Brain activity was monitored while participants viewed picture sets that reflected high or low levels of arousal and positive, neutral, or negative valence. Pictures within a set were presented rapidly in an incidental viewing task while fMRI data were collected. The primary purpose of the study was to determine if multi-voxel pattern analysis could be used within and between participants to predict valence, arousal and combined affective states elicited by pictures based on distributed patterns of whole brain activity. A secondary purpose was to determine if distributed patterns of whole brain activity can be used to derive a lower dimensional representation of affective states consistent with behavioral data. Results demonstrated above chance prediction of valence, arousal and affective states that was robust across a wide range of number of voxels used in prediction. Additionally, individual differences multidimensional scaling based on fMRI data clearly separated valence and arousal levels and was consistent with a circumplex model of affective states.
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