Neural network modelling of the wave-structure interaction processes

This thesis presents a new Artificial Neural Network (ANN) able to predict at once the main parameters representative of the wave-structure interaction processes, i.e. the wave overtopping discharge, the wave transmission coefficient and the wave reflection coefficient. The new ANN has been specifically developed in order to provide managers and scientists with a tool that can be efficiently used for design purposes. The development of this ANN started with the preparation of a new extended and homogeneous database that collects all the available tests reporting at least one of the three parameters, for a total amount of 16’165 data. The variety of structure types and wave attack conditions in the database includes smooth, rock and armour unit slopes, berm breakwaters, vertical walls, low crested structures, oblique wave attacks. Some of the existing ANNs were compared and improved, leading to the selection of a final ANN, whose architecture was optimized through an in-depth sensitivity analysis to the training parameters of the ANN. Each of the selected 15 input parameters represents a physical aspect of the wave-structure interaction process, describing the wave attack (wave steepness and obliquity, breaking and shoaling factors), the structure geometry (submergence, straight or non-straight slope, with or without berm or toe, presence or not of a crown wall), or the structure type (smooth or covered by an armour layer, with permeable or impermeable core). The advanced ANN here proposed provides accurate predictions for all the three parameters, and demonstrates to overcome the limits imposed by the traditional formulae and approach adopted so far by some of the existing ANNs. The possibility to adopt just one model to obtain a handy and accurate evaluation of the overall performance of a coastal or harbor structure represents the most important and exportable result of the work.

Long-term potentiation and neural network activity in the neonatal rat cerebral cortex in vivo

Long-term potentiation in the neonatal rat rnbarrel cortex in vivo rnLong-term potentiation (LTP) is important for the activity-dependent formation of early cortical circuits. In the neonatal rodent barrel cortex LTP has been so far only studied in vitro. I combined voltage-sensitive dye imaging with extracellular multi-electrode recordings to study whisker stimulation-induced LTP for both the slope of field potential and the number of multi-unit activity in the whisker-to-barrel cortex pathway of the neonatal rat barrel cortex in vivo. Single whisker stimulation at 2 Hz for 10 min induced an age-dependent expression of LTP in postnatal day (P) 0 to P14 rats with the strongest expression of LTP at P3-P5. The magnitude of LTP was largest in the stimulated barrel-related column, smaller in the surrounding septal region and no LTP could be observed in the neighboring barrel. Current source density analyses revealed an LTP-associated increase of synaptic current sinks in layer IV / lower layer II/III at P3-P5 and in the cortical plate / upper layer V at P0-P1. This study demonstrates for the first time an age-dependent and spatially confined LTP in the barrel cortex of the newborn rat in vivo. These activity-dependent modifications during the critical period may play an important role in the development and refinement of the topographic map in the barrel cortex. (An et al., 2012)rnEarly motor activity triggered by gamma and spindle bursts in neonatal rat motor cortexrnSelf-generated neuronal activity generated in subcortical regions drives early spontaneous motor activity, which is a hallmark of the developing sensorimotor system. However, the neuronal activity patterns and functions of neonatal primary motor cortex (M1) in the early movements are still unknown. I combined voltage-sensitive dye imaging with simultaneous extracellular multi-electrode recordings in the neonatal rat S1 and M1 in vivo. At P3-P5, gamma and spindle bursts observed in M1 could trigger early paw movements. Furthermore, the paw movements could be also elicited by the focal electrical stimulation of M1 at layer V. Local inactivation of M1 could significantly attenuate paw movements, suggesting that the neonatal M1 operates in motor mode. In contrast, the neonatal M1 can also operate in sensory mode. Early spontaneous movements and sensory stimulations of paw trigger gamma and spindle bursts in M1. Blockade of peripheral sensory input from the paw completely abolished sensory evoked gamma and spindle bursts. Moreover, both sensory evoked and spontaneously occurring gamma and spindle bursts mediated interactions between S1 and M1. Accordingly, local inactivation of the S1 profoundly reduced paw stimulation-induced and spontaneously occurring gamma and spindle bursts in M1, indicating that S1 plays a critical role in generation of the activity patterns in M1. This study proposes that both self-generated and sensory evoked gamma and spindle bursts in M1 may contribute to the refinement and maturation of corticospinal and sensorimotor networks required for sensorimotor coordination.rn

