The Novelty Appraisal of the Feeling of Risk in Vehicles.

Nowadays, vehicle assistance systems may assess the risks of the traffic situation with the help of advanced sensor technology and optimized algorithms. However, the passengers' feelings of risk in the vehicle have been mostly neglected. According to the Component Process Model of emotions, during the feeling of risk, novelty is one of the relevant event appraisals leading to particular physiological and facial responses.

[Subjective certainty to increase the acceptance of automated and connected driving].

An important factor for the acceptance and thus the spread of automated and connected driving (ACD) is the degree of subjective uncertainty that users experience when interacting with automated vehicles. Subjective uncertainties always occur when people are not able to predict the further course of a situation or future events due to lack of experience or information. If such uncertainties occur during the use of automated vehicles, the development of trust and thus acceptance of this technology is impaired by the negative emotions accompanying subjective uncertainties.

Understanding the Multidimensional and Dynamic Nature of Facial Expressions Based on Indicators for Appraisal Components as Basis for Measuring Drivers' Fear.

Facial expressions are one of the commonly used implicit measurements for the in-vehicle affective computing. However, the time courses and the underlying mechanism of facial expressions so far have been barely focused on. According to the Component Process Model of emotions, facial expressions are the result of an individual's appraisals, which are supposed to happen in sequence.

Alexithymia and automatic processing of facial emotions: behavioral and neural findings.

Background: Alexithymia is a personality trait characterized by difficulties identifying and describing feelings, an externally oriented style of thinking, and a reduced inclination to imagination. Previous research has shown deficits in the recognition of emotional facial expressions in alexithymia and reductions of brain responsivity to emotional stimuli. Using an affective priming paradigm, we investigated automatic perception of facial emotions as a function of alexithymia at the behavioral and neural level.

Demonstrating Brain-Level Interactions Between Visuospatial Attentional Demands and Working Memory Load While Driving Using Functional Near-Infrared Spectroscopy.

Driving is a complex task concurrently drawing on multiple cognitive resources. Yet, there is a lack of studies investigating interactions at the brain-level among different driving subtasks in dual-tasking. This study investigates how visuospatial attentional demands related to increased driving difficulty interacts with different working memory load (WML) levels at the brain level.

Corrigendum: Assessing the Driver's Current Level of Working Memory Load With High Density Functional Near-infrared Spectroscopy: A Realistic Driving Simulator Study.

[This corrects the article DOI: 10.3389/fnhum.2017.

Recognizing Frustration of Drivers From Face Video Recordings and Brain Activation Measurements With Functional Near-Infrared Spectroscopy.

Experiencing frustration while driving can harm cognitive processing, result in aggressive behavior and hence negatively influence driving performance and traffic safety. Being able to automatically detect frustration would allow adaptive driver assistance and automation systems to adequately react to a driver's frustration and mitigate potential negative consequences. To identify reliable and valid indicators of driver's frustration, we conducted two driving simulator experiments.

Volumetric Associations Between Amygdala, Nucleus Accumbens, and Socially Anxious Tendencies in Healthy Women.

Socially anxious individuals report higher social fears and feelings of distress in interpersonal interactions. Structural neuroimaging studies indicate brain morphological abnormalities in patients with social anxiety disorder (SAD), but findings are heterogeneous and partially discrepant. Studies on structural correlates of socially anxious tendencies in participants without clinical diagnoses are scarce.

Assessing the Driver's Current Level of Working Memory Load with High Density Functional Near-infrared Spectroscopy: A Realistic Driving Simulator Study.

Cognitive overload or underload results in a decrease in human performance which may result in fatal incidents while driving. We envision that driver assistive systems which adapt their functionality to the driver's cognitive state could be a promising approach to reduce road accidents due to human errors. This research attempts to predict variations of cognitive working memory load levels in a natural driving scenario with multiple parallel tasks and to reveal predictive brain areas.

Observer-Rated Alexithymia and its Relationship with the Five-Factor-Model of Personality.

Studies examining the relationship between alexithymia and personality exclusively employed self-report measures of alexithymia. In the present study, we examined the relationship of both observer-rated and self-reported alexithymia with the Big Five personality dimensions. We administered the Toronto Structured Interview for Alexithymia (TSIA) as an interview-based measure of alexithymia and, in addition, two self-report questionnaires, the 20-item Toronto Alexithymia Scale (TAS-20) and the Bermond-Vorst Alexithymia Questionnaire (BVAQ).

