A neurophysiological fingerprint of the empty-chair dialogue

The empty chair dialogue is a validated technique used in Gestalt and emotion focused therapy to help clients overcome unresolved interpersonal grievances. It aims at influencing emotional processing in a way that emotional states characterized by advanced meaning making, thus by the integration of cognition and affect, are facilitated. Even though a variety of studies demonstrated the effectiveness of this technique as well as the usefulness of improvements in emotional processing, it remains unclear how these changes are characterized on a neuronal level. The present study aimed at tracing changes induced by the empty-chair dialogue with electrophysiological methods. Subjects reporting long-standing interpersonal grievances were recruited. After informed consent, an experienced therapist guided subjects to work on their individual interpersonal theme using the empty chair dialogue. During this one-session intervention, multichannel EEG was recorded and the session was video-taped. Afterwards, a validated observational rating instrument was used to identify time periods representing emotional states characterized by either high or low meaning making and the preprocessed, artifact-free EEG-data was labeled accordingly. Thus the comparison of neurophysiological activity during two distinct types of emotional processing becomes possible. EEG-data will be analyzed with modern methods of frequency analysis. Furthermore global field synchronization will be compared between the two types of emotional processing.

Collective Referential Intentionality in the Semantics of Dialogue

The concept of a dialogue is considered in general terms from the standpoint of its referential presuppositions. The semantics of dialogue implies that dialogue participants must generally have a collective intentionality of agreed-upon references that is minimally sufficient for them to be able to disagree about other things, and ideally for outstanding disagreements to become clearer at successive stages of the dialogue. These points are detailed and illustrated in a fictional dialogue, in which precisely these kinds of referential confusions impede progress in shared understanding. It is only through a continuous exchange of question and answer in this dialogue case study that the meanings of key terms and anaphorical references are disambiguated, and a relevantly complete collective intentionality of shared meaning between dialogue participants is achieved. The importance of a minimally shared referential semantics for the terms entering into reasoning and argument in dialogue contexts broadly construed cannot be over-estimated. Where to draw the line between referential agreement and disagreement within any chosen dialogue, as participants work toward better mutual understanding in clearing up referential incongruities, is sometimes among the dialogue’s main points of dispute.

Being Open, Being Faithful: The Journey of Interreligious Dialogue

What does Christian identity mean in the face of religious pluralism? In some ways, the frontier of global Christianity lies not in repairing its past divisions so much as bravely facing its future in a world of many other faiths and conflicting convictions. Being Open, Being Faithful is a brief history, astute analysis, and trustworthy guide for Christian encounters in this pluralistic environment. A central argument of this perceptive book is that interreligious dialogue has moved so far as to fundamentally change the attitudes and openness of world religious traditions to each other, promising a future more open and less hostile than one might otherwise think. The book presents and reflects on the recent history of interreligious encounter and dialogue, and it traces the manifold difficulties involved, especially as they are experienced in Roman Catholic and World Council of Churches' engagements with other faiths. Yet, it goes even further: along with the history of such encounters, Being Open, Being Faithful examines the issue of Christian discipleship in the context of interfaith engagement, the operative models, the thorny issue of core theological commitments, and what might be the shape of Christian identity in light of such encounters.

Microbe sampling by mucosal dendritic cells is a discrete, MyD88-independent step in DeltainvG S. Typhimurium colitis.

Intestinal dendritic cells (DCs) are believed to sample and present commensal bacteria to the gut-associated immune system to maintain immune homeostasis. How antigen sampling pathways handle intestinal pathogens remains elusive. We present a murine colitogenic Salmonella infection model that is highly dependent on DCs. Conditional DC depletion experiments revealed that intestinal virulence of S. Typhimurium SL1344 DeltainvG mutant lacking a functional type 3 secretion system-1 (DeltainvG)critically required DCs for invasion across the epithelium. The DC-dependency was limited to the early phase of infection when bacteria colocalized with CD11c(+)CX3CR1(+) mucosal DCs. At later stages, the bacteria became associated with other (CD11c(-)CX3CR1(-)) lamina propria cells, DC depletion no longer attenuated the pathology, and a MyD88-dependent mucosal inflammation was initiated. Using bone marrow chimeric mice, we showed that the MyD88 signaling within hematopoietic cells, which are distinct from DCs, was required and sufficient for induction of the colitis. Moreover, MyD88-deficient DCs supported transepithelial uptake of the bacteria and the induction of MyD88-dependent colitis. These results establish that pathogen sampling by DCs is a discrete, and MyD88-independent, step during the initiation of a mucosal innate immune response to bacterial infection in vivo.

Shallow Dialogue Processing Using Machine Learning Algorithms (or not)

This paper presents a shallow dialogue analysis model, aimed at human-human dialogues in the context of staff or business meetings. Four components of the model are defined, and several machine learning techniques are used to extract features from dialogue transcripts: maximum entropy classifiers for dialogue acts, latent semantic analysis for topic segmentation, or decision tree classifiers for discourse markers. A rule-based approach is proposed for solving cross-modal references to meeting documents. The methods are trained and evaluated thanks to a common data set and annotation format. The integration of the components into an automated shallow dialogue parser opens the way to multimodal meeting processing and retrieval applications.