Abstract
In an object-contemplation task, participants were presented with 60 line drawings of objects (e.g. hammer, dog) with text labels and were instructed to think of the same properties of the stimulus object consistently during multiple presentations of each item. Machine learning classifiers can be trained to decode mental states associated with the stimulus object, given the corresponding functional magnetic resonance imaging (fMRI) neural activity signature.

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