A Comparison of the emotion perception between the timbre of Korean traditional and Western wind instrument

2021 ◽  
Vol 49 ◽  
pp. 159-177
Author(s):  
Shinhye Joo ◽  
Hyunju Chong
Keyword(s):  
Emotion Perception ◽  
Wind Instrument

Perception of Emotional Expressions in Adults

2016 ◽  
Vol 37 (1) ◽  
pp. 16-23 ◽  
Author(s):  
Chit Yuen Yi ◽  
Matthew W. E. Murry ◽  
Amy L. Gentzler
Keyword(s):  
Facial Expressions ◽  
Negative Mood ◽  
Emotion Perception ◽  
State Level ◽  
Past Research ◽  
Negative Emotionality ◽  
Basic Emotions ◽  
Perceived Intensity ◽  
Trait Level ◽  
Facial Expressions Of Emotion

Abstract. Past research suggests that transient mood influences the perception of facial expressions of emotion, but relatively little is known about how trait-level emotionality (i.e., temperament) may influence emotion perception or interact with mood in this process. Consequently, we extended earlier work by examining how temperamental dimensions of negative emotionality and extraversion were associated with the perception accuracy and perceived intensity of three basic emotions and how the trait-level temperamental effect interacted with state-level self-reported mood in a sample of 88 adults (27 men, 18–51 years of age). The results indicated that higher levels of negative mood were associated with higher perception accuracy of angry and sad facial expressions, and higher levels of perceived intensity of anger. For perceived intensity of sadness, negative mood was associated with lower levels of perceived intensity, whereas negative emotionality was associated with higher levels of perceived intensity of sadness. Overall, our findings added to the limited literature on adult temperament and emotion perception.

Nonautomatic Emotion Perception in a Dual-Task Situation

2008 ◽  
Author(s):  
Dave Tomasik ◽  
Eric Ruthruff ◽  
Philip A. Allen ◽  
Mei-Ching Lien
Keyword(s):  
Dual Task ◽  
Emotion Perception

Differences in Gradient Emotion Perception: Human vs. Alexa Voices

2020 ◽  
Author(s):  
Michelle Cohn ◽  
Eran Raveh ◽  
Kristin Predeck ◽  
Iona Gessinger ◽  
Bernd Möbius ◽  
...  
Keyword(s):  
Emotion Perception

scholarly journals Machine learning-based ability to classify psychosis and early stages of disease through parenting and attachment-related variables is associated with social cognition

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Linda A. Antonucci ◽  
Alessandra Raio ◽  
Giulio Pergola ◽  
Barbara Gelao ◽  
Marco Papalino ◽  
...  
Keyword(s):  
Machine Learning ◽  
Social Cognition ◽  
Attachment Style ◽  
Learning Algorithm ◽  
Early Recognition ◽  
Emotion Perception ◽  
First Episode ◽  
Support Vector ◽  
Significant Group ◽  
Early Stages

Abstract Background Recent views posited that negative parenting and attachment insecurity can be considered as general environmental factors of vulnerability for psychosis, specifically for individuals diagnosed with psychosis (PSY). Furthermore, evidence highlighted a tight relationship between attachment style and social cognition abilities, a key PSY behavioral phenotype. The aim of this study is to generate a machine learning algorithm based on the perceived quality of parenting and attachment style-related features to discriminate between PSY and healthy controls (HC) and to investigate its ability to track PSY early stages and risk conditions, as well as its association with social cognition performance. Methods Perceived maternal and paternal parenting, as well as attachment anxiety and avoidance scores, were trained to separate 71 HC from 34 PSY (20 individuals diagnosed with schizophrenia + 14 diagnosed with bipolar disorder with psychotic manifestations) using support vector classification and repeated nested cross-validation. We then validated this model on independent datasets including individuals at the early stages of disease (ESD, i.e. first episode of psychosis or depression, or at-risk mental state for psychosis) and with familial high risk for PSY (FHR, i.e. having a first-degree relative suffering from psychosis). Then, we performed factorial analyses to test the group x classification rate interaction on emotion perception, social inference and managing of emotions abilities. Results The perceived parenting and attachment-based machine learning model discriminated PSY from HC with a Balanced Accuracy (BAC) of 72.2%. Slightly lower classification performance was measured in the ESD sample (HC-ESD BAC = 63.5%), while the model could not discriminate between FHR and HC (BAC = 44.2%). We observed a significant group x classification interaction in PSY and HC from the discovery sample on emotion perception and on the ability to manage emotions (both p = 0.02). The interaction on managing of emotion abilities was replicated in the ESD and HC validation sample (p = 0.03). Conclusion Our results suggest that parenting and attachment-related variables bear significant classification power when applied to both PSY and its early stages and are associated with variability in emotion processing. These variables could therefore be useful in psychosis early recognition programs aimed at softening the psychosis-associated disability.

Neural mechanisms of the cognitive control of emotion

2006 ◽  
Vol 18 (3-4) ◽  
pp. 144-153 ◽  
Author(s):  
Melissa J. Green ◽  
Gin S. Malhi
Keyword(s):  
Emotion Regulation ◽  
Cognitive Control ◽  
Psychiatric Disorders ◽  
Psychological Health ◽  
Emotion Dysregulation ◽  
Emotional Experience ◽  
Cognitive Strategies ◽  
Emotion Perception ◽  
Neural Mechanisms ◽  
Emotion Generation

Background:Emotion regulation involves the initiation of new emotional responses and continual alteration of current emotions in response to rapidly changing environmental and social stimuli. The capacity to effectively implement emotion regulation strategies is essential for psychological health; impairments in the ability to regulate emotions may be critical to the development of clinical levels of depression, anxiety and mania.Objective:This review provides a summary of findings from current research examining the neural mechanisms of emotion regulation by means of conscious cognitive strategies of reappraisal. These findings are considered in the context of related concepts of emotion perception and emotion generation, with discussion of the likely cognitive neuropsychological contributions to emotion regulation and the implications for psychiatric disorders.Results:Convergent evidence implicates an inhibitory role of prefrontal cortex and cingulate regions upon subcortical and cortical emotion generation systems in the cognitive control of emotional experience. Concurrent modulation of cortical activity by the peripheral nervous system is highlighted by recent studies using simultaneous physiological and neuroimaging techniques. Individual differences in emotion perception, generation of affect and neuropsychological skills are likely to have direct consequences for emotion regulation.Conclusions:Emotion regulation relies on synergy within brain stem, limbic and cortical processes that promote the adaptive perception, generation and regulation of affect. Aberrant emotion processing in any of these stages may disrupt this self-sustaining regulatory system, with the potential to manifest in distinct forms of emotion dysregulation as seen in major psychiatric disorders such as depression, bipolar disorder and schizophrenia.

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