Bridging Scales in Alzheimer's Disease: Biological Framework for Brain Simulation With The Virtual Brain

被引:24
|
作者
Stefanovski, Leon [1 ,2 ,3 ,4 ]
Meier, Jil Mona [1 ,2 ,3 ,4 ]
Pai, Roopa Kalsank [1 ,2 ,3 ,4 ,5 ]
Triebkorn, Paul [1 ,2 ,3 ,4 ,6 ]
Lett, Tristram [1 ,2 ,3 ,4 ]
Martin, Leon [1 ,2 ,3 ,4 ]
Buelau, Konstantin [1 ,2 ,3 ,4 ]
Hofmann-Apitius, Martin [7 ]
Solodkin, Ana [8 ]
McIntosh, Anthony Randal [9 ]
Ritter, Petra [1 ,2 ,3 ,4 ,5 ,10 ,11 ]
机构
[1] Charite, Berlin Inst Hlth, Berlin, Germany
[2] Charite, Berlin, Germany
[3] Free Univ Berlin, Berlin, Germany
[4] Humboldt Univ, Dept Neurol Expt Neurol, Brain Simulat Sect, Berlin, Germany
[5] Bernstein Ctr Computat Neurosci Berlin, Berlin, Germany
[6] Aix Marseille Univ, Inst Neurosci Syst, Marseille, France
[7] Fraunhofer Inst Algorithms & Sci Comp SCAI, St Augustin, Germany
[8] Univ Texas Dallas, Behav & Brain Sci, Dallas, TX USA
[9] Rotman Res Inst, Baycrest Hlth Sci, Toronto, ON, Canada
[10] Einstein Ctr Neurosci Berlin, Berlin, Germany
[11] Einstein Ctr Digital Future, Berlin, Germany
基金
欧洲研究理事会; 欧盟地平线“2020”;
关键词
Alzheimer's disease; The Virtual Brain; brain simulation; multi-scale brain modeling; connectomics; MILD COGNITIVE IMPAIRMENT; MEDIAL TEMPORAL-LOBE; NERVE GROWTH-FACTOR; DISRUPTED FUNCTIONAL CONNECTIVITY; CEREBROSPINAL-FLUID BIOMARKERS; WHITE-MATTER HYPERINTENSITIES; ENCAPSULATED CELL BIODELIVERY; POSITRON-EMISSION-TOMOGRAPHY; GRAPH-THEORETICAL ANALYSIS; RESTING-STATE NETWORKS;
D O I
10.3389/fninf.2021.630172
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
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 (), 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.
引用
收藏
页数:30
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