Development of Dynamic Constraint Models for a Model Based Transient Calibration Process

Model based calibration has gained popularity in recent years as a method to optimize increasingly complex engine systems. However virtually all model based techniques are applied to steady state calibration. Transient calibration is by and large an emerging technology. An important piece of any transient calibration process is the ability to constrain the optimizer to treat the problem as a dynamic one and not as a quasi-static process. The optimized air-handling parameters corresponding to any instant of time must be achievable in a transient sense; this in turn depends on the trajectory of the same parameters over previous time instances. In this work dynamic constraint models have been proposed to translate commanded to actually achieved air-handling parameters. These models enable the optimization to be realistic in a transient sense. The air handling system has been treated as a linear second order system with PD control. Parameters for this second order system have been extracted from real transient data. The model has been shown to be the best choice relative to a list of appropriate candidates such as neural networks and first order models. The selected second order model was used in conjunction with transient emission models to predict emissions over the FTP cycle. It has been shown that emission predictions based on air-handing parameters predicted by the dynamic constraint model do not differ significantly from corresponding emissions based on measured air-handling parameters.

Development of a model-based transient calibration process for diesel engine electronic control module tables – Part 2: modelling and optimization

This is the second part of a study investigating a model-based transient calibration process for diesel engines. The first part addressed the data requirements and data processing required for empirical transient emission and torque models. The current work focuses on modelling and optimization. The unexpected result of this investigation is that when trained on transient data, simple regression models perform better than more powerful methods such as neural networks or localized regression. This result has been attributed to extrapolation over data that have estimated rather than measured transient air-handling parameters. The challenges of detecting and preventing extrapolation using statistical methods that work well with steady-state data have been explained. The concept of constraining the distribution of statistical leverage relative to the distribution of the starting solution to prevent extrapolation during the optimization process has been proposed and demonstrated. Separate from the issue of extrapolation is preventing the search from being quasi-static. Second-order linear dynamic constraint models have been proposed to prevent the search from returning solutions that are feasible if each point were run at steady state, but which are unrealistic in a transient sense. Dynamic constraint models translate commanded parameters to actually achieved parameters that then feed into the transient emission and torque models. Combined model inaccuracies have been used to adjust the optimized solutions. To frame the optimization problem within reasonable dimensionality, the coefficients of commanded surfaces that approximate engine tables are adjusted during search iterations, each of which involves simulating the entire transient cycle. The resulting strategy, different from the corresponding manual calibration strategy and resulting in lower emissions and efficiency, is intended to improve rather than replace the manual calibration process.

LIF promotes neurogenesis and maintains neural precursors in cell populations derived from spiral ganglion stem cells

BACKGROUND: Stem cells with the ability to form clonal floating colonies (spheres) were recently isolated from the neonatal murine spiral ganglion. To further examine the features of inner ear-derived neural stem cells and their derivatives, we investigated the effects of leukemia inhibitory factor (LIF), a neurokine that has been shown to promote self-renewal of other neural stem cells and to affect neural and glial cell differentiation. RESULTS: LIF-treatment led to a dose-dependent increase of the number of neurons and glial cells in cultures of sphere-derived cells. Based on the detection of developmental and progenitor cell markers that are maintained in LIF-treated cultures and the increase of cycling nestin-positive progenitors, we propose that LIF maintains a pool of neural progenitor cells. We further provide evidence that LIF increases the number of nestin-positive progenitor cells directly in a cell cycle-independent fashion, which we interpret as an acceleration of neurogenesis in sphere-derived progenitors. This effect is further enhanced by an anti-apoptotic action of LIF. Finally, LIF and the neurotrophins BDNF and NT3 additively promote survival of stem cell-derived neurons. CONCLUSION: Our results implicate LIF as a powerful tool to control neural differentiation and maintenance of stem cell-derived murine spiral ganglion neuron precursors. This finding could be relevant in cell replacement studies with animal models featuring spiral ganglion neuron degeneration. The additive effect of the combination of LIF and BDNF/NT3 on stem cell-derived neuronal survival is similar to their effect on primary spiral ganglion neurons, which puts forward spiral ganglion-derived neurospheres as an in vitro model system to study aspects of auditory neuron development.

