ROC Curves within the Framework of Neural Network Assembly Memory Model: Some Analytic Results

On the basis of convolutional (Hamming) version of recent Neural Network Assembly Memory Model (NNAMM) for intact two-layer autoassociative Hopfield network optimal receiver operating characteristics (ROCs) have been derived analytically. A method of taking into account explicitly a priori probabilities of alternative hypotheses on the structure of information initiating memory trace retrieval and modified ROCs (mROCs, a posteriori probabilities of correct recall vs. false alarm probability) are introduced. The comparison of empirical and calculated ROCs (or mROCs) demonstrates that they coincide quantitatively and in this way intensities of cues used in appropriate experiments may be estimated. It has been found that basic ROC properties which are one of experimental findings underpinning dual-process models of recognition memory can be explained within our one-factor NNAMM.

Trained Neural Network Characterizing Variables for Predicting Organic Retention by Nanofiltration Membranes

Many organic compounds cause an irreversible damage to human health and the ecosystem and are present in water resources. Among these hazard substances, phenolic compounds play an important role on the actual contamination. Utilization of membrane technology is increasing exponentially in drinking water production and waste water treatment. The removal of organic compounds by nanofiltration membranes is characterized not only by molecular sieving effects but also by membrane-solute interactions. Influence of the sieving parameters (molecular weight and molecular diameter) and the physicochemical interactions (dissociation constant and molecular hydrophobicity) on the membrane rejection of the organic solutes were studied. The molecular hydrophobicity is expressed as logarithm of octanol-water partition coefficient. This paper proposes a method used that can be used for symbolic knowledge extraction from a trained neural network, once they have been trained with the desired performance and is based on detect the more important variables in problems where exist multicolineality among the input variables.

Classification of Data to Extract Knowledge from Neural Networks

A major drawback of artificial neural networks is their black-box character. Therefore, the rule extraction algorithm is becoming more and more important in explaining the extracted rules from the neural networks. In this paper, we use a method that can be used for symbolic knowledge extraction from neural networks, once they have been trained with desired function. The basis of this method is the weights of the neural network trained. This method allows knowledge extraction from neural networks with continuous inputs and output as well as rule extraction. An example of the application is showed. This example is based on the extraction of average load demand of a power plant.

The Usage of Neural Networks for the Medical Diagnosis

The problem of cancer diagnosis from multi-channel images using the neural networks is investigated. The goal of this work is to classify the different tissue types which are used to determine the cancer risk. The radial basis function networks and backpropagation neural networks are used for classification. The results of experiments are presented.

Application of support vector machines on the basis of the first Hungarian bankruptcy model

In our study we rely on a data mining procedure known as support vector machine (SVM) on the database of the first Hungarian bankruptcy model. The models constructed are then contrasted with the results of earlier bankruptcy models with the use of classification accuracy and the area under the ROC curve. In using the SVM technique, in addition to conventional kernel functions, we also examine the possibilities of applying the ANOVA kernel function and take a detailed look at data preparation tasks recommended in using the SVM method (handling of outliers). The results of the models assembled suggest that a significant improvement of classification accuracy can be achieved on the database of the first Hungarian bankruptcy model when using the SVM method as opposed to neural networks.

Photovoltaic power forecast modeling with artificial neural networks

Dissertação de Mestrado, Engenharia Eletrónica e Telecomunicações, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2016

Functional and neural mechanisms of human fear conditioning: studies in healthy and brain-damaged individuals

Fear conditioning represents the learning process by which a stimulus, after repeated pairing with an aversive event, comes to evoke fear and becomes intrinsically aversive. This learning is essential to organisms throughout the animal kingdom and represents one the most successful laboratory paradigm to reveal the psychological processes that govern the expression of emotional memory and explore its neurobiological underpinnings. Although a large amount of research has been conducted on the behavioural or neural correlates of fear conditioning, some key questions remain unanswered. Accordingly, this thesis aims to respond to some unsolved theoretic and methodological issues, thus furthering our understanding of the neurofunctional basis of human fear conditioning both in healthy and brain-damaged individuals. Specifically, in this thesis, behavioural, psychophysiological, lesion and non-invasive brain stimulation studies were reported. Study 1 examined the influence of normal aging on context-dependent recall of extinction of fear conditioned stimulus. Study 2 aimed to determine the causal role of the ventromedial PFC (vmPFC) in the acquisition of fear conditioning by systematically test the effect of bilateral vmPFC brain-lesion. Study 3 aimed to interfere with the reconsolidation process of fear memory by the means of non-invasive brain stimulation (i.e. TMS) disrupting PFC neural activity. Finally, Study 4 aimed to investigate whether the parasympathetic – vagal – modulation of heart rate might reflect the anticipation of fearful, as compared to neutral, events during classical fear conditioning paradigm. Evidence reported in this PhD thesis might therefore provide key insights and deeper understanding of critical issues concerning the neurofunctional mechanisms underlying the acquisition, the extinction and the reconsolidation of fear memories in humans.

