认知
功能磁共振成像
多元统计
脑磁图
认知心理学
心理学
神经影像学
多元分析
社会认知
感知
计算机科学
脑电图
机器学习
神经科学
作者
Marius V. Peelen,Paul E. Downing
标识
DOI:10.31234/osf.io/rhzt9
摘要
Multivariate pattern analysis (MVPA) has emerged as a powerful method for the analysis of functional magnetic resonance imaging, electroencephalography and magnetoencephalography data. The new approaches to experimental design and hypothesis testing afforded by MVPA have made it possible to address theories that describe cognition at the functional level. Here we review a selection of studies that have used MVPA to test cognitive theories from a range of domains, including perception, attention, memory, navigation, emotion, social cognition and motor control. This broad view reveals properties of MVPA that make it suitable for understanding the ‘how’ of human cognition, such as the ability to test predictions expressed at the item or event level. It also reveals limitations and points to future directions.
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