Analysis of postprandial lipemia as a Cardiovascular Disease risk factor using genetic and clinical information: an Artificial Neural Network perspective

Clinical studies indicate that exaggerated postprandial lipemia is linked to the progression of atherosclerosis, leading cause of Cardiovascular Diseases (CVD). CVD is a multi-factorial disease with complex etiology and according to the literature postprandial Triglycerides (TG) can be used as an independent CVD risk factor. Aim of the current study is to construct an Artificial Neural Network (ANN) based system for the identification of the most important gene-gene and/or gene-environmental interactions that contribute to a fast or slow postprandial metabolism of TG in blood and consequently to investigate the causality of postprandial TG response. The design and development of the system is based on a dataset of 213 subjects who underwent a two meals fatty prandial protocol. For each of the subjects a total of 30 input variables corresponding to genetic variations, sex, age and fasting levels of clinical measurements were known. Those variables provide input to the system, which is based on the combined use of Parameter Decreasing Method (PDM) and an ANN. The system was able to identify the ten (10) most informative variables and achieve a mean accuracy equal to 85.21%.

Computer-aided diagnosis of carotid atherosclerosis based on ultrasound image statistics, laws' texture and neural networks

Quantitative characterisation of carotid atherosclerosis and classification into symptomatic or asymptomatic is crucial in planning optimal treatment of atheromatous plaque. The computer-aided diagnosis (CAD) system described in this paper can analyse ultrasound (US) images of carotid artery and classify them into symptomatic or asymptomatic based on their echogenicity characteristics. The CAD system consists of three modules: a) the feature extraction module, where first-order statistical (FOS) features and Laws' texture energy can be estimated, b) the dimensionality reduction module, where the number of features can be reduced using analysis of variance (ANOVA), and c) the classifier module consisting of a neural network (NN) trained by a novel hybrid method based on genetic algorithms (GAs) along with the back propagation algorithm. The hybrid method is able to select the most robust features, to adjust automatically the NN architecture and to optimise the classification performance. The performance is measured by the accuracy, sensitivity, specificity and the area under the receiver-operating characteristic (ROC) curve. The CAD design and development is based on images from 54 symptomatic and 54 asymptomatic plaques. This study demonstrates the ability of a CAD system based on US image analysis and a hybrid trained NN to identify atheromatous plaques at high risk of stroke.

Understanding Neural Maps with Topographica

The biological function of neurons can often be understood only in the context of large, highly interconnected networks. These networks typically form two-dimensional topographic maps, such as the retinotopic maps in mammalian visual cortex. Computational simulations of these areas have led to valuable insights about how cortical topography develops and functions, but further progress has been hindered due to the lack of appropriate simulation tools. This paper introduces the freely available Topographica maplevel simulator, originally developed at the University of Texas at Austin and now maintained at the University of Edinburgh, UK. Topographica is designed to make large-scale, detailed models practical. The goal is to allow neuroscientists and computational scientists to work together to understand how topographic maps and their connections organize and operate. This understanding will be crucial for integrating experimental observations into a comprehensive theory of brain function.

Special Issue: Interactive Educational Media for the Neural and Cognitive Sciences

Understanding the functioning of brains is an extremely challenging endeavour - both for researches as well as for students. Interactive media and tools, like simulations, databases and visualizations or virtual laboratories proved to be not only indispensable in research but also in education to help understanding brain function. Accordingly, a wide range of such media and tools are now available and it is getting increasingly difficult to see an overall picture. Written by researchers, tool developers and experienced academic teachers, this special issue of Brains, Minds & Media covers a broad range of interactive research media and tools with a strong emphasis on their use in neural and cognitive sciences education. The focus lies not only on the tools themselves, but also on the question of how research tools can significantly enhance learning and teaching and how a curricular integration can be achieved. This collection gives a comprehensive overview of existing tools and their usage as well as the underlying educational ideas and thus provides an orientation guide not only for teaching researchers but also for interested teachers and students.

Neuroretina specification in mouse embryos requires Six3-mediated suppression of Wnt8b in the anterior neural plate.