Changes In Motor Behavior During Pregnancy In Rats: The Basis For A Possible Animal Model Of Restless Legs Syndrome.

Pregnant women have a 2-3 fold higher probability of developing restless legs syndrome (RLS - sleep-related movement disorders) than general population. This study aims to evaluate the behavior and locomotion of rats during pregnancy in order to verify if part of these animals exhibit some RLS-like features. We used 14 female 80-day-old Wistar rats that weighed between 200 and 250 g. The rats were distributed into control (CTRL) and pregnant (PN) groups. After a baseline evaluation of their behavior and locomotor activity in an open-field environment, the PN group was inducted into pregnancy, and their behavior and locomotor activity were evaluated on days 3, 10 and 19 of pregnancy and in the post-lactation period in parallel with the CTRL group. The serum iron and transferrin levels in the CTRL and PN groups were analyzed in blood collected after euthanasia by decapitation. There were no significant differences in the total ambulation, grooming events, fecal boli or urine pools between the CTRL and PN groups. However, the PN group exhibited fewer rearing events, increased grooming time and reduced immobilization time than the CTRL group (ANOVA, p<0.05). These results suggest that pregnant rats show behavioral and locomotor alterations similar to those observed in animal models of RLS, demonstrating to be a possible animal model of this sleep disorder.

Neural Mechanisms And Delayed Gastric Emptying Of Liquid Induced Through Acute Myocardial Infarction In Rats.

Background: In pathological situations, such as acute myocardial infarction, disorders of motility of the proximal gut can trigger symptoms like nausea and vomiting. Acute myocardial infarction delays gastric emptying (GE) of liquid in rats. Objective: Investigate the involvement of the vagus nerve, α 1-adrenoceptors, central nervous system GABAB receptors and also participation of paraventricular nucleus (PVN) of the hypothalamus in GE and gastric compliance (GC) in infarcted rats. Methods: Wistar rats, N = 8-15 in each group, were divided as INF group and sham (SH) group and subdivided. The infarction was performed through ligation of the left anterior descending coronary artery. GC was estimated with pressure-volume curves. Vagotomy was performed by sectioning the dorsal and ventral branches. To verify the action of GABAB receptors, baclofen was injected via icv (intracerebroventricular). Intravenous prazosin was used to produce chemical sympathectomy. The lesion in the PVN of the hypothalamus was performed using a 1mA/10s electrical current and GE was determined by measuring the percentage of gastric retention (% GR) of a saline meal. Results: No significant differences were observed regarding GC between groups; vagotomy significantly reduced % GR in INF group; icv treatment with baclofen significantly reduced %GR. GABAB receptors were not conclusively involved in delaying GE; intravenous treatment with prazosin significantly reduced GR% in INF group. PVN lesion abolished the effect of myocardial infarction on GE. Conclusion: Gastric emptying of liquids induced through acute myocardial infarction in rats showed the involvement of the vagus nerve, alpha1- adrenergic receptors and PVN.Fundamento: Distúrbios da motilidade do intestino proximal no infarto agudo do miocárdio podem desencadear sintomas digestivos como náuseas e vômitos. O infarto do miocárdio ocasiona retardo do esvaziamento gástrico (EG) de líquido em ratos. Objetivo: Investigar se existe a influência do nervo vago (VGX), adrenoreceptores α-1, receptores GABAB do sistema nervoso central e participação do núcleo paraventricular (NPV) do hipotálamo no esvaziamento gástrico (EG) e complacência gástrica (CG) em ratos infartados. Métodos: Ratos Wistar (n = 8-15) foram divididos em: grupo infarto (INF), sham (SH) e subdivididos. O infarto foi realizado por ligadura da artéria coronária descendente anterior. A complacência gástrica foi estimada com curvas pressão-volume. Realizada vagotomia por secção dos ramos dorsal e ventral. Para verificar a ação dos receptores GABAB foi injetado baclofeno por via intra ventrículo-cerebral. Simpatectomia química foi realizada com prazosina intravenosa (iv), e na lesão do núcleo paraventricular do hipotálamo foi utilizada corrente elétrica de 1mA/10s, com esvaziamento gástrico determinado por medição da retenção gástrica (% RG) de uma refeição salina. Resultados: Não houve diferença significativa na CG. A vagotomia (VGX) reduziu significativamente a %RG; no grupo INF, o tratamento intra ventrículo-cerebral (ivc) com baclofeno reduziu significativamente a % RG; não houve conclusivamente envolvimento dos receptores GABAB em retardar o EG; o tratamento intravenoso com prazosina reduziu significativamente a %RG no grupo INF. A lesão do NPV aboliu o efeito do infarto do miocárdio no EG. Conclusão: O nervo vago, receptores α-adrenérgicos e núcleo paraventricular estão envolvidos no retardo do esvaziamento gástrico no infarto agudo do miocárdio em ratos.

