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We construct a neuronal network to model the logic of associative conditioning as revealed in experimental results using the terrestrial mollusk Limax maximus. We show, in particular, how blocking to a previously conditioned stimulus in the presence of the unconditional stimulus, can emerge as a dynamical property of the network. We also propose experiments to test the new model.
We present an analysis of the computational features of neural networks and fuzzy logic architectures which attempts to explain their recent popularity as well as their drawbacks. Based upon many reports in several fields, we identify the key computational requirements in the clinical laboratory setting, and review several classical tools. In particular we make the observation that all of these needs may be viewed as a search for an appropriate mathematical mapping. We suggest that the neural networks promise as a universal function approximant is the main source of its apparent attractivity. We then describe a customized neural network architecture as a non-linear, adaptive signal processor for integrated monitoring. This architecture is employed in the Adaptive Real-Time Anesthesiologist Associate (ARTAA) system, which has been developed as a joint project at the Department of Anesthesiology, Albert Einstein Medical Center and the Electrical and Computer Engineering Department, Drexel University in Philadelphia, USA. In this application the neural network realizes a non-linear scalar map from the set of physiological signals to a vital function status (VFS) indicator. The system is now under clinical testing.
In order to successfully engage in social exchange--cooperation between two or more individuals for mutual benefit--humans must be able to solve a number of complex computational problems, and do so with special efficiency. Following Marr (1982), Cosmides (1985) and Cosmides and Tooby (1989) used evolutionary principles to develop a computational theory of these adaptive problems. Specific hypotheses concerning the structure of the algorithms that govern how humans reason about social exchange were derived from this computational theory. This article presents a series of experiments designed to test these hypotheses, using the Wason selection task, a test of logical reasoning. Part I reports experiments testing social exchange theory against the availability theories of reasoning; Part II reports experiments testing it against Cheng and Holyoak's (1985) permission schema theory. The experimental design included eight critical tests designed to choose between social exchange theory and these other two families of theories; the results of all eight tests support social exchange theory. The hypothesis that the human mind includes cognitive processes specialized for reasoning about social exchange predicts the content effects found in these experiments, and parsimoniously explains those that have already been reported in the literature. The implications of this line of research for a modular view of human reasoning are discussed, as well as the utility of evolutionary biology in the development of computational theories.
Development of medical knowledge bases is a time-consuming process, and no single medical institution can develop medical knowledge bases covering all areas of medicine. The use of medical knowledge representation standards such as the Arden Syntax is an attempt to enhance the writability and readability of computer-stored knowledge and facilitate transfer and sharing among institutions. A method for the realisation of decision support systems based on knowledge formulated according to the Arden Syntax is presented. An essential tool in this process is a medical logic module (MLM) pre-compiler, translating MLMs into an object-oriented programming language, C++. Advantages of the C++ approach compared with other alternatives are discussed.
It is demonstrated how improvements of general multiple test procedures can be obtained using information about the logical structures among the hypotheses. Based on a procedure of Bergmann and Hommel (B. Bergmann and G. Hommel, Improvements of general multiple test procedures for redundant systems of hypotheses, in Multiple Hypothesenprüfung--Multiple Hypotheses Testing, Eds. P. Bauer, G. Hommel and E. Sonnemann, pp. 100-115 (Springer-Verlag, Berlin, 1988)), a computer program was written by Bernhard (G. Bernhard, Computerunterstützte Durchführung von multiplen Testprozeduren--Algorithmen und Powervergleich, Doctoral thesis (Mainz, 1992)) using this information. It is applicable for a general class of systems of hypotheses which can be expressed in a linear way. By means of a simulation study it is shown that the proposed procedure is often substantially more powerful than other usual multiple test procedures.
A method for solid-filling protein cavities is presented. The method uses a pattern-recognition technique based on cellular logic operations to distinguish between convex and concave regions of a protein. In doing this it solid fills protein cavities and automatically defines a boundary between cavity and exterior free space. The operations used to fill the cavities also can be used to process the filler to filter out small-scale features. So far the main use of the method has been in visualizing protein active sites for docking. The method can be used to find cavities of a given size range and could be used to find novel protein binding sites.
An algorithm has been developed that can be used to divide triangulated molecular surfaces into distinct domains on the basis of physical and topographical molecular properties. Domains are defined by a certain degree of homogeneity concerning one of these properties. The method is based on fuzzy logic strategies, thus taking into consideration the smooth changes of the properties considered along complex macromolecular surfaces. Scalar qualities assigned to every node point on a triangulated surface are translated into linguistic variables, which can then be processed using a special fuzzy dissimilarity operator. Possible applications are demonstrated using surface segmentation for properties like electrostatic potential, lipophilicity and shape for the analysis of serine proteinase substrate/inhibitor specificity.
