The default mode network is functionally and structurally disrupted in amnestic mild cognitive impairment ��� a bimodal MEG���DTI study

Over the past years, several studies on Mild Cognitive Impairment (MCI) and Alzheimer's disease (AD) have reported Default Mode Network (DMN) deficits. This network is attracting increasing interest in the AD community, as it seems to play an important role in cognitive functioning and in beta amyloid deposition. Attention has been particularly drawn to how different DMN regions are connected using functional or structural connectivity. To this end, most studies have used functional Magnetic Resonance Imaging (fMRI), Positron Emission Tomography (PET) or Diffusion Tensor Imaging (DTI). In this study we evaluated (1) functional connectivity from resting state magnetoencephalography (MEG) and (2) structural connectivity from DTI in 26 MCI patients and 31 age-matched controls. Compared to controls, the DMN in the MCI group was functionally disrupted in the alpha band, while no differences were found for delta, theta, beta and gamma frequency bands. In addition, structural disconnection could be assessed through a decreased fractional anisotropy along tracts connecting different DMN regions. This suggests that the DMN functional and anatomical disconnection could represent a core feature of MCI.

Guiding functional connectivity estimation by structural connectivity in MEG: an application to discrimination of mild cognitive impaired conditions

Whole brain resting state connectivity is a promising biomarker that might help to obtain an early diagnosis in many neurological diseases, such as dementia. Inferring resting-state connectivity is often based on correlations, which are sensitive to indirect connections, leading to an inaccurate representation of the real backbone of the network. The precision matrix is a better representation for whole brain connectivity, as it considers only direct connections. The network structure can be estimated using the graphical lasso (GL), which achieves sparsity through l1-regularization on the precision matrix. In this paper, we propose a structural connectivity adaptive version of the GL, where weaker anatomical connections are represented as stronger penalties on the corre- sponding functional connections. We applied beamformer source reconstruction to the resting state MEG record- ings of 81 subjects, where 29 were healthy controls, 22 were single-domain amnestic Mild Cognitive Impaired (MCI), and 30 were multiple-domain amnestic MCI. An atlas-based anatomical parcellation of 66 regions was ob- tained for each subject, and time series were assigned to each of the regions. The fiber densities between the re- gions, obtained with deterministic tractography from diffusion-weighted MRI, were used to define the anatomical connectivity. Precision matrices were obtained with the region specific time series in five different frequency bands. We compared our method with the traditional GL and a functional adaptive version of the GL, in terms of log-likelihood and classification accuracies between the three groups. We conclude that introduc- ing an anatomical prior improves the expressivity of the model and, in most cases, leads to a better classification between groups.

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

La investigaci��n para el conocimiento del cerebro es una ciencia joven, su inicio se remonta a Santiago Ram��n y Cajal en 1888. Desde esta fecha a nuestro tiempo la neurociencia ha avanzado mucho en el desarrollo de t��cnicas 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 as�� hablamos de una ciencia casi en pa��ales que tiene un lago recorrido por delante. Una de las claves del ��xito en los estudios de la funci��n cerebral ha sido convertirse en una disciplina que combina conocimientos de diversas ��reas: de la f��sica, de las matem��ticas, de la estad��stica y de la psicolog��a. Esta es la raz��n 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 integraci��n multimodal de la magnetoencefalograf��a (MEG) y la resonancia magn��tica ponderada en difusi��n (dMRI). Estas t��cnicas son sensibles, respectivamente, a los campos magn��ticos emitidos por las corrientes neuronales, y a la microestructura de la materia blanca cerebral. A lo largo de este trabajo hemos visto que la combinaci��n de estas t��cnicas permiten descubrir sinergias estructurofuncionales en el procesamiento de la informaci��n en el cerebro sano y en el curso de patolog��as neurol��gicas. M��s espec��ficamente en este trabajo se ha estudiado la relaci��n entre la conectividad funcional y estructural y en c��mo fusionarlas. Para ello, se ha cuantificado la conectividad funcional mediante el estudio de la sincronizaci��n de fase o la correlaci��n de amplitudes entre series temporales, de esta forma se ha conseguido un ��ndice que mide la similitud entre grupos neuronales o regiones cerebrales. Adicionalmente, la cuantificaci��n de la conectividad estructural a partir de im��genes de resonancia magn��tica ponderadas en difusi��n, ha permitido hallar ��ndices de la integridad de materia blanca o de la fuerza de las conexiones estructurales entre regiones. Estas medidas fueron combinadas en los cap��tulos 3, 4 y 5 de este trabajo siguiendo tres aproximaciones que iban desde el nivel m��s bajo al m��s alto de integraci��n. Finalmente se utiliz�� la informaci��n fusionada de MEG y dMRI para la caracterizaci��n de grupos de sujetos con deterioro cognitivo leve, la detecci��n de esta patolog��a resulta relevante en la identificaci��n precoz de la enfermedad de Alzheimer. Esta tesis est�� dividida en seis cap��tulos. En el cap��tulos 1 se establece un contexto para la introducci��n de la connect��mica dentro de los campos de la neuroimagen y la neurociencia. Posteriormente en este cap��tulo se describen los objetivos de la tesis, y los objetivos espec��ficos de cada una de las publicaciones cient��ficas que resultaron de este trabajo. En el cap��tulo 2 se describen los m��todos para cada t��cnica que fue empleada: conectividad estructural, conectividad funcional en resting state, redes cerebrales complejas y teor��a de grafos y finalmente se describe la condici��n de deterioro cognitivo leve y el estado actual en la b��squeda de nuevos biomarcadores diagn��sticos. En los cap��tulos 3, 4 y 5 se han incluido los art��culos cient��ficos 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 introducci��n, materiales y m��todos, resultados y discusi��n. Todos los m��todos que fueron empleados en los art��culos est��n descritos en el cap��tulo 2 de la tesis. Finalmente, en el cap��tulo 6 se concluyen los resultados generales de la tesis y se discuten de forma espec��fica los resultados de cada art��culo. 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.

