vMMN for schematic faces: automatic detection of change in emotional expression

Our brain is able to automatically detect changes in sensory stimulation, including in vision. A large variety of changes of features in stimulation elicit a deviance-reflecting ERP component known as the mismatch negativity (MMN). The present study has three main goals: (1) to register vMMN using a rapidly presented stream of schematic faces (neutral, happy, angry; adapted from Öhman et al., 2001); (2) to compare elicited vMMNs to angry and happy schematic faces in two different paradigms, in a traditional oddball design with frequent standard and rare target and deviant stimuli (12.5% each) and in an version of an optimal multi-feature paradigm with several deviant stimuli (altogether 37.5%) in the stimulus block; (3) to compare vMMNs to subjective ratings of valence, arousal and attention capture for happy and angry schematic faces, i.e., to estimate the effect of affective value of stimuli on their automatic detection. Eleven observers (19-32 years, 6 women) took part in both experiments, an oddball and optimum paradigm. Stimuli were rapidly presented schematic faces and an object with face-features that served as the target stimulus to be detected by a button-press. Results show that a vMMN-type response at posterior sites was equally elicited in both experiments. Post-experimental reports confirmed that the angry face attracted more automatic attention than the happy face but the difference did not emerge directly at the ERP level. Thus, when interested in studying change detection in facial expressions we encourage the use of the optimum (multi-feature) design in order to save time and other experimental resources