The effectiveness of specific training in statistics and decision-making principles upon physicians' judgmental skills was assessed by means of problems of intuitive logical reasoning. The responses of 43 statistically sophisticated physicians (SP) were compared to those of 42 practicing physicians (PP), 43 clinical nurses (CN) and 41 hospital laborers (HL). On problems evaluating use of faulty heuristics in judgments of conditional probabilities, the SP group's responses were the most biased. The proportion of subjects displaying consistent use of a particular heuristic in solving the three problems were 0.36 (SP), 0.45 (PP), 0.35 (CN) and 0.41 (HL). On problems assessing use of prevalence rate data in estimating probabilities, SP performed substantially better than the other three groups: 34% of their responses were accurate. However, 37% of their responses reflected ignorance of prevalence information concepts. We conclude that intensive statistical and decision-making training of physicians is likely to be of only limited value for improving clinicians' judgmental skills.
'Risk' is a widely used concept in literatures related to health, health care and medicine. In recent decades, three bodies of literature have emerged in which 'risk' is the primary focus of concern: Health Risk Appraisal, the Risk Approach and Risk Analysis/Assessment/Management. These literatures overlook important concepts and theoretical developments in contemporary social science. They also lack conceptual coherence. Reduction of incoherence will require re-examination of the epistemology of risk in relation to both its language and its logic in light of developments in social science.
Neurons in the central nervous system of mammals and many other species receive most of their synaptic inputs in their dendritic branches and spines, but the precise manner in which this information is processed in the dendrites is not understood. In order to gain insight into these mechanisms, simulations of interactions between distal dendritic spines with an excitable membrane have been carried out, using an electrical circuit analysis program for the compartmental representation of a dendrite and several spines. Interactions between responses to single and paired excitatory and inhibitory synaptic inputs have been analyzed. Basic logic operations, including AND gates, OR gates and AND-NOT gates, arise from these interactions. The results suggest the computational power and precision of excitable spines in distal branches of neuronal dendrites, especially those of pyramidal neurons in the cerebral cortex. The applicability to information processing in distal dendrites is discussed.
Logic, a fundamental component of research in the exact sciences is often not applied in prominent fields of medical research. Investigation into the aetiopathogenesis of headache, vertigo, and fatigue--acknowledged as the commonest and amongst the most prominent and debilitating of symptoms known to mankind--may be significantly impeded because of this. The "Notion of Untenability", upon which this premise is based, is articulated. Physicians investigating the aetiopathogenesis of headache, vertigo and fatigue generally neglect examining a major part of the head, namely the mandible, maxillae and their appendages, thereby contravening the fundamental principle of medicine of properly examining the patient before making a diagnosis or prescribing treatment. It is irrational to suppose that one can obtain the same amount of information from the examination of only a part of the head that one could obtain from examining the whole head. Other prominent examples of illogic in medical research are also discussed. Recognition that a serious conceptual and methodological problem does exist is seen as a prerequisite for further progress being made in these fields.
Although children take over a year to learn the meanings of the first three number words, they eventually master the logic of counting and the meanings of all the words in their count list. Here, we ask whether children's knowledge applies to number words beyond those they have mastered: Does a child who can only count to 20 infer that number words above 'twenty' refer to exact cardinal values? Three experiments provide evidence for this understanding in preschool children. Before beginning formal education or gaining counting skill, children possess a productive symbolic system for representing number.
In this paper, we describe a combined approach with fuzzy logic and structure tensor towards improved enhancement of possible MCs (microcalcifications) in digital mammograms. The proposed contrast enhancement algorithm has two operational components. One is structure tensor operator and the other is fuzzy enhancement operator, both of which are arranged in parallel to process the input digital mammograms. While the structure tensor operator processes the digital mammograms and produces a corresponding eigen-image to highlight the region-of-interests, the fuzzy enhancement operator fuzzifies the mammogram via the maximum fuzzy entropy principle in fuzzy domain. As a result, the local fuzzy contrast can be extracted and modified adaptively in accordance with the information provided by the eigen-image, and those non-MCs regions are suppressed by being taken as noise. After that, the mammogram is transformed back to the pixel domain and the enhanced mammogram is constructed. Extensive experimental results show that our proposed algorithm outperforms the existing benchmark in terms of cost figures across the whole range of true positive fractions (TPF).
Following neural network simulations of the two experiments of, argued that the opposition logic advocated by was incapable of distinguishing between single and multiple influences on performance of artificial grammar learning and more generally. We show that their simulations do not support their conclusions. We also provide different neural network simulations that do simulate the essential results of Higham et al. (2000).
