单变量
多元统计
功能连接
编码
心理学
多元分析
神经科学
大脑活动与冥想
神经影像学
大脑定位
计算机科学
认知心理学
生物
机器学习
脑电图
基因
生物化学
作者
Stefano Anzellotti,Marc N. Coutanche
标识
DOI:10.1016/j.tics.2017.12.002
摘要
For over two decades, interactions between brain regions have been measured in humans by asking how the univariate responses in different regions co-vary ('Functional Connectivity'). Thousands of Functional Connectivity studies have been published investigating the healthy brain and how it is affected by neural disorders. The advent of multivariate fMRI analyses showed that patterns of responses within regions encode information that is lost by averaging. Despite this, connectivity methods predominantly continue to focus on univariate responses. In this review, we discuss the recent emergence of multivariate and nonlinear methods for studying interactions between brain regions. These new developments bring sensitivity to fluctuations in multivariate information, and offer the possibility to ask not only whether brain regions interact, but how they do so.
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