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  1. The uncanny advantage of using androids in cognitive and social science research.Karl F. MacDorman & Hiroshi Ishiguro - 2006 - Interaction Studies. Social Behaviour and Communication in Biological and Artificial Systemsinteraction Studies / Social Behaviour and Communication in Biological and Artificial Systemsinteraction Studies 7 (3):297-337.
    The development of robots that closely resemble human beings can contribute to cognitive research. An android provides an experimental apparatus that has the potential to be controlled more precisely than any human actor. However, preliminary results indicate that only very humanlike devices can elicit the broad range of responses that people typically direct toward each other. Conversely, to build androids capable of emulating human behavior, it is necessary to investigate social activity in detail and to develop models of the cognitive (...)
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  • Empirical evaluation of the uncanny valley hypothesis fails to confirm the predicted effect of motion.Lukasz Piwek, Lawrie S. McKay & Frank E. Pollick - 2014 - Cognition 130 (3):271-277.
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  • Putting yourself in the skin of a black avatar reduces implicit racial bias.Tabitha C. Peck, Sofia Seinfeld, Salvatore M. Aglioti & Mel Slater - 2013 - Consciousness and Cognition 22 (3):779-787.
    Although it has been shown that immersive virtual reality can be used to induce illusions of ownership over a virtual body , information on whether this changes implicit interpersonal attitudes is meager. Here we demonstrate that embodiment of light-skinned participants in a dark-skinned VB significantly reduced implicit racial bias against dark-skinned people, in contrast to embodiment in light-skinned, purple-skinned or with no VB. 60 females participated in this between-groups experiment, with a VB substituting their own, with full-body visuomotor synchrony, reflected (...)
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  • Psychophysical and cognitive aspects of categorical perception:A critical overview.Stevan Harnad - unknown
    There are many entry points into the problem of categorization. Two particularly important ones are the so-called top-down and bottom-up approaches. Top-down approaches such as artificial intelligence begin with the symbolic names and descriptions for some categories already given; computer programs are written to manipulate the symbols. Cognitive modeling involves the further assumption that such symbol-interactions resemble the way our brains do categorization. An explicit expectation of the top-down approach is that it will eventually join with the bottom-up approach, which (...)
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  • Unconscious facial reactions to emotional facial expressions.U. Dimberg, M. Thunberg & K. Elmehed - 2000 - Psychological Science 11 (1):86-89.
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  • From presence to consciousness through virtual reality.Maria V. Sanchez-Vives & Mel Slater - 2005 - Nature Reviews Neuroscience 6 (4):332-339.
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  • Categorical Perception of Facial Expressions: Categories and their Internal Structure.Beatrice de Gelder, Jan-Pieter Teunisse & Philip J. Benson - 1997 - Cognition and Emotion 11 (1):1-23.
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  • Rejoinder - Bimodal emotion perception: integration across separate modalities, cross-modal perceptual grouping or perception of multimodal events?Beatrice de Gelder & Jean Vroomen - 2000 - Cognition and Emotion 14 (3):321-324.
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  • The perception of emotions by ear and by eye.Beatrice de Gelder & Jean Vroomen - 2000 - Cognition and Emotion 14 (3):289-311.
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  • The discrimination of speech sounds within and across phoneme boundaries.Alvin M. Liberman, Katherine Safford Harris, Howard S. Hoffman & Belver C. Griffith - 1957 - Journal of Experimental Psychology 54 (5):358.
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  • Interoceptive inference, emotion, and the embodied self.Anil K. Seth - 2013 - Trends in Cognitive Sciences 17 (11):565-573.
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  • Facial mimicry and the mirror neuron system: simultaneous acquisition of facial electromyography and functional magnetic resonance imaging.Katja U. Likowski, Andreas Mühlberger, Antje B. M. Gerdes, Matthias J. Wieser, Paul Pauli & Peter Weyers - 2012 - Frontiers in Human Neuroscience 6.
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  • The influence of categories on perception: Explaining the perceptual magnet effect as optimal statistical inference.Naomi H. Feldman, Thomas L. Griffiths & James L. Morgan - 2009 - Psychological Review 116 (4):752-782.
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