Abstract — This work is concerned with a framework for visual object recognition in real world tasks. Our approach is motivated by biological findings of the representation of space around the body, the so-called peripersonal space. We show that the principles behind those findings can lead to a natural structuring of object recognition tasks in artificial systems. We demonstrate this by the supervised learning and recognition of 20 complexshaped objects from unsegmented visual input.

Gaze following is the ability to re-direct one’s gaze to the location where another agent is looking. We present a computational model of how hu-man infants or other agents may acquire gaze following by learning to pre-dict the locations of interesting sights from the looking behavior of other agents through reinforcement learning. The model accounts for many find-ings about the development of gaze following in human infants. During learning, the model develops pre-motor representations that exhibit many properties characteristic of mirror neurons, but they are specific to looking behaviors. The existence of such a new class of mirror neurons is the main prediction of our model. The model also offers a parsimonious account of how these and possibly other mirror neurons may acquire their special re-sponse properties. In this account, visual representations of other agents’ actions become associated with pre-motor neurons that represent the inten-tion to perform corresponding actions. The model also demonstrates how this development may be obstructed in autism spectrum disorder, giving rise to specific physiological and anatomical differences in the mirror system.

Observing actions and understanding sentences about actions activates corresponding motor processes in the observer–comprehender. In 5 experiments, the authors addressed 2 novel questions regarding language-based motor resonance. The 1st question asks whether visual motion that is associated with an action produces motor resonance in sentence comprehension. The 2nd question asks whether motor resonance is modulated during sentence comprehension. The authors ’ experiments provide an affirmative response to both questions. A rotating visual stimulus affects both actual manual rotation and the comprehension of manual rotation sentences. Motor resonance is modulated by the linguistic input and is a rather immediate and localized phenomenon. The results are discussed in the context of theories of action observation and mental simulation.

Computer-animated characters are common in popular culture and have begun to be used as experimental tools in social cognitive neurosciences. Here we investigated how appearance of these characters ’ influences perception of their actions. Subjects were presented with different characters animated either with motion data captured from human actors or by interpolating between poses (keyframes) designed by an animator, and were asked to categorize the motion as biological or artificial. The response bias towards ‘biological’, derived from the Signal Detection Theory, decreases with characters’ anthropomorphism, while sensitivity is only affected by the simplest rendering style, point-light displays. fMRI showed that the response bias correlates positively with activity in the mentalizing network including left temporoparietal junction and anterior cingulate cortex, and negatively with regions sustaining motor resonance. The absence of significant effect of the characters on the brain activity suggests individual differences in the neural responses to unfamiliar artificial agents. While computer-animated characters are invaluable tools to investigate the neural bases of social cognition, further research is required to better understand how factors such as anthropomorphism affect their perception, in order to optimize their appearance for entertainment, research or therapeutic purposes.

More than 50 years after the appearance of the motor theory of speech perception, it is timely to evaluate its three main claims that (1) speech processing is special, (2) perceiving speech is perceiving gestures, and (3) the motor system is recruited for perceiving speech. We argue that to the extent that it can be evaluated, the first claim is likely false. As for the second claim, we review findings that support it and argue that although each of these findings may be explained by alternative accounts, the claim provides a single coherent account. As for the third claim, we review findings in the literature that support it at different levels of generality and argue that the claim anticipated a theme that has become widespread in cognitive science.

A large volume of neurobiological research has been conducted in recent years, almost all of which has been considered solely from the perspective of biology. However, most of the insights gained through this research are also valuable for the game research field. This paper discusses the implications of existing research in neurobiology to the play of games (including, but not restricted to digital games), and connects neurobiological perspectives with models of play aiming to construct superior player satisfaction models built upon biological foundations. Connections are presented between already recognized patterns of play and recent research on the brain (in particular, the limbic system). By providing a framework for understanding how the brain responds to recurrent patterns inherent to play, we aim to provide a platform for future experimental player-game interaction research (for which possible directions are briefly explored), and a propaedeutic to biologically-grounded player satisfaction models.

Abstract. Collective decision making involves on the one hand individual mental states such as beliefs, emotions and intentions, and on the other hand interaction with others with possibly different mental states. Achieving a satisfactory common group decision on which all agree requires that such mental states are adapted to each other by social interaction. Recent developments in Social Neuroscience have revealed neural mechanisms by which such mutual adaptation can be realised. These mechanisms not only enable intentions to converge to an emerging common decision, but at the same time enable to achieve shared underlying individual beliefs and emotions. This paper presents a computational model for such processes.

Abstract — Robot imitation is a useful and promising alternative to robot programming. Robot imitation involves two crucial issues. The first is how a robot can imitate a human whose physical structure and properties differ greatly from its own. The second is how the robot can generate various motions from finite programmable patterns (generalization). This paper describes a novel approach to robot imitation based on its own physical experiences. Let us consider a target task of moving an object on a table. For imitation, we focused on an active sensing process in which the robot acquires the relation between the object’s motion and its own arm motion. For generalization, we applied a recurrent neural network with parametric bias (RNNPB) model to enable recognition/generation of imitation motions. The robot associates the arm motion which reproduces the observed object’s motion presented by a human operator. Experimental results demonstrated that our method enabled the robot to imitate not only motion it has experienced but also unknown motion, which proved its capability for generalization. I.

Three experiments investigated the size and sources of age-related changes in visual imitation. In Experiment 1, young and older adults viewed sequences of quasi-random movements and then reproduced from memory what they had seen. As expected, older adults made more errors in imitation than did their younger counterparts. However older adults seemed to supplement their memory by exploiting an abstracted representation (gist) of a sequence. Experiments 2 and 3 apportioned the observed age-related changes in imitation performance among several possible causes. Experiment 2 showed that changes in precision of visual perception and motor control together accounted for only a small fraction of age-related changes in imitation quality; Experiment 3 showed that the bulk of the age-related changes arose from the older participants’ reduced ability to accommodate for increases in memory load, likely caused by diminished ability to encode or retain detailed information about movement sequences. Guided by these results, strategies are proposed for enhancing older adults ’ imitation learning.

Abstract. This paper introduces a neurologically inspired computational model for the emergence of group decisions. The model combines an individual decision making model based on Damasio’s Somatic Marker Hypothesis with mutual effects of group members on each other via mirroring of emotions and intentions. The obtained model shows how this combination of assumed neural mechanisms can form an adequate basis for the emergence of common group decisions, while, in addition, there is a feeling of wellness with these common decisions amongst the group members. 1