The uncanny valley hypothesis, proposed already in the 1970s, suggests that almost but not fully humanlike artificial characters will trigger a profound sense of unease. This hypothesis has become widely acknowledged both in the popular media and scientific research. Surprisingly, empirical evidence for the hypothesis has remained inconsistent. In the present article, we reinterpret the original uncanny valley hypothesis and review empirical evidence for different theoretically motivated uncanny valley hypotheses. The uncanny valley could be understood as the naïve claim that any kind of human-likeness manipulation will lead to experienced negative affinity at close-to-realistic levels. More recent hypotheses have suggested that the uncanny valley would be caused by artificial–human categorization difficulty or by a perceptual mismatch between artificial and human features. Original formulation also suggested that movement would modulate the uncanny valley. The reviewed empirical literature failed to provide consistent support for the naïve uncanny valley hypothesis or the modulatory effects of movement. Results on the categorization difficulty hypothesis were still too scarce to allow drawing firm conclusions. In contrast, good support was found for the perceptual mismatch hypothesis. Taken together, the present review findings suggest that the uncanny valley exists only under specific conditions. More research is still needed to pinpoint the exact conditions under which the uncanny valley phenomenon manifests itself.

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Dyadic gaming experience was studied in a psychophysiological experiment where conflict structure and the presence of an artificial intelligence (AI) agent in a turnbased game were varied in four different conditions. Electrocardiographic and electrodermal activity signals of 41 same-gender dyads were recorded to study joint changes in their physiological signals. A strong physiological linkage was found within dyads in all conditions, but the linkage scores did not differentiate between conflict modes. The only significant difference in linkage between conditions was an increase when the AI agents were not present. In addition, linkage was associated with different self-report scales assessing social presence. These results suggest that social presence and physiological linkage within dyads are higher when dyads can focus on each others' actions without distractions.

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Winning against an opponent in a competitive video game can be expected to be more rewarding than losing, especially when the opponent is a fellow human player rather than a computer. We show that winning versus losing in a first-person video game activates the brain's reward circuit and the ventromedial prefrontal cortex (vmPFC) differently depending on the type of the opponent. Participants played a competitive tank shooter game against alleged human and computer opponents while their brain activity was measured with functional magnetic resonance imaging. Brain responses to wins and losses were contrasted by fitting an event-related model to the hemodynamic data. Stronger activation to winning was observed in ventral and dorsal striatum as well as in vmPFC. Activation in ventral striatum was associated with participants' self-ratings of pleasure. During winning, ventral striatum showed stronger functional coupling with right insula, and weaker coupling with dorsal striatum, sensorimotor pre- and postcentral gyri, and visual association cortices. The vmPFC and dorsal striatum responses were stronger to winning when the subject was playing against a human rather than a computer. These results highlight the importance of social context in the neural encoding of reward value.