  Mental imagery refers to percept-like experiences in the absence of sensory
input. Brain imaging studies suggest common, modality-specific, neural
correlates imagery and perception. We associated abstract visual stimuli with
either visually presented or imagined monetary rewards and scrambled pictures.
Brain images for a group of 12 participants were collected using functional
magnetic resonance imaging. Statistical analysis showed that human midbrain
regions were activated irrespective of the monetary rewards being imagined or
visually present. A support vector machine trained on the midbrain activation
patterns to the visually presented rewards predicted with 75% accuracy whether
the participants imagined the monetary reward or the scrambled picture during
imagination trials. Training samples were drawn from visually presented trials
and classification accuracy was assessed for imagination trials. These results
suggest the use of machine learning technique for classification of underlying
cognitive states from brain imaging data.
