Multivariate analysis of brain activity patterns as a tool to understand predictive processes in speech perception

Speech perception is heavily influenced by our expectations about what will be said. In this review, we discuss the potential of multivariate analysis as a tool to understand the neural mechanisms underlying predictive processes in speech perception. First, we discuss the advantages of multivariate approaches and what they have added to the understanding of speech processing from the acoustic-phonetic form of speech, over syllable identity and syntax, to its semantic content. Second, we suggest that using multivariate techniques to measure informational content across the hierarchically organised speech-sensitive brain areas might enable us to specify the mechanisms by which prior knowledge and sensory speech signals are combined. Specifically, this approach might allow us to decode how different priors, e.g. about a speaker's voice or about the topic of the current conversation, are represented at different processing stages and how incoming speech is as a result differently represented.