连接组学
连接体
神经科学
磁共振弥散成像
病变
神经影像学
功能连接
预言
计算机科学
图论
光学(聚焦)
静息状态功能磁共振成像
心理学
认知科学
人工智能
医学
精神科
磁共振成像
物理
数据挖掘
数学
放射科
光学
组合数学
作者
Amy Kuceyeski,Aaron D. Boes
出处
期刊:Neuromethods
日期:2022-01-01
卷期号:: 149-166
被引量:2
标识
DOI:10.1007/978-1-0716-2225-4_8
摘要
Historically, topological lesion-based studies have provided a direct way to map brain regions to their corresponding functions; however, these approaches fail to consider the impact of the lesion on broader brain networks. Focus has shifted in the latter half of the nineteenth century from topological to hodological, or network-based, approaches that link networks of brain regions to function. More recent advances in neuroimaging, including diffusion and resting-state functional MRI, have begun to reveal network-behavior maps in both healthy and clinical populations. An understanding of these relationships is imperative if we are to improve diagnostics, prognostics, and treatments of neurological and neuropsychiatric disorders. In this chapter, we begin by introducing general concepts in connectomics, including graph theory and connectome imaging techniques. We then outline strategies for quantifying lesions' impact on the connectome and, finally, discuss clinical applications and possible avenues of future work.
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