连接组学
神经科学
连接体
神经病理学
计算机科学
网络拓扑
人脑
拓扑(电路)
疾病
生物
功能连接
心理学
医学
计算机网络
数学
病理
组合数学
作者
Alex Fornito,Andrew Zalesky,Michael Breakspear
摘要
Pathological perturbations of the brain are rarely confined to a single locus; instead, they often spread via axonal pathways to influence other regions. Patterns of such disease propagation are constrained by the extraordinarily complex, yet highly organized, topology of the underlying neural architecture; the so-called connectome. Thus, network organization fundamentally influences brain disease, and a connectomic approach grounded in network science is integral to understanding neuropathology. Here, we consider how brain-network topology shapes neural responses to damage, highlighting key maladaptive processes (such as diaschisis, transneuronal degeneration and dedifferentiation), and the resources (including degeneracy and reserve) and processes (such as compensation) that enable adaptation. We then show how knowledge of network topology allows us not only to describe pathological processes but also to generate predictive models of the spread and functional consequences of brain disease.
科研通智能强力驱动
Strongly Powered by AbleSci AI