The high-pressure inactivation (200 to 600 MPa) of Lactococcus lactis ssp. cremoris MG 1363 suspended in milk buffer was investigated with both experimental and theoretical methods. The inactivation kinetics were characterised by the determination of the viable cell counts, cell counts of undamaged cells, LmrP activity, membrane integrity, and metabolic activity. Pressures between 200 and 600 MPa were applied, and pressure holding times were varied between 0 and 120 min. Experiments were carried out in milk buffer at pH values ranging between 4.0 and 6.5, and the effect of the addition of molar concentrations of NaCl and sucrose was furthermore determined. The inactivation curves of L. lactis, as characterised by viable cell counts, exhibited typical sigmoid asymmetric shapes. Generally, inactivation of the membrane transport system LmrP was the most sensitive indicator of pressure-induced sublethal injury. Furthermore, the metabolic activity was inactivated concomitant with or prior to the loss of viability. Membrane integrity was lost concomitant with or later than cell death. For example, treatments at 200 MPa for 60 min in milk buffer did not inactivate L. lactis, but fully inactivated LmrP activity and reduced the metabolic activity by 50%. The membrane integrity was unaffected. Thus, the assay systems chosen are suitable to dissect the multistep high-pressure inactivation of L. lactis ssp. cremoris MG 1363. A fuzzy logic model accounting for the specific knowledge on the multistep pressure inactivation and allowing the prediction of the quantities of sublethally damaged cells was formulated. Furthermore, the fuzzy model could be used to accurately predict pressure inactivation of L. lactis using conditions not taken into account in model generation. It consists of 160 rules accounting for several dependent and independent variables. The rules were generated automatically with fuzzy clustering methods and rule-oriented statistical analysis. The set is open for the integration of further knowledge-based rules. A very good overall agreement between measured and predicted values was obtained. Single, deviating results have been identified and can be explained to be measurement errors or model intrinsic deficiencies.
Trabecular bone fractures heal through intramembraneous ossification. This process differs from diaphyseal fracture healing in that the trabecular marrow provides a rich vascular supply to the healing bone, there is very little callus formation, woven bone forms directly without a cartilage intermediary, and the woven bone is remodelled to form trabecular bone. Previous studies have used numerical methods to simulate diaphyseal fracture healing or bone remodelling, however not trabecular fracture healing, which involves both tissue differentiation and trabecular formation. The objective of this study was to determine if intramembraneous bone formation and remodelling during trabecular bone fracture healing could be simulated using the same mechanobiological principles as those proposed for diaphyseal fracture healing. Using finite element analysis and the fuzzy logic for diaphyseal healing, the model simulated formation of woven bone in the fracture gap and subsequent remodelling of the bone to form trabecular bone. We also demonstrated that the trabecular structure is dependent on the applied loading conditions. A single model that can simulate bone healing and remodelling may prove to be a useful tool in predicting musculoskeletal tissue differentiation in different vascular and mechanical environments.
Questions and the logical principle of contradiction became a formal basis of scientific research and education in the newly founded universities in the 1200s. With the advent of experimental methods in the 1700s, the scholastic method of disputing questions as exclusive source for research and teaching disappeared. However, those times' stringent continuum of questions, answers and further questions corresponds to today's empirical science with hypotheses, tests and new hypotheses. This paper summarizes background information to the scientific methods of disputing questions and testing hypotheses. While both questions and answers are necessary for research and education, it is suggested that the generation of questions and hypotheses, i.e., propositions about observations or ideas which can be disputed and empirically examined, drives scientific progress. Importantly, questions are necessary tools to challenge locked-in concepts and to instigate new avenues. It is concluded that questions and hypotheses as their formal expression must be strongly encouraged: appropriate answers and crucial tests will ultimately follow.
The purpose of this work was to apply fuzzy logic image processing techniques to characterize the trabecular bone structure with high-resolution magnetic resonance images. Fifteen ex vivo high-resolution magnetic resonance images of specimens of human radii at 1.5 T and 12 in vivo high-resolution magnetic resonance images of the calcanei of peri- and postmenopausal women at 3 T were obtained. Soft segmentation using fuzzy clustering was applied to MR data to obtain fuzzy bone volume fraction maps, which were then analyzed with three-dimensional (3D) fuzzy geometrical parameters and measures of fuzziness. Geometrical parameters included fuzzy perimeter and fuzzy compactness, while measures of fuzziness included linear index of fuzziness, quadratic index of fuzziness, logarithmic fuzzy entropy, and exponential fuzzy entropy. Fuzzy parameters were validated at 1.5 T with 3D structural parameters computed from microcomputed tomography images, which allow the observation of true trabecular bone structure and with apparent MR structural indexes at 1.5 T and 3 T. The validation was statistically performed with the Pearson correlation coefficient as well as with the Bland-Altman method. Bone volume fraction correlation values (r) were up to .99 (P<.001) with good agreements based on Bland-Altman analysis showing that fuzzy clustering is a valid technique to quantify this parameter. Measures of fuzziness also showed consistent correlations to trabecular number parameters (r>.85; P<.001) and good agreements based on Bland-Altman analysis, suggesting that the level of fuzziness in high-resolution magnetic resonance images could be related to the trabecular bone structure.