RESEARCH ARTICLE Decoding Multiple Sound Categories in the Human Temporal Cortex Using High Resolution fMRI

Perception of sound categories is an important aspect of auditory perception. The extent to which the brain’s representation of sound categories is encoded in specialized subregions or distributed across the auditory cortex remains unclear. Recent studies using multivariate pat-tern analysis (MVPA) of brain activations have provided important insights into how the brain decodes perceptual information. In the large existing literature on brain decoding using MVPAmethods, relatively few studies have been conducted onmulti-class categorization in the auditory domain. Here, we investigated the representation and processing of auditory cat-egories within the human temporal cortex using high resolution fMRI and MVPAmethods. More importantly, we considered decoding multiple sound categories simultaneously through multi-class support vector machine-recursive feature elimination (MSVM-RFE) as our MVPA tool. Results show that for all classifications the model MSVM-RFEwas able to learn the func-tional relation between the multiple sound categories and the corresponding evoked spatial patterns and classify the unlabeled sound-evoked patterns significantly above chance. This indicates the feasibility of decoding multiple sound categories not only within but across sub