Use of Mental Imagery in Psychotherapy: A Critical Review

The paper presents arguments in favor of the use of mental imagery for therapeutic purposes. Several existing imagery approaches to psychotherapy are critically examined and suggestions for future inquiry are offered. The intimate relation between imagery and the affective-somatic processes is stressed

Visualisation techniques, human perception and the built environment

Historically, architecture has a wealth of visualisation techniques that have evolved throughout the period of structural design, with Virtual Reality (VR) being a relatively recent addition to the toolbox. To date the effectiveness of VR has been demonstrated from conceptualisation through to final stages and maintenance, however, its full potential has yet to be realised (Bouchlaghem et al, 2005). According to Dewey (1934), perceptual integration was predicted to be transformational; as the observer would be able to ‘engage’ with the virtual environment. However, environmental representations are predominately focused on the area of vision, regardless of evidence stating that the experience is multi sensory. In addition, there is a marked lack of research exploring the complex interaction of environmental design and the user, such as the role of attention or conceptual interpretation. This paper identifies the potential of VR models to aid communication for the Built Environment with specific reference to human perception issues

Reading the Readers: Modelling Complex Humanities Processes to Build Cognitive Systems

The ink and stylus tablets discovered at the Roman Fort of Vindolanda are a unique resource for scholars of ancient history. However, the stylus tablets have proved particularly difficult to read. This paper describes the initial stages in the development of a computer system designed to aid historians in the reading of the stylus tablets. A detailed investigation was undertaken, using Knowledge Elicitation techniques borrowed from Artificial IntelliJOURce, Cognitive Psychology, and Computational Linguistics, to elicit the processes experts use whilst reading an ancient text. The resulting model was used as the basis of a computer architecture to construct a system which takes in images of the tablets and outputs plausible interpretations of the documents. It is demonstrated that using Knowledge Elicitation techniques can further the understanding of complex processes in the humanities, and that these techniques can provide an underlying structure for the basis of a computer system that replicates that process. As such it provides significant insight into how experts work in the humanities, whilst providing the means to develop tools to assist them in their complex task

Evidence for Information Processing in the Brain

Many cognitive and neuroscientists attempt to assign biological functions to brain structures. To achieve this end, scientists perform experiments that relate the physical properties of brain structures to organism-level abilities, behaviors, and environmental stimuli. Researchers make use of various measuring instruments and methodological techniques to obtain this kind of relational evidence, ranging from single-unit electrophysiology and optogenetics to whole brain functional MRI. Each experiment is intended to identify brain function. However, seemingly independent of experimental evidence, many cognitive scientists, neuroscientists, and philosophers of science assume that the brain processes information as a scientific fact. In this work we analyze categories of relational evidence and find that although physical features of specific brain areas selectively covary with external stimuli and abilities, and that the brain shows reliable causal organization, there is no direct evidence supporting the claim that information processing is a natural function of the brain. We conclude that the belief in brain information processing adds little to the science of cognitive science and functions primarily as a metaphor for efficient communication of neuroscientific data

User-centered visual analysis using a hybrid reasoning architecture for intensive care units

One problem pertaining to Intensive Care Unit information systems is that, in some cases, a very dense display of data can result. To ensure the overview and readability of the increasing volumes of data, some special features are required (e.g., data prioritization, clustering, and selection mechanisms) with the application of analytical methods (e.g., temporal data abstraction, principal component analysis, and detection of events). This paper addresses the problem of improving the integration of the visual and analytical methods applied to medical monitoring systems. We present a knowledge- and machine learning-based approach to support the knowledge discovery process with appropriate analytical and visual methods. Its potential benefit to the development of user interfaces for intelligent monitors that can assist with the detection and explanation of new, potentially threatening medical events. The proposed hybrid reasoning architecture provides an interactive graphical user interface to adjust the parameters of the analytical methods based on the users' task at hand. The action sequences performed on the graphical user interface by the user are consolidated in a dynamic knowledge base with specific hybrid reasoning that integrates symbolic and connectionist approaches. These sequences of expert knowledge acquisition can be very efficient for making easier knowledge emergence during a similar experience and positively impact the monitoring of critical situations. The provided graphical user interface incorporating a user-centered visual analysis is exploited to facilitate the natural and effective representation of clinical information for patient care