Kinase Inhibitor Profile For Human Nek1, Nek6, And Nek7 And Analysis Of The Structural Basis For Inhibitor Specificity.

Human Neks are a conserved protein kinase family related to cell cycle progression and cell division and are considered potential drug targets for the treatment of cancer and other pathologies. We screened the activation loop mutant kinases hNek1 and hNek2, wild-type hNek7, and five hNek6 variants in different activation/phosphorylation statesand compared them against 85 compounds using thermal shift denaturation. We identified three compounds with significant Tm shifts: JNK Inhibitor II for hNek1(Δ262-1258)-(T162A), Isogranulatimide for hNek6(S206A), andGSK-3 Inhibitor XIII for hNek7wt. Each one of these compounds was also validated by reducing the kinases activity by at least 25%. The binding sites for these compounds were identified by in silico docking at the ATP-binding site of the respective hNeks. Potential inhibitors were first screened by thermal shift assays, had their efficiency tested by a kinase assay, and were finally analyzed by molecular docking. Our findings corroborate the idea of ATP-competitive inhibition for hNek1 and hNek6 and suggest a novel non-competitive inhibition for hNek7 in regard to GSK-3 Inhibitor XIII. Our results demonstrate that our approach is useful for finding promising general and specific hNekscandidate inhibitors, which may also function as scaffolds to design more potent and selective inhibitors.

Plasticidade neural: relações com o comportamento e abordagens experimentais

Behavioral adaptiveness to different situations as well as behavioral individuality result from the interrelations between environmental sitmuli and the responses of an organism.These kind of interrelationships also shape the neural circuits as well as characterize the plasticity and the neural individuality of the organism. Studies on neural plasticity may analyze changes in neural circuitry after environmental manipulations or changes in behavior after lesions in the nervous system. Issues on neural plasticity and recovery of function refer both to physiology and behavior as well as to the subjacent mechanisms related to morphology, biochemistry and genetics. They may be approached at the systemic, behavioral, cellular and molecular levels. This work intends to characterize these kinds of studies pointing to their relations with the analyis of behavior and learning.The analysis of how the environmental-organismic interrelationships affect the neural substrates of behavior is pointed as a very stimulating area for investigation.

Central chemoreceptors and neural mechanisms of cardiorespiratory control

The arterial partial pressure (P CO2) of carbon dioxide is virtually constant because of the close match between the metabolic production of this gas and its excretion via breathing. Blood gas homeostasis does not rely solely on changes in lung ventilation, but also to a considerable extent on circulatory adjustments that regulate the transport of CO2 from its sites of production to the lungs. The neural mechanisms that coordinate circulatory and ventilatory changes to achieve blood gas homeostasis are the subject of this review. Emphasis will be placed on the control of sympathetic outflow by central chemoreceptors. High levels of CO2 exert an excitatory effect on sympathetic outflow that is mediated by specialized chemoreceptors such as the neurons located in the retrotrapezoid region. In addition, high CO2 causes an aversive awareness in conscious animals, activating wake-promoting pathways such as the noradrenergic neurons. These neuronal groups, which may also be directly activated by brain acidification, have projections that contribute to the CO2-induced rise in breathing and sympathetic outflow. However, since the level of activity of the retrotrapezoid nucleus is regulated by converging inputs from wake-promoting systems, behavior-specific inputs from higher centers and by chemical drive, the main focus of the present manuscript is to review the contribution of central chemoreceptors to the control of autonomic and respiratory mechanisms.

