Bassett Danielle S, Sporns Olaf
Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Department of Electrical &Systems Engineering, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Nat Neurosci. 2017 Feb 23;20(3):353-364. doi: 10.1038/nn.4502.
Despite substantial recent progress, our understanding of the principles and mechanisms underlying complex brain function and cognition remains incomplete. Network neuroscience proposes to tackle these enduring challenges. Approaching brain structure and function from an explicitly integrative perspective, network neuroscience pursues new ways to map, record, analyze and model the elements and interactions of neurobiological systems. Two parallel trends drive the approach: the availability of new empirical tools to create comprehensive maps and record dynamic patterns among molecules, neurons, brain areas and social systems; and the theoretical framework and computational tools of modern network science. The convergence of empirical and computational advances opens new frontiers of scientific inquiry, including network dynamics, manipulation and control of brain networks, and integration of network processes across spatiotemporal domains. We review emerging trends in network neuroscience and attempt to chart a path toward a better understanding of the brain as a multiscale networked system.
尽管最近取得了重大进展,但我们对复杂大脑功能和认知背后的原理及机制的理解仍不完整。网络神经科学旨在应对这些长期存在的挑战。网络神经科学从明确的综合视角来研究大脑结构和功能,寻求新的方法来绘制、记录、分析和模拟神经生物学系统的元素及相互作用。有两个并行的趋势推动了这一方法:一是出现了新的实证工具,可用于创建综合图谱并记录分子、神经元、脑区和社会系统之间的动态模式;二是现代网络科学的理论框架和计算工具。实证和计算方面的进展相结合,开辟了科学探究的新前沿,包括网络动力学、大脑网络的操纵与控制,以及跨时空领域的网络过程整合。我们回顾了网络神经科学的新兴趋势,并试图勾勒出一条更好地将大脑理解为多尺度网络系统的路径。