Dieser Beitrag zeigt die Integration der Körperzentrierten Psychotherapie die komplexe Behandlungsstruktur bei einer schizophrenen Erkrankung auf. Neben den gängigen Methoden der Pharmakotherapie sowie sozialpsychiatrischer und familientherapeutischer Betreuung trugen die Kombination von Körperzentrierter Psychotherapie mit dem Progressiven Therapeutischen Spiegelbild in dem angeführten Beispiel entscheidend zum positiven Behandlung sergebnis bei. Die körperzentrierte Methodik erlaubte trotz des verbal abwehrenden Verhaltens einen Zugang zum Patienten.

Dieses Kapitel regt den Praktiker an, bei Diagnostik und Therapie vermehrt die Möglichkeit einer dissoziativen Störung in Erwägung zu ziehen, diese als durch ein Trauma aktivierten Schutzmechanismus zu begreifen und sich nicht durch die Vielfalt von Symptomen irreführen zu lassen. Die Spezifität der Körperzentrierten Psychotherapie (KZPT) und deren Eignung zur Behandlung traumatischer Störungen wird eruiert. Es zeigt sich, dass die KZPT mit ihrer Berücksichtigung der verschiedenen Lebensdimensionen und durch ihre reichhaltigen Interventionsmöglichkeiten die Therapeuten in hohem Maße zur Arbeit mit traumatisierten Menschen befähigt.

Sjl2p is one of three yeast phosphoinositide 5′‐phosphatases that belong to the conserved family of synaptojanins. Here, we show that Sjl2p is specifically associated with cortical actin patches which aggregate upon loss of the actin‐regulating kinases Ark1p and Prk1p. The Sjl2p‐containing clumps overlap with clathrin and early endocytic structures generated independently of NSF/Sec18p, but not with endosome‐ and trans Golgi network‐derived membranes. Consistent with the finding that Sjl2p can bind to clathrin heavy chain in vitro, our results suggest that Sjl2p localizes to smooth endocytic vesicles that may be derived from clathrin‐coated structures.

A model based diagnosis procedure traces connections between components only where these are provided explicitly in the system description. Consequently structure faults fall between the meshes. This problem has been known since research started in this field ([Davis 84]), but no general solution has been presented so far. We present a procedure to diagnose structure faults, based on a scheme to detect hidden interactions guided by the observation that structure faults lead to discrepancies in apparently unrelated areas and which in contrast to [Preist. Welham 90] modifies the system description dynamically. Like Davis' approach the one presented in the paper is based on the principle that an interaction can occur only where components are adjacent in some way ([Davis 84]). Unlike Davis approach we introduce an explicit representation scheme for hidden interactions. A hidden interaction model links a required contextual, behaviour independent constellation to the impact of the interaction on the overall system behaviour. In order to control hidden interaction hypotheses we exploit the structure of diagnoses based on behavioural mode assignments.

In recent years reasoning about structure and function of physical systems for the purpose of diagnosis has seen a dramatic increase in activities. New exciting results concerning modelling issues, diagnostic inference patterns and inferential power have emerged. A state of the art diagnosis agent now has a considerable toolset at hand. A main obstacle for building large diagnosis systems, however, remains. How can we controlwhen to usewhich inference pattern or representation? We argue that the actions available to a diagnosis agent can be understood in terms of change ofworking hypotheses. The control problem then becomes a belief revision problem: when to adopt or drop beliefs. Our approach proceeds in two steps. First, we adopt the principle of informational economy from Gärdenfors, Knowledge in Flux (MIT Press, 1988) as kind of a law of inertia for diagnostic processes, that helps us identify candidates for revised belief states. In a second step we employ specificdiagnostic knowledge to actually choose the next belief state. We demonstrate the use of our concepts on an example in the domain of ballast tank systems as e.g. used in offshore plants.

A main obstacle for building large diagnosis systems is the problem of decidingwhen to usewhich inference pattern or representation. If diagnostic actions such as changing representations or applying specific inference patterns are understood in terms of change of working hypotheses, the control problem becomes a belief revision problem: when to adopt or drop beliefs. Our approach proceeds in two steps. First, we adopt the principle of informational economy as kind of a law of inertia for diagnostic processes. It proposes candidates for revised belief states. In a second step we employ specific diagnostic knowledge to actually choose the next belief state.