认知
计算机科学
认知科学
神经功能成像
神经科学
复杂网络
神经影像学
灵活性(工程)
背景(考古学)
人工智能
心理学
生物
古生物学
统计
数学
万维网
作者
Andrei Dragomir,L. Sirovich
标识
DOI:10.1007/978-981-16-5540-1_76
摘要
Understanding the brain's cognitive function depends on the knowledge of how neural units interconnect both locally, within distinct brain regions, and at the large scale of the whole brain. Balance between localized processing and global integration provides support for the complex processing patterns, underlying high-order cognitive function, while at the same time ensuring flexibility, robustness, and functional diversification in the brain. In this context, the network paradigm enables a theoretical framework for investigating interactions between brain regions as well as the use of powerful computational tools for interpreting the complex topology of functional networks. In this chapter we review current state of the art in studying brain functional networks and summarize methodological advances used to quantify the networks characteristics. We also overview the main neuroimaging techniques, whose data give rise to network interpretations. Further, we discuss the current knowledge on core large-scale networks involved in cognitive function and dysfunction. Overall, this chapter promotes a systematic exploration of how cognition emerges as a network phenomenon.
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