Despite the acceleration of knowledge and data accumulation in neuroscience over the last years, the highly prevalent neurodegenerative disease of AD remains a growing problem. Alzheimer's Disease (AD) is the most common cause of dementia and represents the most prevalent neurodegenerative disease. For AD, disease-modifying treatments are presently lacking, and the understanding of disease mechanisms continues to be incomplete. In the present review, we discuss candidate contributing factors leading to AD, and evaluate novel computational brain simulation methods to further disentangle their potential roles. We first present an overview of existing computational models for AD that aim to provide a mechanistic understanding of the disease. Next, we outline the potential to link molecular aspects of neurodegeneration in AD with large-scale brain network modeling using The Virtual Brain (www.thevirtualbrain.org), an open-source, multiscale, whole-brain simulation neuroinformatics platform. Finally, we discuss how this methodological approach may contribute to the understanding, improved diagnostics, and treatment optimization of AD.

中文翻译：

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在阿尔茨海默氏病中架起桥梁：使用虚拟大脑进行大脑模拟的生物学框架

尽管近年来神经科学领域的知识和数据积累不断增长，但高度流行的AD神经退行性疾病仍然是一个日益严重的问题。阿尔茨海默氏病（AD）是痴呆症最常见的病因，代表最普遍的神经退行性疾病。对于AD，目前缺乏改善疾病的疗法，并且对疾病机理的理解仍然不完全。在本综述中，我们讨论了导致AD的候选贡献因素，并评估了新型的计算机模拟大脑方法，以进一步弄清它们的潜在作用。我们首先介绍现有的AD计算模型，以提供对该疾病的机械理解。下一个，我们概述了使用虚拟大脑（www.thevirtualbrain.org）（一种开放源代码，多尺度，全大脑模拟神经信息平台）将大规模神经网络建模与AD中神经变性的分子方面联系起来的潜力。最后，我们讨论了这种方法论方法如何有助于对AD的理解，改进的诊断和治疗优化。