This paper reports on the results of a long-term experiment in which a social robot's facial expressions were changed to reflect di#erent moods. While the facial changes in each condition were not extremely di#erent, they still altered how people interacted with the robot. On days when many visitors were present, average interactions with the robot were longer when the robot displayed either a "happy" or a "sad" expression instead of a neutral face, but the opposite was true for low-visitor days. The implications of these findings for human-robot social interaction are discussed.

Recognizing emotion from facial expressions draws on diverse psychological processes implemented in a large array of neural structures. Studies using evoked potentials, lesions, and functional imaging have begun to elucidate some of the mechanisms. Early perceptual processing of faces draws on cortices in occipital and temporal lobes that construct detailed representations from the configuration of facial features. Subsequent recognition requires a set of structures, including amygdala and orbitofrontal cortex, that links perceptual representations of the face to the generation of knowledge about the emotion signaled, a complex set of mechanisms using multiple strategies. Although recent studies have provided a wealth of detail regarding these mechanisms in the adult human brain, investigations are also being extended to nonhuman primates, to infants, and to patients with psychiatric disorders.

Abstract—This research began with a preliminary exploratory study that observed the relationship between the facial expressions of three human lecturers in a real academic lecture theatre and the reactions of the students to those expressions. Results informed the design of the first experiment that aimed to investigate the effectiveness of a virtual lecturer’s expressions on the students ’ learning outcomes in a virtual pedagogical environment. A second follow-up experiment then focussed on the effectiveness of a single facial expression (the smile) on student performance. Both experiments involved virtual lectures, with virtual lecturers teaching real students. Results indicated that students performed better (by 86%) in the lectures where the virtual lecturer performed facial expressions compared to the results of the lectures that did not use facial expressions. However, this applied only for reasonably complex instructional material; when simple or basic instructional material was used the facial expressions of the virtual lecturer had no substantial effect on the students ’ learning outcome. Finally, it was demonstrated that the appropriate use of smiling increased the interest of the students and consequently their performance. Index Terms—Emotion, facial expression, smile, virtual educational environment, avatar, agent, virtual lecturer. I.

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Prior studies have demonstrated that both nicotine administration and cigarette smoking lead to dopamine (DA) release in the ventral striatum/nucleus accumbens. In tobacco-dependent individuals, smoking denicotinized cigarettes leads to reduced craving, but less pleasure, than smoking regular cigarettes. Using denicotinized cigarettes and 11 C-raclopride positron emission tomography (PET) scanning, we sought to determine if nicotine is necessary for smoking-induced DA release. Sixty-two tobacco-dependent smokers underwent 11 C-raclopride PET scanning, during which they smoked either a regular or denicotinized cigarette (double-blind). Change in 11 C-raclopride binding potential (BP) in the ventral striatum from before to after smoking was determined as an indirect measure of DA release. Cigarette craving, anxiety, and mood were monitored during scanning. Smoking a regular cigarette resulted in a significantly greater mean reduction in ventral striatal 11 C-raclopride BP than smoking a denicotinized cigarette. Although both groups had reductions in craving and anxiety with smoking, the regular cigarette group had a greater improvement in mood. For the total group, change in BP correlated inversely with change in mood, indicating that greater smoking-induced DA release was associated with more smoking-related mood improvement. Thus, nicotine delivered through cigarette smoking appears to be important for ventral striatal DA release. Study findings also suggest that mood improvement from smoking is specifically related to ventral striatal DA release.

Some documents provoke emotions in people viewing them. Will it be possible to describe emotions consistently and use this information in retrieval systems? We tested collective (statistically aggregated) emotion indexing using images as examples. Considering psychological results, basic emotions are anger, disgust, fear, happiness, and sadness. This study follows an approach developed by Lee and Neal (2007) for music emotion retrieval and applies scroll bars for tagging basic emotions and their intensities. A sample comprising 763 persons tagged emotions caused by images (retrieved from www.Flickr.com) applying scroll bars and (linguistic) tags. Using SPSS, we performed descriptive statistics and correlation analysis. For more than half of the images, the test persons have clear emotion favorites. There are prototypical images for given emotions. The document-specific consistency of tagging using a scroll bar is, for some images, very high. Most of the (most commonly used) linguistic tags are on the basic level (in the sense of Rosch’s basic level theory). The distributions of the linguistic tags in our examples follow an inverse power-law. Hence, it seems possible to apply collective image emotion tagging to image information systems and to present a new search option for basic emotions. This article is one of the first steps in the research area of emotional information retrieval (EmIR).