Impact of emotional valence on mismatch negativity in the course of cortical face processing.

Various aspects of cortical face processing have been studied by assessing event related potentials (ERP). It has been described in the literature that mismatch negativity (MMN), a well-studied ERP, is not only modulated by sensory features but also emotional valence. However, the exact impact of emotion on the temporo-spatial profile of visual MMN during face processing remains inconsistent. By employing a sequential oddball paradigm using both neutral and emotional deviants, we were able to differentiate two distinct vMMN subcomponents. While an early subcomponent at 150-250 ms is elicited by emotional salient facial stimuli, the later subcomponent at 250-400 ms seems to reflect the detection of regularity violations in facial recognition per se, unaffected by emotional salience. Our results suggest that emotional valence is encoded in vMMN signal strength at an early stage of facial processing. Furthermore, we assume that of facial processing consists of temporo-spatially distinct, partially overlapping levels concerning different facial aspects.

Portrayed emotions in the movie "Forrest Gump".

Here we present a dataset with a description of portrayed emotions in the movie "Forrest Gump". A total of 12 observers independently annotated emotional episodes regarding their temporal location and duration. The nature of an emotion was characterized with basic attributes, such as arousal and valence, as well as explicit emotion category labels. In addition, annotations include a record of the perceptual evidence for the presence of an emotion. Two variants of the movie were annotated separately: 1) an audio-movie version of Forrest Gump that has been used as a stimulus for the acquisition of a large public functional brain imaging dataset, and 2) the original audio-visual movie. We present reliability and consistency estimates that suggest that both stimuli can be used to study visual and auditory emotion cue processing in real-life like situations. Raw annotations from all observers are publicly released in full in order to maximize their utility for a wide range of applications and possible future extensions. In addition, aggregate time series of inter-observer agreement with respect to particular attributes of portrayed emotions are provided to facilitate adoption of these data.