Finding decodable information that can be read out in behaviour.

Multivariate decoding methods applied to neuroimaging data have become the standard in cognitive neuroscience for unravelling statistical dependencies between brain activation patterns and experimental conditions. The current challenge is to demonstrate that decodable information is in fact used by the brain itself to guide behaviour. Here we demonstrate a promising approach to do so in the context of neural activation during object perception and categorisation behaviour. We first localised decodable information about visual objects in the human brain using a multivariate decoding analysis and a spatially-unbiased searchlight approach. We then related brain activation patterns to behaviour by testing whether the classifier used for decoding can be used to predict behaviour. We show that while there is decodable information about visual category throughout the visual brain, only a subset of those representations predicted categorisation behaviour, which were strongest in anterior ventral temporal cortex. Our results have important implications for the interpretation of neuroimaging studies, highlight the importance of relating decoding results to behaviour, and suggest a suitable methodology towards this aim.