Engagement of multifocal neural circuits during recall of autobiographical happy events

Happy emotional states have not been extensively explored in functional magnetic resonance imaging studies using autobiographic recall paradigms. We investigated the brain circuitry engaged during induction of happiness by standardized script-driven autobiographical recall in 11 healthy subjects (6 males), aged 32.4 ± 7.2 years, without physical or psychiatric disorders, selected according to their ability to vividly recall personal experiences. Blood oxygen level-dependent (BOLD) changes were recorded during auditory presentation of personal scripts of happiness, neutral content and negative emotional content (irritability). The same uniform structure was used for the cueing narratives of both emotionally salient and neutral conditions, in order to decrease the variability of findings. In the happiness relative to the neutral condition, there was an increased BOLD signal in the left dorsal prefrontal cortex and anterior insula, thalamus bilaterally, left hypothalamus, left anterior cingulate gyrus, and midportions of the left middle temporal gyrus (P < 0.05, corrected for multiple comparisons). Relative to the irritability condition, the happiness condition showed increased activity in the left insula, thalamus and hypothalamus, and in anterior and midportions of the inferior and middle temporal gyri bilaterally (P < 0.05, corrected), varying in size between 13 and 64 voxels. Findings of happiness-related increased activity in prefrontal and subcortical regions extend the results of previous functional imaging studies of autobiographical recall. The BOLD signal changes identified reflect general aspects of emotional processing, emotional control, and the processing of sensory and bodily signals associated with internally generated feelings of happiness. These results reinforce the notion that happiness induction engages a wide network of brain regions.

Structural and chemical basis for anticancer activity of a series of 'beta'-tubulin ligands: molecular modeling and 3D QSAR studies

An important approach to cancer therapy is the design of small molecule modulators that interfere with microtubule dynamics through their specific binding to the ²-subunit of tubulin. In the present work, comparative molecular field analysis (CoMFA) studies were conducted on a series of discodermolide analogs with antimitotic properties. Significant correlation coefficients were obtained (CoMFA(i), q² =0.68, r²=0.94; CoMFA(ii), q² = 0.63, r²= 0.91), indicating the good internal and external consistency of the models generated using two independent structural alignment strategies. The models were externally validated employing a test set, and the predicted values were in good agreement with the experimental results. The final QSAR models and the 3D contour maps provided important insights into the chemical and structural basis involved in the molecular recognition process of this family of discodermolide analogs, and should be useful for the design of new specific ²-tubulin modulators with potent anticancer activity.

Neural networks and statistical analysis for classification of corneal videokeratography maps based on Zernike coefficients: a quantitative comparison

PURPOSE: The main goal of this study was to develop and compare two different techniques for classification of specific types of corneal shapes when Zernike coefficients are used as inputs. A feed-forward artificial Neural Network (NN) and discriminant analysis (DA) techniques were used. METHODS: The inputs both for the NN and DA were the first 15 standard Zernike coefficients for 80 previously classified corneal elevation data files from an Eyesys System 2000 Videokeratograph (VK), installed at the Departamento de Oftalmologia of the Escola Paulista de Medicina, São Paulo. The NN had 5 output neurons which were associated with 5 typical corneal shapes: keratoconus, with-the-rule astigmatism, against-the-rule astigmatism, "regular" or "normal" shape and post-PRK. RESULTS: The NN and DA responses were statistically analyzed in terms of precision ([true positive+true negative]/total number of cases). Mean overall results for all cases for the NN and DA techniques were, respectively, 94% and 84.8%. CONCLUSION: Although we used a relatively small database, results obtained in the present study indicate that Zernike polynomials as descriptors of corneal shape may be a reliable parameter as input data for diagnostic automation of VK maps, using either NN or DA.