Retinal degeneration causes vision impairment and blindness in humans. If one day we are to harness the potential of stem cell-based cell replacement therapies to treat these conditions, it is imperative that we better understand normal retina development. Currently, the genes and mechanisms that regulate the specification of the neuroretina during vertebrate eye development remain unknown. Here, we identify sine oculis-related homeobox 3 (Six3) as a crucial player in this process in mice. In Six3 conditional-mutant mouse embryos, specification of the neuroretina was abrogated, but that of the retinal pigmented epithelium was normal. Conditional deletion of Six3 did not affect the initial development of the optic vesicle but did arrest subsequent neuroretina specification. Ectopic rostral expansion of Wnt8b expression was the major response to Six3 deletion and the leading cause for the specific lack of neuroretina, as ectopic Wnt8b expression in transgenic embryos was sufficient to suppress neuroretina specification. Using chromatin immunoprecipitation assays, we identified Six3-responsive elements in the Wnt8b locus and demonstrated that Six3 directly repressed Wnt8b expression in vivo. Our findings provide a molecular framework to the program leading to neuroretina differentiation and may be relevant for the development of novel strategies aimed at characterizing and eventually treating different abnormalities in eye formation.

Functional studies of homeobox gene {\it Cart1\/} during mouse development

Cart1 is a paired-class homeobox-containing gene that is expressed in head mesenchyme, branchial arches, limb buds, and various cartilages during embryogenesis. To understand the role of Cart1 during mammalian development, I generated Cart1-mutant mice by gene targeting in mouse embryonic stem cells. Cart1-homozygous mutants were born alive but all died soon after birth. Most had acrania (absence of the cranial vault) and meroanencephaly (absence of part of the brain). In situ hybridization studies showed that Cart1 is expressed specifically in forebrain mesenchyme but not in midbrain or hindbrain mesenchyme nor in the neural tube. Developmental studies revealed a transient deficiency of forebrain mesenchyme cells due to apoptosis associated with a delay in neural tube closure in that region. Subsequently, the forebrain region became filled with mesenchyme and closed, however, the midbrain neural tube region never initiated closure and remained open. These results suggest that Cart1 is required for the survival of forebrain mesenchyme and that its absence disrupts cranial neural tube morphogenesis by blocking the initiation of closure in the midbrain region, and this ultimately leads to the generation of lethal craniofacial defects. Prenatal treatment of Cart1 homozygous mutants with folic acid suppressed the development of the acrania/meroanencephaly phenotype. Thus, Cart1 mutant mice provide a novel animal model for understanding the cellular, molecular, and genetic etiology of neural tube defects and for the development of prenatal therapeutic protocols using folic acid. ^

Neural tube defects in Mexican-Americans living on the US-Mexico border: The effects of folic acid and dietary folate

Neural tube defects (NTDs) are malformations of the developing brain and spinal cord; the most common are anencephaly and spina bifida. Evidence from many populations suggests that 50% of NTDs can be prevented through daily consumption of folic acid. A recent study has reported that folic acid may not protect populations of Mexican descent. This finding has serious implications for women living along the US-Mexico border. Not only is risk high in these Mexican American women compared with other US women; they also differ markedly in supplemental folic acid and dietary folate consumption, and in NTD-related risks (e.g., obesity, diabetes). This case-control study investigated whether folic acid supplements and dietary folate reduces NTDs in Mexican Americans. Cases included liveborn, stillborn, electively and spontaneously aborted NTD-affected fetuses and infants occurring in the 14-county Texas-Mexico border. Controls were randomly selected from unaffected live births, frequency matched to cases by hospital and year. An in-person interview of 110 case and 113 control mothers solicited data on folic acid supplements, dietary folate, and other covariates. Consumption of folic acid-containing vitamins before conception was only 5% for both case and control women. Taking vitamins the trimester before conception had no apparent effect, after adjusting for covariates [odds ratio (OR) = 1.0, 95% confidence interval (CI) = 0.3–3.4]. Combining folate from vitamins and diet showed a 20% risk reduction for women consuming at least 400 μg of folate daily [OR = 0.8, 95% CI = 0.5–1.5]; however, this estimate is statistically indistinguishable from the null. Although consistent with an inherent ineffectiveness of supplemental folic acid, that so few women consumed multivitamins during the critical time severely limited the assessment of folic acid in this population. A reduced folate response in Mexican descent women may be due to a genetic heterogeneity for metabolizing folate. Alternatively, folate intakes may be insufficient to overcome other underlying risk factors. In conclusion, determining whether folic acid reduces NTD risk in Mexican American women requires further study in populations with higher folic acid exposures. Meanwhile, we should pursue all recommended prevention strategies to reduce risk, including motivating Mexican American women of childbearing age to take folic acid routinely. ^

