Testing cognitive theories with multivariate pattern analysis of neuroimaging data

The development of non-invasive neuroimaging techniques to measure brain activity while human participants engage in cognitive tasks has driven thousands of investigations over recent decades. This has been paralleled by advances in experimental design and analysis, including the family of approaches known as multivariate pattern analysis (MVPA). For many researchers, the increased sensitivity provided by applying MVPA to functional MRI, EEG or MEG data made it possible to address theories that describe cognition at the functional level. Here, we review a selection of studies that 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.