Upregulating positive affect through compassion: Psychological and physiological evidence

The pattern theory of compassion

Concepts of empathy, sympathy and compassion are often confused in a variety of literatures. This article proposes a pattern-theoretic approach to distinguishing compassion from empathy and sympathy. Drawing on psychology, Western philosophy, affective neuroscience, and contemplative science, we clarify the nature of compassion as a specific pattern of dynamically related factors that include physiological, cognitive, and affective processes, relational/intersubjective processes, and motivational/action tendencies. We also show that the dynamic nature of the compassion pattern is reflected in neuroscientific findings, as well as in compassion practice. The pattern theory of compassion allows us to make several clear distinctions between compassion, empathy, and sympathy.

Do compassion and self-compassion moderate the relationship between childhood socioeconomic position and adulthood body composition?

The study aims to investigate the associations of compassion and self-compassion with body composition, and whether adulthood compassion and self-compassion moderate the relationship between childhood SEP and adulthood body composition. The participants came from the Northern Finland Birth Cohort 1986 Study (n = 789, 52.1% women), with a mean age of 34.0 years. Compassion and self-compassion were measured with the Dispositional Positive Emotions Scale and Self-Compassion Scale-Short Form, respectively. Body composition was assessed using anthropometric and body fat measurements at a clinic. Childhood SEP included parental occupation, education, and employment. The results showed that high compassion was associated with three out of the five body composition measurements, namely lower waist circumference (B = -0.960, p = 0.039, 95% CI: -1.870; -0.498), body fat percentage (B = -0.693, p = 0.030, 95% CI: -1.317; -0.069), and fat mass index (B = -0.325, p = 0.023, 95% CI: -0.605; -0.044) (adjusted for sex, and childhood and adulthood SEP) but not with body mass index or waist-to-hip ratio. Self-compassion was not associated with body composition. Neither compassion nor self-compassion moderated the association between childhood SEP and adulthood body composition, as the interaction effects were not significant. Therefore, the dispositions did not protect against the negative effects of childhood SEP on adulthood body composition. High other-directed compassion may be, however, associated with healthier body composition.

A compassion-based treatment for couples with the female partner suffering from current depressive disorder: A randomized-controlled trial

BACKGROUND

Studies have shown that depression and interpersonal relationships are interdependently connected and that including the intimate partner in treatment for depression has beneficial effects. Given evidence that compassion is both an interpersonal quality and a promising treatment target, the goal of this study was to examine the effects of a compassion-based, contemplative treatment for couples employing a multi-method approach for evaluation.

METHODS

In a pre-post-follow-up design, n = 53 different-sex couples including women with current depression were randomly assigned to a 10-week-long CBCT®-fC (Cognitively-Based Compassion Training/intervention for couples) or treatment-as-usual (TAU) condition. Multi-level linear regression models and post-hoc contrasts were calculated to determine changes in depressive symptoms, mindfulness and self-compassion, interpersonal functioning and neuroendocrine markers collected during a partnership appreciation task (PAT) in the laboratory before and after CBCT-fC treatment.

RESULTS

While CBCT-fC led to a comparable decrease of depressive symptoms as TAU, the training specifically increased self-compassion and mindfulness versus TAU. Interestingly, interpersonal functioning did not improve, which was also reflected in participants' preferred self-focus in-between-session practices, instead of practices with interpersonal focus. There were no group-specific changes in psychobiological stress-marker reactivity.

CONCLUSIONS

CBCT-fC was effective in decreasing current depressive symptomatology and increasing mindfulness, and self-compassion. Especially the motivation to participate, such as improving interpersonal functioning, should be addressed and intrinsic motives of the partners to be involved. In highly burdened individuals, self-regulation may need to be improved before co-regulation can be addressed, which would requiring longer treatments. Facilitating factors for engaging in the practice between-sessions seem meaningful.

The Neural Correlates of Narcissism: Is There a Connection with Desire for Fame and Celebrity Worship?

(1) Objective: Narcissism is characterized by emotional regulation deficits, a lack of empathy for others, and extreme self-focus. Narcissism has also been linked to an increased desire for fame and celebrity worship. Here, the neuroscience underlying narcissism is examined in order to determine what regions and networks of the brain are altered when non-narcissistic individuals are compared to participants with both grandiose and vulnerable narcissism. (2) Methods: The behavioral relationships between grandiose narcissism and desire for fame and vulnerable narcissism and celebrity worship are explored, along with a possible relationship at the neural level between these constructs. In this paper, we review research demonstrating that increased levels of grandiose narcissism are associated with an increase in obsession with fame, while vulnerable narcissism is associated with celebrity worship. (3) Results: Based on current data, the frontal regions underlie narcissism and also likely underlie celebrity worship and desire for fame. This tenuous conclusion is based on a limited number of studies. (4) Conclusions: The brain areas associated with grandiose narcissism may be associated with an intense desire for fame as well, while brain regions associated with vulnerable narcissism may be similar in celebrity worshipers. Future research studies on the brain that are specifically designed to test these relationships at a neurological level are needed.

Analysis of Erhu Performance Effect in Public Health Music Works Based on Artificial Intelligence Technology

With the rise of Erhu teaching in recent years, a large number of people have joined the team to learn Erhu playing. However, due to the high cost of teaching and the unique one-to-one teaching mode between teachers and students, Erhu education resources are very scarce. Learning Erhu performance has become a luxury activity. Nowadays, with the rise of artificial intelligence, computer music is developing rapidly. Music has two important aspects: composition and performance. Different kinds of instruments convey different styles, and players inject different rhythms and dynamics into their performance, thus producing rich expressive force. The development of image style conversion, which opens people's evaluation of music performance, is an important issue in many fields of artificial intelligence (it is also known as intelligence, machine intelligence, referring to the intelligence shown by the machine made by people. Usually, artificial intelligence refers to the technique of presenting human intelligence through ordinary computer programs). For an Erhu song, there are various factors that affect its effectiveness, and there are many indexes to evaluate it, such as sense of rhythm, expressive force, musical sense, style, and so on. Using a computer to simulate the evaluation process is essential to find out the mathematical relationship between the factors that affect the performance of music and the evaluation indexes. Neural network is a kind of mathematical model proposed by simulating the way of thinking of human brain in artificial intelligence. It has the advantages of not having strict requirements on data distribution, nonlinear data processing method, strong robustness, and dynamics and is very suitable for the mathematical model of evaluation system. In addition, the neural network also has a strong theoretical basis, and their application in various industries has developed basically mature. This paper tries to introduce a deep neural network mathematical model into the evaluation system of Erhu performance, and the experimental results prove the reliability and practicality of the method in this paper. It can provide a method basis and theoretical reference for evaluation of Erhu performance effect.