Comparative Behavioral and Neural Effects of Tryptophan and Catecholamine Depletion in Remitted Depression

Background: Despite immense efforts into development of new antidepressant drugs, the increases of serotoninergic and catechominergic neurotransmission have remained the two major pharmacodynamic principles of current drug treatments for depression. Consequently, psychopathological or biological markers that predict response to drugs that selectively increase serotonin and/or catecholamine neurotransmission hold the potential to optimize the prescriber’s selection among currently available treatment options. The aim of this study was to elucidate the differential symptomatology and neurophysiology in response to reductions in serotonergic versus catecholaminergic neurotransmission in subjects at high risk of depression recurrence. Methods: Using identical neuroimaging procedures with [18F] fluorodeoxyglucose positron emission tomography after tryptophan depletion (TD) and catecholamine depletion (CD), subjects with remitted depression were compared to healthy controls in a double-blind, randomized, crossover design. Results: While TD induced significantly more depressed mood, sadness and hopelessness than CD, CD induced more inactivity, concentration difficulties, lassitude and somatic anxiety than TD. CD specifically increased glucose metabolism in the bilateral ventral striatum and decreased glucose metabolism in the bilateral orbitofrontal cortex, whereas TD specifically increased metabolism in the right prefrontal cortex and the posterior cingulate cortex (PCC). While we found direct associations between changes in brain metabolism and induced depressive symptoms following CD, the relationship between neural activity and symptoms was less clear after TD. Conclusions: In conclusion, this study showed that serotonin and catecholamines play common and differential roles in the pathophysiology of depression.

Neural change following different memory training approaches in very preterm born children - A pilot study.

OBJECTIVE There is mixed evidence regarding neural change following cognitive training. Brain activation increase, decrease, or a combination of both may occur. We investigated training-induced neural change using two different memory training approaches. METHODS Very preterm born children (aged 7-12 years) were randomly allocated to a memory strategy training, an intensive working memory practice or a waiting control group. Before and immediately after the trainings and the waiting period, brain activation during a visual working memory task was measured using fMRI and cognitive performance was assessed. RESULTS Following both memory trainings, there was a significant decrease of fronto-parietal brain activation and a significant increase of memory performance. In the control group, no neural or performance change occurred after the waiting period. CONCLUSION These pilot data point towards a training-related decrease of brain activation, independent of the training approach. Our data highlight the high training-induced plasticity of the child's brain during development.

Usage of Complementary Medicine in Switzerland: Results of the Swiss Health Survey 2012 and Development Since 2007

Background Complementary medicine (CM) is popular in Switzerland. Several CM methods (traditional Chinese medicine/acupuncture, homeopathy, anthroposophic medicine, neural therapy, and herbal medicine) are currently covered by the mandatory basic health insurance when performed by a certified physician. Treatments by non-medical therapists are partially covered by a supplemental and optional health insurance. In this study, we investigated the frequency of CM use including the evolvement over time, the most popular methods, and the user profile. Methods Data of the Swiss Health Surveys 2007 and 2012 were used. In 2007 and 2012, a population of 14,432 and 18,357, respectively, aged 15 years or older answered the written questionnaire. A set of questions queried about the frequency of use of various CM methods within the last 12 months before the survey. Proportions of usage and 95% confidence intervals were calculated for these methods and CM in general. Users and non-users of CM were compared using logistic regression models. Results The most popular methods in 2012 were homeopathy, naturopathy, osteopathy, herbal medicine, and acupuncture. The average number of treatments within the 12 months preceding the survey ranged from 3 for homeopathy to 6 for acupuncture. 25.0% of the population at the age of 15 and older had used at least one CM method in the previous 12 months. People with a chronic illness or a poor self-perceived health status were more likely to use CM. Similar to other countries, women, people of middle age, and those with higher education were more likely to use CM. 59.9% of the adult population had a supplemental health insurance that partly covered CM treatments. Conclusions Usage of CM in Switzerland remained unchanged between 2007 and 2012. The user profile in Switzerland was similar to other countries, such as Germany, United Kingdom, United States or Australia.