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：

---

阿尔茨海默病的桥接尺度：使用虚拟大脑进行大脑模拟的生物框架


尽管过去几年神经​​科学的知识和数据积累加速，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）是痴呆症最常见的原因，也是最常见的神经退行性疾病。对于 AD，目前缺乏缓解疾病的治疗方法，并且对疾病机制的了解仍然不完整。在本综述中，我们讨论了导致 AD 的候选因素，并评估了新颖的计算大脑模拟方法，以进一步阐明其潜在作用。我们首先概述现有的 AD 计算模型，旨在提供对该疾病的机制理解。接下来，我们概述了使用虚拟大脑 (www.thevirtualbrain.org)（一个开源、多尺度、全脑模拟神经信息学平台）将 AD 神经退行性变的分子方面与大规模脑网络建模联系起来的潜力。最后，我们讨论这种方法如何有助于 AD 的理解、改进诊断和优化治疗。