Implicit affectivity and rapid processing of affective body language: An fMRI study.

Previous research has revealed affect-congruity effects for the recognition of affects from faces. Little is known about the impact of affect on the perception of body language. The aim of the present study was to investigate the relationship of implicit (versus explicit) affectivity with the recognition of briefly presented affective body expressions.

Alexithymic features and the labeling of brief emotional facial expressions - An fMRI study.

The ability to recognize subtle facial expressions can be valuable in social interaction to infer emotions and intentions of others. Research has shown that the personality trait of alexithymia is linked to difficulties labeling facial expressions especially when these are presented with temporal constraints. The present study investigates the neural mechanisms underlying this deficit.

Automatic emotion processing as a function of trait emotional awareness: an fMRI study.

It is unclear whether reflective awareness of emotions is related to extent and intensity of implicit affective reactions. This study is the first to investigate automatic brain reactivity to emotional stimuli as a function of trait emotional awareness. To assess emotional awareness the Levels of Emotional Awareness Scale (LEAS) was administered.

Enhanced response to music in pregnancy.

Given a possible effect of estrogen on the pleasure-mediating dopaminergic system, musical appreciation in participants whose estrogen levels are naturally elevated during the oral contraceptive cycle and pregnancy has been investigated (n = 32, 15 pregnant, 17 nonpregnant; mean age 27.2). Results show more pronounced blood pressure responses to music in pregnant women.

Alexithymia and the labeling of facial emotions: response slowing and increased motor and somatosensory processing.

Background: Alexithymia is a personality trait that is characterized by difficulties in identifying and describing feelings. Previous studies have shown that alexithymia is related to problems in recognizing others' emotional facial expressions when these are presented with temporal constraints. These problems can be less severe when the expressions are visible for a relatively long time.

Assessing alexithymia and emotional awareness: relations between measures in a German non-clinical sample.

The aim of this study was to evaluate psychometric properties and relations between two different methods of measuring alexithymia and one measure of emotional awareness in a German non-clinical sample. The 20-Item Toronto Alexithymia Scale (TAS-20), the Toronto Structured Interview for Alexithymia (TSIA), and the Levels of Emotional Awareness Scale (LEAS), which is a performance-based measure of emotional awareness, were administered to 84 university students. Both internal reliability and inter-rater reliability for the TSIA were acceptable.

Alexithymia is related to differences in gray matter volume: a voxel-based morphometry study.

Objective: Alexithymia has been characterized as the inability to identify and describe feelings. Functional imaging studies have revealed that alexithymia is linked to reactivity changes in emotion- and face-processing-relevant brain areas. In this respect, anterior cingulate cortex (ACC), amygdala, anterior insula and fusiform gyrus (FFG) have been consistently reported.

Adult attachment anxiety is associated with enhanced automatic neural response to positive facial expression.

According to social psychology models of adult attachment, a fundamental dimension of attachment is anxiety. Individuals who are high in attachment anxiety are motivated to achieve intimacy in relationships, but are mistrustful of others and their availability. Behavioral research has shown that anxiously attached persons are vigilant for emotional facial expression, but the neural substrates underlying this perceptual sensitivity remain largely unknown.

A Dry EEG-System for Scientific Research and Brain-Computer Interfaces.

Although it ranks among the oldest tools in neuroscientific research, electroencephalography (EEG) still forms the method of choice in a wide variety of clinical and research applications. In the context of brain-computer interfacing (BCI), EEG recently has become a tool to enhance human-machine interaction. EEG could be employed in a wider range of environments, especially for the use of BCI systems in a clinical context or at the homes of patients.

A public data hub for benchmarking common brain-computer interface algorithms.

Methods of statistical machine learning have recently proven to be very useful in contemporary brain-computer interface (BCI) research based on the discrimination of electroencephalogram (EEG) patterns. Because of this, many research groups develop new algorithms for both feature extraction and classification. However, until now, no large-scale comparison of these algorithms has been accomplished due to the fact that little EEG data is publicly available.