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Abstract：
BACKGROUND: Alzheimer\'s disease (AD) and frontotemporal dementia (FTD) are the two most common neurodegenerative dementias, presenting with similar clinical features that challenge accurate diagnosis. Despite extensive research, the underlying pathophysiological mechanisms remain unclear, and effective treatments are limited. This study aims to investigate the alterations in brain network connectivity associated with AD and FTD to enhance our understanding of their pathophysiology and establish a scientific foundation for their diagnosis and treatment.
METHODS: We analyzed preprocessed electroencephalogram (EEG) data from the OpenNeuro public dataset, comprising 36 patients with AD, 23 patients with FTD, and 29 healthy controls (HC). Participants were in a resting state with eyes closed. We estimated the average functional connectivity using the Phase Lag Index (PLI) for lower frequencies (delta and theta) and the Amplitude Envelope Correlation with leakage correction (AEC-c) for higher frequencies (alpha, beta, and gamma). Graph theory was applied to calculate topological parameters, including mean node degree, clustering coefficient, characteristic path length, global and local efficiency. A permutation test was then utilized to assess changes in brain network connectivity in AD and FTD based on these parameters.
RESULTS: Both AD and FTD patients showed increased mean PLI values in the theta frequency band, along with increases in average node degree, clustering coefficient, global efficiency, and local efficiency. Conversely, mean AEC-c values in the alpha frequency band were notably diminished, which was accompanied by decreases average node degree, clustering coefficient, global efficiency, and local efficiency. Furthermore, AD patients in the occipital region showed an increase in theta band node degree and decreased alpha band clustering coefficient and local efficiency, a pattern not observed in FTD.
CONCLUSIONS: Our findings reveal distinct abnormalities in the functional network topology and connectivity in AD and FTD, which may contribute to a better understanding of the pathophysiological mechanisms of these diseases. Specifically, patients with AD demonstrated a more widespread change in functional connectivity, while those with FTD retained connectivity in the occipital lobe. These observations could provide valuable insights for developing electrophysiological markers to differentiate between the two diseases.
METHODS: We analyzed preprocessed electroencephalogram (EEG) data from the OpenNeuro public dataset, comprising 36 patients with AD, 23 patients with FTD, and 29 healthy controls (HC). Participants were in a resting state with eyes closed. We estimated the average functional connectivity using the Phase Lag Index (PLI) for lower frequencies (delta and theta) and the Amplitude Envelope Correlation with leakage correction (AEC-c) for higher frequencies (alpha, beta, and gamma). Graph theory was applied to calculate topological parameters, including mean node degree, clustering coefficient, characteristic path length, global and local efficiency. A permutation test was then utilized to assess changes in brain network connectivity in AD and FTD based on these parameters.
RESULTS: Both AD and FTD patients showed increased mean PLI values in the theta frequency band, along with increases in average node degree, clustering coefficient, global efficiency, and local efficiency. Conversely, mean AEC-c values in the alpha frequency band were notably diminished, which was accompanied by decreases average node degree, clustering coefficient, global efficiency, and local efficiency. Furthermore, AD patients in the occipital region showed an increase in theta band node degree and decreased alpha band clustering coefficient and local efficiency, a pattern not observed in FTD.
CONCLUSIONS: Our findings reveal distinct abnormalities in the functional network topology and connectivity in AD and FTD, which may contribute to a better understanding of the pathophysiological mechanisms of these diseases. Specifically, patients with AD demonstrated a more widespread change in functional connectivity, while those with FTD retained connectivity in the occipital lobe. These observations could provide valuable insights for developing electrophysiological markers to differentiate between the two diseases.
摘要：
背景：阿尔茨海默病（AD）和额颞叶痴呆（FTD）是两种最常见的神经退行性痴呆，具有相似的临床特征，挑战准确的诊断。尽管进行了广泛的研究,潜在的病理生理机制尚不清楚，有效的治疗方法是有限的。这项研究旨在研究与AD和FTD相关的大脑网络连接变化，以增强我们对其病理生理学的理解，并为其诊断和治疗奠定科学基础。
方法：我们分析了来自OpenNeuro公共数据集的预处理的脑电图（EEG）数据，包括36名AD患者，23名FTD患者，和29名健康对照（HC）。参与者处于闭眼休息状态。我们使用较低频率（delta和theta）的相位滞后指数（PLI）和较高频率（alpha，beta,和伽马）。应用图论计算拓扑参数,包括平均节点度，聚类系数，特征路径长度,全球和地方效率。然后基于这些参数利用置换测试来评估AD和FTD中脑网络连接的变化。
结果：AD和FTD患者在theta频段显示平均PLI值增加，随着平均节点度的增加，聚类系数，全球效率，本地效率。相反，Alpha频段的平均AEC-c值明显减弱，伴随着平均节点度的降低，聚类系数，全球效率，本地效率。此外，AD患者在枕区表现出θ带节点程度的增加和α带聚集系数和局部效率的降低,在FTD中未观察到的模式。
结论：我们的发现揭示了AD和FTD中功能网络拓扑和连通性的明显异常，这可能有助于更好地理解这些疾病的病理生理机制。具体来说,AD患者表现出更广泛的功能连接变化，而FTD保留了枕叶的连通性。这些观察结果可以为开发电生理标志物以区分两种疾病提供有价值的见解。
方法：我们分析了来自OpenNeuro公共数据集的预处理的脑电图（EEG）数据，包括36名AD患者，23名FTD患者，和29名健康对照（HC）。参与者处于闭眼休息状态。我们使用较低频率（delta和theta）的相位滞后指数（PLI）和较高频率（alpha，beta,和伽马）。应用图论计算拓扑参数,包括平均节点度，聚类系数，特征路径长度,全球和地方效率。然后基于这些参数利用置换测试来评估AD和FTD中脑网络连接的变化。
结果：AD和FTD患者在theta频段显示平均PLI值增加，随着平均节点度的增加，聚类系数，全球效率，本地效率。相反，Alpha频段的平均AEC-c值明显减弱，伴随着平均节点度的降低，聚类系数，全球效率，本地效率。此外，AD患者在枕区表现出θ带节点程度的增加和α带聚集系数和局部效率的降低,在FTD中未观察到的模式。
结论：我们的发现揭示了AD和FTD中功能网络拓扑和连通性的明显异常，这可能有助于更好地理解这些疾病的病理生理机制。具体来说,AD患者表现出更广泛的功能连接变化，而FTD保留了枕叶的连通性。这些观察结果可以为开发电生理标志物以区分两种疾病提供有价值的见解。
