Ultimate Questions of Science and the Theory of System Relations

Summary  Whenever an adequate theory is found in science, we will still be left with two questions: why this theory rather than some other theory, and how should this theory be interpreted? I argue that these questions can be answered by a theory of system relations. The basic idea is that fundamental characteristics of systems, viz. those arising from the general systemic nature of those systems, cannot be comprehended with the aid of discipline-specific methods. The systems theory required should commence with an analysis of the qualitatively different relations possible between systems, because it is precisely the nature of those relations that determines the basic structures of systems. That the theory of the fundamental system relations and their ontological and epistemological implications is indeed able to provide the answers sought is demonstrated in theoretical physics and Plessner’s analysis of the basic structures of plant, animal and human being.     

Emotion and Pain: A Functional Cerebral Systems Integration

Emotion and pain are psychological constructs that have received extensive attention in neuropsychological research. However, neuropsychological models of emotional processing have made more progress in describing how brain regions interact to process emotion. Theories of emotional processing can describe inter-hemispheric and intra-hemispheric interactions during emotional processing. Due to similarities between emotion and pain, it is thought that emotional models can be applied to pain. The following review examines the neuropsychology of emotion and pain using a functional cerebral systems approach. Specific comparisons are made between pain and anger. Attention is given to differences in cerebral function and physiology that may contribute to the processing of emotion and pain. Suggestions for future research in emotion and pain are given.     

Estrogen modulates place learning through estrogen receptors in the hippocampus

Moderate elevations in circulating estradiol enhance learning in tasks that tap place learning strategies such as those requiring the use of extramaze cues. Use of place learning strategies is particularly impaired by damage to the hippocampus, a structure shown to be sensitive to estrogen treatments. We have shown that direct estrogen infusions into the dorsal hippocampus, and not the dorsolateral striatum, enhance place learning, suggesting that the hippocampus may be an important modulatory site for the effects of estrogen on place learning. The current experiment tested whether the hippocampus is indeed a critical site of estrogen modulation through classical estrogen receptors. Young adult female Sprague-Dawley rats were ovariectomized for 21 days and given systemic injections (0.1 ml) of sesame oil (OIL) or 10 microg of 17beta-estradiol-benzoate (E2), 48 and 24 h before being trained on a place task. Twenty-four hours prior to the first systemic injection, separate groups of rats received bilateral hippocampal implants of either the antiestrogen ICI 182,780 (ICI) or cholesterol vehicle. Implants were maintained until and throughout training. Intrahippocampal ICI reversed the enhancement in place learning seen with systemic E2 treatment. Unexpectedly, intrahippocampal ICI in OIL-treated rats also enhanced place learning. These data suggest that ICI may have some mixed agonist and antagonist effects in the hippocampus and that estrogen enhances place learning through activation of estrogen receptors located in the hippocampus.     

Visual interaction: models, systems, prototypes. The Pictorial Computing Laboratory at the University of Rome “La Sapienza”

This paper reports on the research activities performed by the Pictorial Computing Laboratory at the University of Rome, La Sapienza, during the last 5 years. Such work, essentially is based on the study of humancomputer interaction, spans from metamodels of interaction down to prototypes of interactive systems for both synchronous multimedia communication and groupwork, annotation systems for web pages, also encompassing theoretical and practical issues of visual languages and environments also including pattern recognition algorithms. Some applications are also considered like e-learning and collaborative work.     

Systems for the Production of Plagiarists? The Implications Arising from the Use of Plagiarism Detection Systems in UK Universities for Asian Learners

This paper argues that the inappropriate framing and implementation of plagiarism detection systems in UK universities can unwittingly construct international students as ‘plagiarists’. It argues that these systems are often implemented with inappropriate assumptions about plagiarism and the way in which new members of a community of practice develop the skills to become full members of that community. Drawing on the literature and some primary data it shows how expectations, norms and practices become translated and negotiated in such a way that legitimate attempts to conform with the expectations of the community of practice often become identified as plagiarism and illegitimate attempts at cheating often become obscured from view. It argues that this inappropriate framing and implementation of plagiarism detection systems may make academic integrity more illusive rather than less. It argues that in its current framing – as systems for ‘detection and discipline’ – plagiarism detection systems may become a new micro-politics of power with devastating consequences for those excluded.     

Linear modeling of steady-state behavioral dynamics

The observed steady-state behavioral dynamics supported by unsignaled periods of reinforcement within repeating 2,000-s trials were modeled with a linear transfer function. These experiments employed improved schedule forms and analytical methods to improve the precision of the measured transfer function, compared to previous work. The refinements include both the use of multiple reinforcement periods that improve spectral coverage and averaging of independently determined transfer functions. A linear analysis was then used to predict behavior observed for three different test schedules. The fidelity of these predictions was determined.