Aerodynamic Optimization of High-Speed Trains Nose using a Genetic Algorithm and Artificial Neural Network

An aerodynamic optimization of the train aerodynamic characteristics in term of front wind action sensitivity is carried out in this paper. In particular, a genetic algorithm (GA) is used to perform a shape optimization study of a high-speed train nose. The nose is parametrically defined via Bézier Curves, including a wider range of geometries in the design space as possible optimal solutions. Using a GA, the main disadvantage to deal with is the large number of evaluations need before finding such optimal. Here it is proposed the use of metamodels to replace Navier-Stokes solver. Among all the posibilities, Rsponse Surface Models and Artificial Neural Networks (ANN) are considered. Best results of prediction and generalization are obtained with ANN and those are applied in GA code. The paper shows the feasibility of using GA in combination with ANN for this problem, and solutions achieved are included.

Tomas Lopez's Geographic Atlas of Spain (1787) and its Hydrographic Network: GIS analysis of the Reyno de Jaen

Knowledge of the development of hydrographic networks can be useful for a number of research works in hydraulic engineering. We thus, intend to analyse the cartography regarding the first work that systematically encompasses the entire hydrographic network: Tomas Lopez’s Geographic Atlas of Spain (1787). In order to achieve this goal, we will first analyze –by way of the Geographic Information System (GIS) – both the present and referred historical cartographies. In comparing them, we will use the then-existing population centres that correspond to modern ones. The aim is to compare the following research variables in the hydrographic network: former toponyms, length of riverbeds and distance to population centres. The results of this study will show the variation in the riverbeds and the probable change in their denomination.

HERMES: Towards an Integrated Toolbox to Characterize Functional and Effective Brain Connectivity

The analysis of the interdependence between time series has become an important field of research in the last years, mainly as a result of advances in the characterization of dynamical systems from the signals they produce, the introduction of concepts such as generalized and phase synchronization and the application of information theory to time series analysis. In neurophysiology, different analytical tools stemming from these concepts have added to the ‘traditional’ set of linear methods, which includes the cross-correlation and the coherency function in the time and frequency domain, respectively, or more elaborated tools such as Granger Causality. This increase in the number of approaches to tackle the existence of functional (FC) or effective connectivity (EC) between two (or among many) neural networks, along with the mathematical complexity of the corresponding time series analysis tools, makes it desirable to arrange them into a unified-easy-to-use software package. The goal is to allow neuroscientists, neurophysiologists and researchers from related fields to easily access and make use of these analysis methods from a single integrated toolbox. Here we present HERMES (http://hermes.ctb.upm.es), a toolbox for the Matlab® environment (The Mathworks, Inc), which is designed to study functional and effective brain connectivity from neurophysiological data such as multivariate EEG and/or MEG records. It includes also visualization tools and statistical methods to address the problem of multiple comparisons. We believe that this toolbox will be very helpful to all the researchers working in the emerging field of brain connectivity analysis.

HERMES: towards an integrated toolbox to characterize functional and effective brain connectivity

The analysis of the interdependence between time series has become an important field of research in the last years, mainly as a result of advances in the characterization of dynamical systems from the signals they produce, the introduction of concepts such as generalized and phase synchronization and the application of information theory to time series analysis. In neurophysiology, different analytical tools stemming from these concepts have added to the ?traditional? set of linear methods, which includes the cross-correlation and the coherency function in the time and frequency domain, respectively, or more elaborated tools such as Granger Causality. This increase in the number of approaches to tackle the existence of functional (FC) or effective connectivity (EC) between two (or among many) neural networks, along with the mathematical complexity of the corresponding time series analysis tools, makes it desirable to arrange them into a unified, easy-to-use software package. The goal is to allow neuroscientists, neurophysiologists and researchers from related fields to easily access and make use of these analysis methods from a single integrated toolbox. Here we present HERMES (http://hermes.ctb.upm.es), a toolbox for the Matlab® environment (The Mathworks, Inc), which is designed to study functional and effective brain connectivity from neurophysiological data such as multivariate EEG and/or MEG records. It includes also visualization tools and statistical methods to address the problem of multiple comparisons. We believe that this toolbox will be very helpful to all the researchers working in the emerging field of brain connectivity analysis.

