment target identification.
摘要：
■越来越多的动物和临床研究证据表明，网络过度兴奋（NH）可能是早期阿尔茨海默病（AD）的重要病理生理过程和潜在治疗目标。功能性连通性(FC)的测量已被提出作为NH的有希望的生物标志物，但尚不清楚哪种测量对兴奋/抑制平衡的早期变化具有最高的敏感性。
■我们旨在使用计算方法测试不同FC措施在最早阶段检测NH的性能。
■我们使用活动依赖性变性的全脑计算模型来模拟进行性AD病理和NH。我们研究了FC的四种测量是否以及在什么阶段(振幅包络相关性校正[AECc]，相位滞后指数[PLI]，联合排列熵[JPE]和一种新的度量：相位滞后时间[PLT]）可以检测早期AD病理生理学。
■活性依赖性变性模型复制了与临床数据一致的光谱变化，并显示出NH增加。与作为金标准的相对θ功率相比，AECc和PLI在检测早期NH和AD相关的神经生理异常方面的敏感性较低。而JPE和PLT显示出更高的灵敏度和优异的测试特性。
■新的FC措施，更好地检测神经活动和连通性的快速波动，在检测早期神经生理异常，特别是AD中的NH方面，可能优于众所周知的措施，例如AECc和PLI。这些标记物可以改善早期诊断和治疗目标识别。
■我们旨在使用计算方法测试不同FC措施在最早阶段检测NH的性能。
■我们使用活动依赖性变性的全脑计算模型来模拟进行性AD病理和NH。我们研究了FC的四种测量是否以及在什么阶段(振幅包络相关性校正[AECc]，相位滞后指数[PLI]，联合排列熵[JPE]和一种新的度量：相位滞后时间[PLT]）可以检测早期AD病理生理学。
■活性依赖性变性模型复制了与临床数据一致的光谱变化，并显示出NH增加。与作为金标准的相对θ功率相比，AECc和PLI在检测早期NH和AD相关的神经生理异常方面的敏感性较低。而JPE和PLT显示出更高的灵敏度和优异的测试特性。
■新的FC措施，更好地检测神经活动和连通性的快速波动，在检测早期神经生理异常，特别是AD中的NH方面，可能优于众所周知的措施，例如AECc和PLI。这些标记物可以改善早期诊断和治疗目标识别。
