Reading the brain visual system as an inverse problem

Standard inference in neuroimaging consists in describing brain activations elicited and modulated by different kinds of stimuli. Recently however, paradigms have been studied in which the converse operation is performed, thus inferring behavioral or mental states associated with activation images. Here, we use the well-known retinotopy of the visual cortex to infer the visual content of real scenes from the activation patterns that they elicit. We present an explicit decoding technique, based on the current knowledge of the retinotopic structure of the visual areas. Our algorithm can predict the stimulus identity with significant accuracy