Multimodal integration of functional and structural brain connectivity. An application to the characterization of Mild Cognitive Impairment

La investigación para el conocimiento del cerebro es una ciencia joven, su inicio se remonta a Santiago Ramón y Cajal en 1888. Desde esta fecha a nuestro tiempo la neurociencia ha avanzado mucho en el desarrollo de técnicas que permiten su estudio. Desde la neurociencia cognitiva hoy se explican muchos modelos que nos permiten acercar a nuestro entendimiento a capacidades cognitivas complejas. Aun así hablamos de una ciencia casi en pañales que tiene un lago recorrido por delante. Una de las claves del éxito en los estudios de la función cerebral ha sido convertirse en una disciplina que combina conocimientos de diversas áreas: de la física, de las matemáticas, de la estadística y de la psicología. Esta es la razón por la que a lo largo de este trabajo se entremezclan conceptos de diferentes campos con el objetivo de avanzar en el conocimiento de un tema tan complejo como el que nos ocupa: el entendimiento de la mente humana. Concretamente, esta tesis ha estado dirigida a la integración multimodal de la magnetoencefalografía (MEG) y la resonancia magnética ponderada en difusión (dMRI). Estas técnicas son sensibles, respectivamente, a los campos magnéticos emitidos por las corrientes neuronales, y a la microestructura de la materia blanca cerebral. A lo largo de este trabajo hemos visto que la combinación de estas técnicas permiten descubrir sinergias estructurofuncionales en el procesamiento de la información en el cerebro sano y en el curso de patologías neurológicas. Más específicamente en este trabajo se ha estudiado la relación entre la conectividad funcional y estructural y en cómo fusionarlas. Para ello, se ha cuantificado la conectividad funcional mediante el estudio de la sincronización de fase o la correlación de amplitudes entre series temporales, de esta forma se ha conseguido un índice que mide la similitud entre grupos neuronales o regiones cerebrales. Adicionalmente, la cuantificación de la conectividad estructural a partir de imágenes de resonancia magnética ponderadas en difusión, ha permitido hallar índices de la integridad de materia blanca o de la fuerza de las conexiones estructurales entre regiones. Estas medidas fueron combinadas en los capítulos 3, 4 y 5 de este trabajo siguiendo tres aproximaciones que iban desde el nivel más bajo al más alto de integración. Finalmente se utilizó la información fusionada de MEG y dMRI para la caracterización de grupos de sujetos con deterioro cognitivo leve, la detección de esta patología resulta relevante en la identificación precoz de la enfermedad de Alzheimer. Esta tesis está dividida en seis capítulos. En el capítulos 1 se establece un contexto para la introducción de la connectómica dentro de los campos de la neuroimagen y la neurociencia. Posteriormente en este capítulo se describen los objetivos de la tesis, y los objetivos específicos de cada una de las publicaciones científicas que resultaron de este trabajo. En el capítulo 2 se describen los métodos para cada técnica que fue empleada: conectividad estructural, conectividad funcional en resting state, redes cerebrales complejas y teoría de grafos y finalmente se describe la condición de deterioro cognitivo leve y el estado actual en la búsqueda de nuevos biomarcadores diagnósticos. En los capítulos 3, 4 y 5 se han incluido los artículos científicos que fueron producidos a lo largo de esta tesis. Estos han sido incluidos en el formato de la revista en que fueron publicados, estando divididos en introducción, materiales y métodos, resultados y discusión. Todos los métodos que fueron empleados en los artículos están descritos en el capítulo 2 de la tesis. Finalmente, en el capítulo 6 se concluyen los resultados generales de la tesis y se discuten de forma específica los resultados de cada artículo. ABSTRACT In this thesis I apply concepts from mathematics, physics and statistics to the neurosciences. This field benefits from the collaborative work of multidisciplinary teams where physicians, psychologists, engineers and other specialists fight for a common well: the understanding of the brain. Research on this field is still in its early years, being its birth attributed to the neuronal theory of Santiago Ramo´n y Cajal in 1888. In more than one hundred years only a very little percentage of the brain functioning has been discovered, and still much more needs to be explored. Isolated techniques aim at unraveling the system that supports our cognition, nevertheless in order to provide solid evidence in such a field multimodal techniques have arisen, with them we will be able to improve current knowledge about human cognition. Here we focus on the multimodal integration of magnetoencephalography (MEG) and diffusion weighted magnetic resonance imaging. These techniques are sensitive to the magnetic fields emitted by the neuronal currents and to the white matter microstructure, respectively. The combination of such techniques could bring up evidences about structural-functional synergies in the brain information processing and which part of this synergy fails in specific neurological pathologies. In particular, we are interested in the relationship between functional and structural connectivity, and how two integrate this information. We quantify the functional connectivity by studying the phase synchronization or the amplitude correlation between time series obtained by MEG, and so we get an index indicating similarity between neuronal entities, i.e. brain regions. In addition we quantify structural connectivity by performing diffusion tensor estimation from the diffusion weighted images, thus obtaining an indicator of the integrity of the white matter or, if preferred, the strength of the structural connections between regions. These quantifications are then combined following three different approaches, from the lowest to the highest level of integration, in chapters 3, 4 and 5. We finally apply the fused information to the characterization or prediction of mild cognitive impairment, a clinical entity which is considered as an early step in the continuum pathological process of dementia. The dissertation is divided in six chapters. In chapter 1 I introduce connectomics within the fields of neuroimaging and neuroscience. Later in this chapter we describe the objectives of this thesis, and the specific objectives of each of the scientific publications that were produced as result of this work. In chapter 2 I describe the methods for each of the techniques that were employed, namely structural connectivity, resting state functional connectivity, complex brain networks and graph theory, and finally, I describe the clinical condition of mild cognitive impairment and the current state of the art in the search for early biomarkers. In chapters 3, 4 and 5 I have included the scientific publications that were generated along this work. They have been included in in their original format and they contain introduction, materials and methods, results and discussion. All methods that were employed in these papers have been described in chapter 2. Finally, in chapter 6 I summarize all the results from this thesis, both locally for each of the scientific publications and globally for the whole work.

