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Emerging Frontiers of Neuroengineering: A Network Science of Brain Connectivity.
Annual Review of Biomedical Engineering ( IF 9.7 ) Pub Date : 2017-03-27 , DOI: 10.1146/annurev-bioeng-071516-044511
Danielle S Bassett 1, 2 , Ankit N Khambhati 1 , Scott T Grafton 3, 4
Affiliation  

Neuroengineering is faced with unique challenges in repairing or replacing complex neural systems that are composed of many interacting parts. These interactions form intricate patterns over large spatiotemporal scales and produce emergent behaviors that are difficult to predict from individual elements. Network science provides a particularly appropriate framework in which to study and intervene in such systems by treating neural elements (cells, volumes) as nodes in a graph and neural interactions (synapses, white matter tracts) as edges in that graph. Here, we review the emerging discipline of network neuroscience, which uses and develops tools from graph theory to better understand and manipulate neural systems from micro- to macroscales. We present examples of how human brain imaging data are being modeled with network analysis and underscore potential pitfalls. We then highlight current computational and theoretical frontiers and emphasize their utility in informing diagnosis and monitoring, brain-machine interfaces, and brain stimulation. A flexible and rapidly evolving enterprise, network neuroscience provides a set of powerful approaches and fundamental insights that are critical for the neuroengineer's tool kit.

中文翻译:

神经工程学的新兴前沿:大脑连通性的网络科学。

在修复或替换由许多相互作用部分组成的复杂神经系统时,神经工程学面临着独特的挑战。这些相互作用在较大的时空尺度上形成了复杂的模式,并产生了难以从单个元素上预测的突发行为。网络科学提供了一个特别合适的框架,可以在其中研究和干预此类系统,方法是将神经元(细胞,体积)视为图中的节点,并将神经交互作用(突触,白质束)视为图中的边缘。在这里,我们回顾了网络神经科学的新兴学科,该学科使用和开发了基于图论的工具,以更好地理解和操纵从微观到宏观的神经系统。我们提供了一些示例,说明如何通过网络分析对人脑成像数据进行建模并强调潜在的陷阱。然后,我们重点介绍当前的计算和理论前沿,并强调它们在通知诊断和监测,脑机接口以及脑部刺激方面的效用。作为一个灵活且迅速发展的企业,网络神经科学提供了一组强大的方法和基本见解,这些对神经工程师的工具包至关重要。
更新日期:2017-06-20
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