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Brain–computer interfaces (BCI) based on event-related potentials (ERP) allow for selection of characters from a visually presented character-matrix and thus provide a communica- tion channel for users with neurodegenerative disease. Although they have been topic of research for more than 20 years and were multiply proven to be a reliable communication method, BCIs are almost exclusively used in experimental settings, handled by qualified experts. This study investigates if ERP–BCIs can be handled independently by laymen without expert support, which is inevitable for establishing BCIs in end-user’s daily life situations. Furthermore we compared the classic character-by-character text entry against a predictive text entry (PTE) that directly incorporates predictive text into the character- matrix. N = 19 BCI novices handled a user-centered ERP–BCI application on their own without expert support. The software individually adjusted classifier weights and control parameters in the background, invisible to the user (auto-calibration). All participants were able to operate the software on their own and to twice correctly spell a sentence with the auto-calibrated classifier (once with PTE, once without). Our PTE increased spelling speed and, importantly, did not reduce accuracy. In sum, this study demonstrates feasi- bility of auto-calibrating ERP–BCI use, independently by laymen and the strong benefit of integrating predictive text directly into the character-matrix.
Faces in context: A review and systematization of contextual influences on affective face processing
(2012)
Facial expressions are of eminent importance for social interaction as they convey information about other individuals’ emotions and social intentions. According to the predominant “basic emotion” approach, the perception of emotion in faces is based on the rapid, auto- matic categorization of prototypical, universal expressions. Consequently, the perception of facial expressions has typically been investigated using isolated, de-contextualized, static pictures of facial expressions that maximize the distinction between categories. However, in everyday life, an individual’s face is not perceived in isolation, but almost always appears within a situational context, which may arise from other people, the physical environment surrounding the face, as well as multichannel information from the sender. Furthermore, situational context may be provided by the perceiver, including already present social infor- mation gained from affective learning and implicit processing biases such as race bias.Thus, the perception of facial expressions is presumably always influenced by contextual vari- ables. In this comprehensive review, we aim at (1) systematizing the contextual variables that may influence the perception of facial expressions and (2) summarizing experimental paradigms and findings that have been used to investigate these influences. The studies reviewed here demonstrate that perception and neural processing of facial expressions are substantially modified by contextual information, including verbal, visual, and auditory information presented together with the face as well as knowledge or processing biases already present in the observer. These findings further challenge the assumption of auto- matic, hardwired categorical emotion extraction mechanisms predicted by basic emotion theories. Taking into account a recent model on face processing, we discuss where and when these different contextual influences may take place, thus outlining potential avenues in future research.
Numerous studies have shown that humans automatically react with congruent facial reactions, i.e., facial mimicry, when seeing a vis-á-vis’ facial expressions. The current experiment is the first investigating the neuronal structures responsible for differences in the occurrence of such facial mimicry reactions by simultaneously measuring BOLD and facial EMG in an MRI scanner. Therefore, 20 female students viewed emotional facial expressions (happy, sad, and angry) of male and female avatar characters. During picture presentation, the BOLD signal as well as M. zygomaticus major and M. corrugator supercilii activity were recorded simultaneously. Results show prototypical patterns of facial mimicry after correction for MR-related artifacts: enhanced M. zygomaticus major activity in response to happy and enhanced M. corrugator supercilii activity in response to sad and angry expressions. Regression analyses show that these congruent facial reactions correlate significantly with activations in the IFG, SMA, and cerebellum. Stronger zygomaticus reactions to happy faces were further associated to increased activities in the caudate, MTG, and PCC. Corrugator reactions to angry expressions were further correlated with the hippocampus, insula, and STS. Results are discussed in relation to core and extended models of the mirror neuron system (MNS).
In recent years, Ideomotor Theory has regained widespread attention and sparked the development of a number of theories on goal-directed behavior and learning. However, there are two issues with previous studies’ use of Ideomotor Theory. Although Ideomotor Theory is seen as very general, it is often studied in settings that are considerably more simplistic than most natural situations. Moreover, Ideomotor Theory’s claim that effect anticipations directly trigger actions and that action-effect learning is based on the formation of direct action-effect associations is hard to address empirically. We address these points from a computational perspective. A simple computational model of Ideomotor Theory was tested in tasks with different degrees of complexity.The model evaluation showed that Ideomotor Theory is a computationally feasible approach for understanding efficient action-effect learning for goal-directed behavior if the following preconditions are met: (1) The range of potential actions and effects has to be restricted. (2) Effects have to follow actions within a short time window. (3) Actions have to be simple and may not require sequencing. The first two preconditions also limit human performance and thus support Ideomotor Theory. The last precondition can be circumvented by extending the model with more complex, indirect action generation processes. In conclusion, we suggest that IdeomotorTheory offers a comprehensive framework to understand action-effect learning. However, we also suggest that additional processes may mediate the conversion of effect anticipations into actions in many situations.
Both specific stimulus valence and unspecific processing dynamics can influence evaluative responses. Eight experiments investigated their respective influence on evaluative judgments in the domain of stereotyping. Valence of stereotypic information and consistency-driven fluency were manipulated in an impression formation paradigm. When information about the to-be-evaluated target person was strongly valenced, no effects of consistency-driven fluency were observed. Higher cognitive processes, valence of inconsistent attributes, processing priority of category information, and impression formation instructions were ruled out as possible factors responsible for the non-occurrence of fluency effects. However, consistency-driven fluency did influence the evaluative judgment, if the information about a target person was not strongly valenced. It is therefore concluded that both stimulus valence and consistency-driven processing fluency play a role in evaluative judgments in the domain of stereotyping. The respective impact of stimulus valence is much stronger than the impact of unspecific processing dynamics, however. Implications for fluency research and the applied field of stereotype change are discussed.
A brain-computer interface (BCI) enables communication without movement based on brain signals measured with electroencephalography (EEG). BCIs usually rely on one of three types of signals: the P300 and other components of the event-related potential (ERP), steady state visual evoked potential (SSVEP), or event related desynchronization (ERD). Although P300 BCIs were introduced over twenty years ago, the past few years have seen a strong increase in P300 BCI research. This closed-loop BCI approach relies on the P300 and other components of the ERP, based on an oddball paradigm presented to the subject. In this paper, we overview the current status of P300 BCI technology, and then discuss new directions: paradigms for eliciting P300s; signal processing methods; applications; and hybrid BCIs. We conclude that P300 BCIs are quite promising, as several emerging directions have not yet been fully explored and could lead to improvements in bit rate, reliability, usability, and flexibility.
Introduction: Sleep disturbances are common in adolescents and adversely affect performance, social contact, and susceptibility to stress. We investigated the hypothesis of a relationship between sleep and health-related quality of life (HRQoL), and applied self- and proxy ratings. Materials and Methods: The sample comprised 92 adolescents aged 11–17 years. All participants and their parents completed a HRQoL measure and the Sleep Disturbance Scale for Children (SDSC ). Children with SDSC T -scores above the normal range (above 60) were classified as poor sleepers. Results: According to self- and proxy ratings, good sleepers reported significantly higher HRQoL than poor sleep- ers. Sleep disturbances were significantly higher and HRQoL significantly lower in self- as compared to parental ratings. Parent-child agreement was higher for subscales measuring observable aspects. Girls experienced significantly stronger sleep disturbances and lower self-rated HRQoL than boys. Discussion: Our findings support the positive relationship of sleep and HRQoL. Furthermore, parents significantly underestimate sleep disturbances and overestimate HRQoL in their children.