Functional integrity of mitochondrial genomes in human platelets and autopsied brain tissues from elderly patients with Alzheimer’s disease

To determine whether pathogenic mutations in mtDNA are involved in phenotypic expression of Alzheimer’s disease (AD), the transfer of mtDNA from elderly patients with AD into mtDNA-less (ρ0) HeLa cells was carried out by fusion of platelets or synaptosomal fractions of autopsied brain tissues with ρ0 HeLa cells. The results showed that mtDNA in postmortem brain tissue survives for a long time without degradation and could be rescued in ρ0 HeLa cells. Next, the cybrid clones repopulated with exogenously imported mtDNA from patients with AD were used for examination of respiratory enzyme activity and transfer of mtDNA with the pathogenic mutations that induce mitochondrial dysfunction. The presence of the mutated mtDNA was restricted to brain tissues and their cybrid clones that formed with synaptosomes as mtDNA donors, whereas no cybrid clones that isolated with platelets as mtDNA donors had detectable mutated mtDNA. However, biochemical analyses showed that all cybrid clones with mtDNA imported from platelets or brain tissues of patients with AD restored mitochondrial respiration activity to almost the same levels as those of cybrid clones with mtDNA from age-matched normal controls, suggesting functional integrity of mtDNA in both platelets and brain tissues of elderly patients with AD. These observations warrant the reassessment of the conventional concept that the accumulation of pathogenic mutations in mtDNA throughout the aging process is responsible for the decrease of mitochondrial respiration capacity with age and with the development of age-associated neurodegenerative diseases.

Expression of membrane-associated carbonic anhydrase XIV on neurons and axons in mouse and human brain

Although long suspected from histochemical evidence for carbonic anhydrase (CA) activity on neurons and observations that CA inhibitors enhance the extracellular alkaline shifts associated with synaptic transmission, an extracellular CA in brain had not been identified. A candidate for this CA was suggested by the recent discovery of membrane CA (CA XIV) whose mRNA is expressed in mouse and human brain and in several other tissues. For immunolocalization of CA XIV in mouse and human brain, we developed two antibodies, one against a secretory form of enzymatically active recombinant mouse CA XIV, and one against a synthetic peptide corresponding to the 24 C-terminal amino acids in the human enzyme. Immunostaining for CA XIV was found on neuronal membranes and axons in both mouse and human brain. The highest expression was seen on large neuronal bodies and axons in the anterolateral part of pons and medulla oblongata. Other CA XIV-positive sites included the hippocampus, corpus callosum, cerebellar white matter and peduncles, pyramidal tract, and choroid plexus. Mouse brain also showed a positive reaction in the molecular layer of the cerebral cortex and granular cellular layer of the cerebellum. These observations make CA XIV a likely candidate for the extracellular CA postulated to have an important role in modulating excitatory synaptic transmission in brain.

Peripheral anti-Aβ antibody alters CNS and plasma Aβ clearance and decreases brain Aβ burden in a mouse model of Alzheimer's disease

Active immunization with the amyloid β (Aβ) peptide has been shown to decrease brain Aβ deposition in transgenic mouse models of Alzheimer's disease and certain peripherally administered anti-Aβ antibodies were shown to mimic this effect. In exploring factors that alter Aβ metabolism and clearance, we found that a monoclonal antibody (m266) directed against the central domain of Aβ was able to bind and completely sequester plasma Aβ. Peripheral administration of m266 to PDAPP transgenic mice, in which Aβ is generated specifically within the central nervous system (CNS), results in a rapid 1,000-fold increase in plasma Aβ, due, in part, to a change in Aβ equilibrium between the CNS and plasma. Although peripheral administration of m266 to PDAPP mice markedly reduces Aβ deposition, m266 did not bind to Aβ deposits in the brain. Thus, m266 appears to reduce brain Aβ burden by altering CNS and plasma Aβ clearance.

General and specific brain regions involved in encoding and retrieval of events: what, where, and when.

