@article{CheethamWuPaulietal.2015,
  author    = {Cheetham, Marcus and Wu, Lingdan and Pauli, Paul and Jancke, Lutz},
  title     = {Arousal, valence, and the uncanny valley: psychophysiological and self-report findings},
  series = {Frontiers in Psychology},
  volume    = {6},
  journal   = {Frontiers in Psychology},
  number    = {981},
  doi       = {10.3389/fpsyg.2015.00981},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-151519},
  year      = {2015},
  abstract  = {The main prediction of the Uncanny Valley Hypothesis (UVH) is that observation of humanlike characters that are difficult to distinguish from the human counterpart will evoke a state of negative affect. Well-established electrophysiological [late positive potential (LPP) and facial electromyography (EMG)] and self-report [Self-Assessment Manikin (SAM)] indices of valence and arousal, i.e., the primary orthogonal dimensions of affective experience, were used to test this prediction by examining affective experience in response to categorically ambiguous compared with unambiguous avatar and human faces (N = 30). LPP and EMG provided direct psychophysiological indices of affective state during passive observation and the SAM provided self-reported indices of affective state during explicit cognitive evaluation of static facial stimuli. The faces were drawn from well-controlled morph continua representing the UVH' dimension of human likeness (DHL). The results provide no support for the notion that category ambiguity along the DHL is specifically associated with enhanced experience of negative affect. On the contrary, the LPP and SAM-based measures of arousal and valence indicated a general increase in negative affective state (i.e., enhanced arousal and negative valence) with greater morph distance from the human end of the DHL. A second sample (N = 30) produced the same finding, using an ad hoc self-rating scale of feelings of familiarity, i.e., an oft-used measure of affective experience along the UVH' familiarity dimension. In conclusion, this multi-method approach using well-validated psychophysiological and self-rating indices of arousal and valence rejects for passive observation and for explicit affective evaluation of static faces the main prediction of the UVH.},
  language  = {en}
}
@phdthesis{Anderson2011,
  author    = {Anderson, Christina},
  title     = {Idiosyncratic Facial Movement in Face Perception and Recognition},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-70355},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2011},
  abstract  = {It has been proposed that different features of a face provide a source of information for separate perceptual and cognitive processes. Properties of a face that remain rather stable over time, so called invariant facial features, yield information about a face's identity, and changeable aspects of faces transmit information underlying social communication such as emotional expressions and speech movements. While processing of these different face properties was initially claimed to be independent, a growing body of evidence suggests that these sources of information can interact when people recognize faces with whom they are familiar. This is the case because the way a face moves can contain patterns that are characteristic for that specific person, so called idiosyncratic movements. As a face becomes familiar these idiosyncratic movements are learned and hence also provide information serving face identification. While an abundance of experiments has addressed the independence of invariant and variable facial features in face recognition, little is known about the exact nature of the impact idiosyncratic facial movements have on face recognition. Gaining knowledge about the way facial motion contributes to face recognition is, however, important for a deeper understanding of the way the brain processes and recognizes faces. In the following dissertation three experiments are reported that investigate the impact familiarity of changeable facial features has on processes of face recognition. Temporal aspects of the processing of familiar idiosyncratic facial motion were addressed in the first experiment via EEG by investigating the influence familiar facial movement exerts on event-related potentials associated to face processing and face recognition. After being familiarized with a face and its idiosyncratic movement, participants viewed familiar or unfamiliar faces with familiar or unfamiliar facial movement while their brain potentials were recorded. Results showed that familiarity of facial motion influenced later event-related potentials linked to memory processes involved in face recognition. The second experiment used fMRI to investigate the brain areas involved in processing familiar facial movement. Participants' BOLD-signal was registered while they viewed familiar and unfamiliar faces with familiar or unfamiliar idiosyncratic movement. It was found that activity of brain regions, such as the fusiform gyrus, that underlie the processing of face identity, was modulated by familiar facial movement. Together these two experiments provide valuable information about the nature of the involvement of idiosyncratic facial movement in face recognition and have important implications for cognitive and neural models of face perception and recognition. The third experiment addressed the question whether idiosyncratic facial movement could increase individuation in perceiving faces from a different ethnic group and hence reduce impaired recognition of these other-race faces compared to own-race faces, a phenomenon named the own-race bias. European participants viewed European and African faces that were each animated with an idiosyncratic smile while their attention was either directed to the form or the motion of the face. Subsequently recognition memory for these faces was tested. Results showed that the own-race bias was equally present in both attention conditions indicating that idiosyncratic facial movement was not able to reduce or diminish the own-race bias. In combination the here presented experiments provide further insight into the involvement of idiosyncratic facial motion in face recognition. It is necessary to consider the dynamic component of faces when investigating face recognition because static facial images are not able to provide the full range of information that leads to recognition of a face. In order to reflect the full process of face recognition, cognitive and neural models of face perception and recognition need to integrate dynamic facial features as a source of information which contributes to the recognition of a face.},
  subject      = {Gesicht},
  language  = {en}
}