When we consider the active involvement of a subject of an emotional state, we have to say that intentionality of emotional states is conative rather than cognitive. Emotion is much closer to desire or a conative state than a belief or perception. Since a conative state is successful when it is carried out, a conative intentional state is more related to action toward others and events rather than passive perception. So it is important to examine the relation between emotion and action to see emotion as an active response. In the first, second and third chapter of my thesis, I will argue that since perception is too passive to be emotions, it is wrong to insist that emotions are a kind of perception. In the fourth chapter, I will show that it is impossible to have emotions without self-involvement. In the fifth chapter, I will discuss the relation between emotions and action through the cases of brain damaged patients and the Confucianist theory of emotion. / text

The purpose of this study was to investigate the influence of background music on children’s recognition of emotions depicted in photographs of human faces. In individual testing sessions, 30 typically developing children and 20 children with high-functioning autism rated the emotions in 30 photographs while listening to background music intended to convey happiness and again while listening to background music intended to convey sadness. The photographs included 10 examples of happy expressions, 10 examples of neutral expressions, and 10 examples of sad expressions. The 7-point response scale ranged from very sad to very happy. Music listening conditions were counterbalanced. Overall, participants in both groups accurately discriminated among the three categories of photographs, although the variances among ratings in each category were somewhat greater for the participants with autism. A significant two-way interaction revealed that participants’ ratings of happy and neutral faces were unaffected by music conditions, but the sad faces were perceived to be sadder when participants listened to sad music than when they listened to happy music. Across both music conditions, typically developing children rated the happy faces as happier and the sad faces as sadder than did the participants with autism. Response times of the typically developing children were consistently shorter than were the response times of the children with autism, and both groups took longer to rate the sad faces than they took to rate the happy faces. Response times of typically developing children were generally unaffected by the music condition, but children with autism took longer to respond when listening to sad music than when listening to happy music. These results indicate that music may affect perceptions of emotion in children with autism, and that perceptions of sad facial expressions seem to be more affected by background music than are perceptions of happy or neutral faces. / text

Cognitive emotion regulation strategies can be used to counter the negative effects of life stress. In neuroimaging paradigms, many different types of reappraisal strategies have been used to promote cognitive coping with impersonal, emotion-evoking stimuli, but limited research has been done utilizing specific reappraisal strategies with real-life events. Big picture reappraisal is a specific emotion regulation strategy that offers a way of managing distress aiming to promote acceptance and cognitive coping. Big picture reappraisal instructions (experimental condition) were compared to distraction and rumination instructions (control conditions) resulting in activation in areas associated with cognitive control (orbital frontal cortex, superior parietal lobe, cerebellum lobule VI). Mood ratings collected after each of several condition prompts were significantly more positive in the distraction compared to the big picture reappraisal condition during the first third of the induction, but as the task progressed the effectiveness of distraction declined considerably. There were no significant condition differences in mood during the second and third segments of the induction. / text

Με τη συνεχώς αυξανόμενη παρουσία αυτόματων συστημάτων στην καθημερινότητά μας, εισέρχεται και το βάρος της αλληλεπίδρασης με αυτά τα συστήματα, εξαιτίας της έλλειψης συναισθηματικής νοημοσύνης από την πλευρά των μηχανών. Η συναισθηματική πληροφορία που μεταδίδεται μέσω της ανθρώπινης ομιλίας αποτελεί σημαντικό παράγοντα στην ανθρώπινη επικοινωνία και αλληλεπίδραση. Όταν όμως μηχανές ή υπολογιστικά συστήματα επικοινωνούν με ανθρώπους δεν αντιλαμβάνονται τις πιθανές συναισθηματικές καταστάσεις του ομιλητή και γι’ αυτό το λόγο υστερούν. Στα πλαίσια αυτής της εργασίας πραγματοποιείται επισημείωση, σε επίπεδο προτάσεων, λέξεων και ήχων, σε ηχογραφήσεις που έχουν πραγματοποιηθεί κατά την διάρκεια αλληλεπίδρασης ανθρώπου-μηχανής, με βάση την προβολή των συναισθημάτων στον κύκλο «ενεργοποίησης-αξιολόγησης». Έτσι καταλήγουμε στη δημιουργία μια ελληνικής βάσης συναισθηματικής ομιλίας. Στη συνέχεια, με βάση τις επισημειωμένες φράσεις εκπαιδεύουμε το γλωσσολογικό μας μοντέλο, το οποίο και ελέγχουμε με ένα υποσύνολο αυτών, για να δούμε κατά πόσο τα αποτελέσματα μας ανταποκρίνονται στην πραγματικότητα. Αποτέλεσμα της διαδικασίας είναι μια αριθμητική τιμή πρόβλεψης για την συναισθηματική κατάσταση της ομιλούμενης φράσης. / -

Emotion states greatly influence many areas in our daily lives, such as: learning, decision making and interaction with others. Therefore, the ability to detect and recognize one’s emotional states is essential in intelligence Human Machine Interaction (HMI). In this thesis, a pattern classification framework was developed to sense and communicate emo- tion changes expressed by the Central Nervous System (CNS) through the use of EEG signals. More specifically, an EEG-based subject-dependent affect recognition system was developed to quantitatively measure and categorize three affect states: Positively excited, neutral and negatively excited. Several existing feature extraction algorithms and classifiers were researched, analyzed and evaluated through a series of classification simulations using a publicly available emotion-based EEG database. Simulation results were presented followed by an interpretation discussion. The findings in this thesis can be useful for the design of affect sensitive applications such as augmented means of communication for severely disabled people that cannot directly express their emotions. Furthermore, we have shown that with significantly reduced number of channels, classification rates maintained a level that is feasible for emotion recognition. Thus current HMI paradigms to integrate consumer electronics such as smart hand-held device with commercially available EEG headsets is promising and will significantly broaden the application cases.