Remembering an event involves not only what happened, but also where and when it occurred. We measured regional cerebral blood flow by positron emission tomography during initial encoding and subsequent retrieval of item, location, and time information. Multivariate image analysis showed that left frontal brain regions were always activated during encoding, and right superior frontal regions were always activated at retrieval. Pairwise image subtraction analyses revealed information-specific activations at (i) encoding, item information in left hippocampal, location information in right parietal, and time information in left fusiform regions; and (ii) retrieval, item in right inferior frontal and temporal, location in left frontal, and time in anterior cingulate cortices. These results point to the existence of general encoding and retrieval networks of episodic memory whose operations are augmented by unique brain areas recruited for processing specific aspects of remembered events.

Substitution rate comparisons between grasses and palms: synonymous rate differences at the nuclear gene Adh parallel rate differences at the plastid gene rbcL.

A number of studies have noted that nucleotide substitution rates at the chloroplast-encoded rbcL locus violate the molecular clock principle. Substitution rate variation at this plastid gene is particularly pronounced between palms and grasses; for example, a previous study estimated that substitution rates in rbcL sequences are approximately 5-fold faster in grasses than in palms. To determine whether a proportionate change in substitution rates also occurs in plant nuclear genes, we characterized nucleotide substitution rates in palm and grass sequences for the nuclear gene Adh. In this article, we report that palm sequences evolve at a rate of 2.61 x 10(-9) substitution per synonymous site per year, a rate which is slower than most plant nuclear genes. Grass Adh sequences evolve approximately 2.5-fold faster than palms at synonymous sites. Thus, synonymous rates in nuclear Adh genes show a marked decrease in palms relative to grasses, paralleling the pattern found at the plastid rbcL locus. This shared pattern indicates that synonymous rates are correlated between a nuclear and a plastid gene. Remarkably, nonsynonymous rates do not show this correlation. Nonsynonymous rates vary between two duplicated grass Adh loci, and nonsynonymous rates at the palm Adh locus are not markedly reduced relative to grasses.

Onconeural antigens and the paraneoplastic neurologic disorders: at the intersection of cancer, immunity, and the brain.

Paraneoplastic neurologic disorders (PNDs) are believed to be autoimmune neuronal degenerations that develop in some patients with systemic cancer. A series of genes encoding previously undiscovered neuronal proteins have been cloned using antiserum from PND patients. Identification of these onconeural antigens suggests a reclassification of the disorders into four groups: those in which neuromuscular junction proteins, nerve terminal/vesicle-associated proteins, neuronal RNA binding proteins, or neuronal signal-transduction proteins serve as target antigens. This review considers insights into basic neurobiology, tumor immunology, and autoimmune neuronal degeneration offered by the characterization of the onconeural antigens.

Localization of the central rhythm generator involved in spontaneous consummatory licking in rats: functional ablation and electrical brain stimulation studies.

Localization of the central rhythm generator (CRG) of spontaneous consummatory licking was studied in freely moving rats by microinjection of tetrodotoxin (TTX) into the pontine reticular formation. Maximum suppression of spontaneous water consumption was elicited by TTX (1 ng) blockade of the oral part of the nucleus reticularis gigantocellularis (NRG), whereas TTX injections into more caudal or rostral locations caused significantly weaker disruption of drinking. To verify the assumption that TTX blocked the proper CRG of licking rather than some relay in its output, spontaneously drinking thirsty rats were intracranially stimulated via electrodes chronically implanted into the oral part of the NRG. Lick-synchronized stimulation (a 100-ms train of 0.1-ms-wide rectangular pulses at 100 Hz and 25-150 microA) applied during continuous licking (after eight regular consecutive licks) caused a phase shift of licks emitted after stimulus delivery. The results suggest that the stimulation has reset the CRG of licking without changing its frequency. The reset-inducing threshold current was lowest during the tongue retraction and highest during the tongue protrusion period of the lick cycle. It is concluded that the CRG of licking is located in the oral part of NRG.

Neural tube defects and abnormal brain development in F52-deficient mice.

F52 is a myristoylated, alanine-rich substrate for protein kinase C. We have generated F52-deficient mice by the gene targeting technique. These mutant mice manifest severe neural tube defects that are not associated with other complex malformations, a phenotype reminiscent of common human neural tube defects. The neural tube defects observed include both exencephaly and spina bifida, and the phenotype exhibits partial penetrance with about 60% of homozygous embryos developing neural tube defects. Exencephaly is the prominent type of defect and leads to high prenatal lethality. Neural tube defects are observed in a smaller percentage of heterozygous embryos (about 10%). Abnormal brain development and tail formation occur in homozygous mutants and are likely to be secondary to the neural tube defects. Disruption of F52 in mice therefore identifies a gene whose mutation results in isolated neural tube defects and may provide an animal model for common human neural tube defects.