The role of the cerebellum in unconsciuos and conscious processing of emotions: a review

Studies from the past three decades have demonstrated that there is cerebellar involvement in the emotional domain. Emotional processing in humans requires both unconscious and conscious mechanisms. A significant amount of evidence indicates that the cerebellum is one of the cerebral structures that subserve emotional processing, although conflicting data have been reported on its function in unconscious and conscious mechanisms. This review discusses the available clinical, neuroimaging and neurophysiological data on this issue. We also propose a model in which the cerebellum acts as a mediator between the internal state and external environment for the unconscious and conscious levels of emotional processing

Does gaze direction modulate facial expression processing in children with autism spectrum disorder?

Two experiments investigated whether children with autism spectrum disorder (ASD) integrate relevant communicative signals, such as gaze direction, when decoding a facial expression. In Experiment 1, typically developing children (9–14 years old; n = 14) were faster at detecting a facial expression accompanying a gaze direction with a congruent motivational tendency (i.e., an avoidant facial expression with averted eye gaze) than those with an incongruent motivational tendency. Children with ASD (9–14 years old; n = 14) were not affected by the gaze direction of facial stimuli. This finding was replicated in Experiment 2, which presented only the eye region of the face to typically developing children (n = 10) and children with ASD (n = 10). These results demonstrated that children with ASD do not encode and/or integrate multiple communicative signals based on their affective or motivational tendency

Speech-based recognition of self-reported and observed emotion in a dimensional space

The differences between self-reported and observed emotion have only marginally been investigated in the context of speech-based automatic emotion recognition. We address this issue by comparing self-reported emotion ratings to observed emotion ratings and look at how differences between these two types of ratings affect the development and performance of automatic emotion recognizers developed with these ratings. A dimensional approach to emotion modeling is adopted: the ratings are based on continuous arousal and valence scales. We describe the TNO-Gaming Corpus that contains spontaneous vocal and facial expressions elicited via a multiplayer videogame and that includes emotion annotations obtained via self-report and observation by outside observers. Comparisons show that there are discrepancies between self-reported and observed emotion ratings which are also reflected in the performance of the emotion recognizers developed. Using Support Vector Regression in combination with acoustic and textual features, recognizers of arousal and valence are developed that can predict points in a 2-dimensional arousal-valence space. The results of these recognizers show that the self-reported emotion is much harder to recognize than the observed emotion, and that averaging ratings from multiple observers improves performance

Emotion meets action : towards an integration of research and theory

Action Contro

Affective Facial Expression Processing via Simulation: A Probabilistic Model

Understanding the mental state of other people is an important skill for intelligent agents and robots to operate within social environments. However, the mental processes involved in `mind-reading' are complex. One explanation of such processes is Simulation Theory - it is supported by a large body of neuropsychological research. Yet, determining the best computational model or theory to use in simulation-style emotion detection, is far from being understood. In this work, we use Simulation Theory and neuroscience findings on Mirror-Neuron Systems as the basis for a novel computational model, as a way to handle affective facial expressions. The model is based on a probabilistic mapping of observations from multiple identities onto a single fixed identity (`internal transcoding of external stimuli'), and then onto a latent space (`phenomenological response'). Together with the proposed architecture we present some promising preliminary resultsComment: Annual International Conference on Biologically Inspired Cognitive Architectures - BICA 201

Theories of understanding others: the need for a new account and the guiding role of the person model theory

What would be an adequate theory of social understanding? In the last decade, the philosophical debate has focused on Theory Theory, Simulation Theory and Interaction Theory as the three possible candidates. In the following, we look carefully at each of these and describe its main advantages and disadvantages. Based on this critical analysis, we formulate the need for a new account of social understanding. We propose the Person Model Theory as an independent new account which has greater explanatory power compared to the existing theorie

Affective games:a multimodal classification system

Affective gaming is a relatively new field of research that exploits human emotions to influence gameplay for an enhanced player experience. Changes in player’s psychology reflect on their behaviour and physiology, hence recognition of such variation is a core element in affective games. Complementary sources of affect offer more reliable recognition, especially in contexts where one modality is partial or unavailable. As a multimodal recognition system, affect-aware games are subject to the practical difficulties met by traditional trained classifiers. In addition, inherited game-related challenges in terms of data collection and performance arise while attempting to sustain an acceptable level of immersion. Most existing scenarios employ sensors that offer limited freedom of movement resulting in less realistic experiences. Recent advances now offer technology that allows players to communicate more freely and naturally with the game, and furthermore, control it without the use of input devices. However, the affective game industry is still in its infancy and definitely needs to catch up with the current life-like level of adaptation provided by graphics and animation

Towards responsive Sensitive Artificial Listeners

This paper describes work in the recently started project SEMAINE, which aims to build a set of Sensitive Artificial Listeners – conversational agents designed to sustain an interaction with a human user despite limited verbal skills, through robust recognition and generation of non-verbal behaviour in real-time, both when the agent is speaking and listening. We report on data collection and on the design of a system architecture in view of real-time responsiveness