Experiments on real-life emotions challenge Ekman's model

The TIE-93: a Facial Emotion Recognition Test Adapted for Culturally, Linguistically, and Educationally Diverse Alzheimer's Dementia Patients in France

OBJECTIVE

Emotion recognition tests are essential for differential diagnostics when assessing patients with Alzheimer's disease (AD) dementia. However, there remains a lack of emotion recognition tests appropriate for culturally and educationally diverse populations. The aim of this study was to develop an emotion recognition test (the TIE-93) appropriate for these populations. We then examined whether the TIE-93 could reduce emotion recognition performance differences between populations with a native French versus a culturally and educationally diverse background (participants who had immigrated to France). This was assessed by comparing performance between controls of each cultural group. We also assessed the effect of demographic variables on TIE-93 test performance and whether performance in an AD patient group was consistent with the research literature.

METHODS

Fifty-seven patients with AD dementia and 240 healthy controls, from native French and culturally and educationally diverse backgrounds, were included in the study. The TIE-93 is composed of eight panels with photos of actors displaying six basic emotions. Participants were asked to identify which of the six facial expressions displayed matched an oral description of a context.

RESULTS

When comparing French and culturally and educationally diverse controls, Quade's ANCOVA revealed that there remained an effect of culture and education on TIE-93 test performance. Nonetheless, while controlling for years of education, age, sex, and cultural group, patients with AD dementia scored significantly more poorly than controls, specifically for most negative emotions.

CONCLUSION

The TIE-93 represents a first step toward developing appropriate emotion recognition tests for culturally and educationally diverse populations.

Individual predictors of vaccine hesitancy in the Italian post COVID-19 pandemic era

A wide range of survey studies have explored vaccination hesitancy/resistance during the COVID-19 pandemic and provided evidence that this can be explained by several individual variables from the ideological, clinical, and socio-affective domain. However, evidence about which individual variables predict vaccine hesitancy in the post-pandemic state of COVID-19 is meager. We administered a battery of questionnaires to a group of 120 Italian participants with high and low scores on the adult vaccine hesitancy scale (aVHS) to investigate the predictive role of ideological (i.e. political orientation), clinical (i.e. anxiety, interoceptive accuracy), and socio-affective (i.e. alexithymia, disgust sensitivity/propensity, empathy) variables on vaccine hesitancy/resistance. This study provides evidence that lower interoceptive awareness and cognitive empathy are predictors of a greater hesitancy to get vaccinated in the post-pandemic COVID-19 state.

An Ensemble Deep Learning Approach for EEG-Based Emotion Recognition Using Multi-Class CSP

In recent years, significant advancements have been made in the field of brain-computer interfaces (BCIs), particularly in the area of emotion recognition using EEG signals. The majority of earlier research in this field has missed the spatial-temporal characteristics of EEG signals, which are critical for accurate emotion recognition. In this study, a novel approach is presented for classifying emotions into three categories, positive, negative, and neutral, using a custom-collected dataset. The dataset used in this study was specifically collected for this purpose from 16 participants, comprising EEG recordings corresponding to the three emotional states induced by musical stimuli. A multi-class Common Spatial Pattern (MCCSP) technique was employed for the processing stage of the EEG signals. These processed signals were then fed into an ensemble model comprising three autoencoders with Convolutional Neural Network (CNN) layers. A classification accuracy of 99.44 ± 0.39% for the three emotional classes was achieved by the proposed method. This performance surpasses previous studies, demonstrating the effectiveness of the approach. The high accuracy indicates that the method could be a promising candidate for future BCI applications, providing a reliable means of emotion detection.

The Role of Serotonin in Fear Learning and Memory: A Systematic Review of Human Studies

Fear is characterized by distinct behavioral and physiological responses that are essential for the survival of the human species. Fear conditioning (FC) serves as a valuable model for studying the acquisition, extinction, and expression of fear. The serotonin (5-hydroxytryptamine, 5-HT) system is known to play a significant role in emotional and motivational aspects of human behavior, including fear learning and expression. Accumulating evidence from both animal and human studies suggests that brain regions involved in FC, such as the amygdala, hippocampus, and prefrontal cortex, possess a high density of 5-HT receptors, implicating the crucial involvement of serotonin in aversive learning. Additionally, studies exploring serotonin gene polymorphisms have indicated their potential influence on FC. Therefore, the objective of this work was to review the existing evidence linking 5-HT with fear learning and memory in humans. Through a comprehensive screening of the PubMed and Web of Science databases, 29 relevant studies were included in the final review. These studies investigated the relationship between serotonin and fear learning using drug manipulations or by studying 5-HT-related gene polymorphisms. The results suggest that elevated levels of 5-HT enhance aversive learning, indicating that the modulation of serotonin 5-HT2A receptors regulates the expression of fear responses in humans. Understanding the role of this neurochemical messenger in associative aversive learning can provide insights into psychiatric disorders such as anxiety and post-traumatic stress disorder (PTSD), among others.