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Stroke is one of the most prevalent chronic illnesses in Canada. Family caregivers can make a significant contribution toward patients’ recovery. Caregivers’ emotions can impact their motivation to engage in empathy-related helping behaviours. The purpose of this study was to examine relationships among functional deficits of post-stroke individuals, family caregivers’ emotions, and caregivers’ ability to empathize with post-stroke individuals. As guided by Davis’s organizational model on empathy, a correlational descriptive methodology was employed. Participants were requested to complete four questionnaires. Study found that caregiver fatigue was the only factor associated with caregiver empathy-related behaviour. Analyses also found that communication deficits had a linkage with caregivers’ negative emotions. Study results will contribute to the current state of the literature on post-stroke care at home by understanding of the impact of caregivers’ psychological experiences on their empathy-related responses toward post-stroke individuals. Recommendations for clinical practice and future research were made based on this study’s results.

Emotion states greatly influence many areas in our daily lives, such as: learning, decision making and interaction with others. Therefore, the ability to detect and recognize one’s emotional states is essential in intelligence Human Machine Interaction (HMI). In this thesis, a pattern classification framework was developed to sense and communicate emo- tion changes expressed by the Central Nervous System (CNS) through the use of EEG signals. More specifically, an EEG-based subject-dependent affect recognition system was developed to quantitatively measure and categorize three affect states: Positively excited, neutral and negatively excited. Several existing feature extraction algorithms and classifiers were researched, analyzed and evaluated through a series of classification simulations using a publicly available emotion-based EEG database. Simulation results were presented followed by an interpretation discussion. The findings in this thesis can be useful for the design of affect sensitive applications such as augmented means of communication for severely disabled people that cannot directly express their emotions. Furthermore, we have shown that with significantly reduced number of channels, classification rates maintained a level that is feasible for emotion recognition. Thus current HMI paradigms to integrate consumer electronics such as smart hand-held device with commercially available EEG headsets is promising and will significantly broaden the application cases.

This thesis aims to elucidate an apparent paradox about the role of emotion in moral agency. A number of lines of concern suggest emotion may have serious negative impact on moral agency. On the other hand, there are considerations that suggest emotion also plays a crucial role in motivating, informing and even constituting moral agency. Significantly, there is a strong connection between participant reactive attitudes and ascription of moral status as agent or subject. Nonemotional agents could not hold such attitudes. Also, removing participant reactive attitudes imposes a peculiar and incoherent form of solipsism about moral agency. Given this necessary role for emotion, can we give an account of emotion that will also meet the worries? I examine, as crucial examples, three recurrent lines of concern about emotion - that it threatens our capacities for objectivity, rationality, and autonomy - to tease out the descriptive assumptions about emotion, and the normative assumptions about moral agency, that these objections are based on. I then offer three lines of argument towards resolving these worries. The first addresses the worries directly, and the other two shift blame off emotion. First, then, I argue that the normative concerns can largely be met by a descriptive account that views emotion as cognitive. However, “judgementalist” cognitive accounts that assimilate emotion to belief may make emotion metaethically respectable at the cost of making it meta-ethically redundant. Also, such accounts are descriptively less than plausible. A better approach, I argue, is to allow that belief may play a significant role in emotion but to also allow at least a quasicognitive role to the distinctively affective element in emotion: feeling. I also argue for a hrther revision of cognitive accounts to emphasise that emotions reflect features of those who feel them. If we were different, our emotions would be different. So, secondly, I argue that a number of the features that power worries about emotions have their sources in what those who feel them are like, rather than in emotions as such. However, both human nature and emotion are capable of significant plasticity and diversity. We are also capable of a considerable - but not infinite - degree of self-determination both about what we are like and what our emotions are like. Finally, I argue that the normative assumptions that power the objections to emotion are themselves in need of revision - and in some tension with each other. This leads to a McGufin-theory of emotion in moral agency: Problems with emotion’s place in moral agency serve as indicators of unresolved tensions in our thinking about moral agency, rather than just indicators of problems with emotion as such. In view of this, I also argue for caution in any attempts to change emotion to fit particular ideals of moral agency.

Introduction: Emotion regulation, the process of changing one’s emotion is necessary for efficiency when performing cognitive tasks, and is often measured using a Stroop task that provides conflict between emotional and factual information. Researchers have found that listening to music increases performance on cognitive tasks, and we hypothesize that listening to music samples that evoke different arousal and valence levels will affect participants’ emotion regulation skills. Method: 38 Georgia State University undergraduates listened to three-minute excerpts of film scores known to evoke a particular mood and arousal state while completing an emotional-Stroop task. Results: We performed a repeated measures ANOVA and found a significant difference of music type and an interaction between music type and word context. Discussion: These results provide evidence that music evokes different arousal and valence states, which have a distinct effect on emotion regulation skills.