Design and technical evaluation of an enhanced location-awareness service enabler for spatial disorientation management of elderly with mild cognitive impairment

The progressive ageing of population has turned the mild cognitive impairment (MCI) into a prevalent disease suffered by elderly. Consequently, the spatial disorientation has become a significant problem for older people and their caregivers. The ambient-assisted living applications are offering location-based services for empowering elderly to go outside and encouraging a greater independence. Therefore, this paper describes the design and technical evaluation of a location-awareness service enabler aimed at supporting and managing probable wandering situations of a person with MCI. Through the presence capabilities of the IP multimedia subsystem (IMS) architecture, the service will alert patient's contacts if a hazardous situation is detected depending on his location. Furthermore, information about the older person's security areas has been included in the user profile managed by IMS. In doing so, the service enabler introduced contribute to ���context-awareness��� paradigm allowing the adaptation and personalization of services depending on user's context and specific conditions or preferences.

Anomalous Consistency in Mild Cognitive Impairment: A Complex Networks Approach

Increased variability in performance has been associated with the emergence of several neurological and psychiatric pathologies. However, whether and how consistency of neuronal activity may also be indicative of an underlying pathology is still poorly understood. Here we propose a novel method for evaluating consistency from non-invasive brain recordings. We evaluate the consistency of the cortical activity recorded with magnetoencephalography in a group of subjects diagnosed with Mild Cognitive Impairment (MCI), a condition sometimes prodromal of dementia, during the execution of a memory task. We use metrics coming from nonlinear dynamics to evaluate the consistency of cortical regions. A representation known as parenclitic networks is constructed, where atypical features are endowed with a network structure, the topological properties of which can be studied at various scales. Pathological conditions correspond to strongly heterogeneous networks, whereas typical or normative conditions are characterized by sparsely connected networks with homogeneous nodes. The analysis of this kind of networks allows identifying the extent to which consistency is affected in the MCI group and the focal points where MCI is especially severe. To the best of our knowledge, these results represent the first attempt at evaluating the consistency of brain functional activity using complex networks theory.

Impacts of coexisting bronchial asthma on severe exacerbations in mild-to-moderate COPD : results from a national database

Acknowledgments The authors would like to thank Kyungjoo Kim for the confident statistical analyses in this work. This study was supported by a grant (2014P3300300) from the Korea Centers for Disease Control and Prevention. The abstract of this paper was presented at the Asian Pacific Society of Respirology 20th Congress as an oral presentation with interim findings. The poster���s abstract was published in ���Poster Abstracts��� in Respirology

Obesity and mild hyperinsulinemia found in neuropeptide Y-Y1 receptor-deficient mice

To elucidate the role of neuropeptide Y (NPY)-Y1 receptor (Y1-R) in food intake, energy expenditure, and other possible functions, we have generated Y1-R-deficient mice (Y1-R���/���) by gene targeting. Contrary to our hypothesis that the lack of NPY signaling via Y1-R would result in impaired feeding and weight loss, Y1-R���/��� mice showed a moderate obesity and mild hyperinsulinemia without hyperphagia. Although there was some variation between males and females, typical characteristics of Y1-R���/��� mice include: greater body weight (females more than males), an increase in the weight of white adipose tissue (WAT) (approximately 4-fold in females), an elevated basal level of plasma insulin (approximately 2-fold), impaired insulin secretion in response to glucose administration, and a significant changes in mitochondrial uncoupling protein (UCP) gene expression (up-regulation of UCP1 in brown adipose tissue and down-regulation of UCP2 in WAT). These results suggest either that the Y1-R in the hypothalamus is not a key molecule in the leptin/NPY pathway, which controls feeding behavior, or that its deficiency is compensated by other receptors, such as NPY-Y5 receptor. We believe that the mild obesity found in Y1-R���/��� mice (especially females) was caused by the impaired control of insulin secretion and/or low energy expenditure, including the lowered expression of UCP2 in WAT. This model will be useful for studying the mechanism of mild obesity and abnormal insulin metabolism in noninsulin-dependent diabetes mellitus.

Investigation by Parkinson���s Disease Research Group of United Kingdom into excess mortality seen with combined levodopa and selegiline treatment in patients with early, mild Parkinson���s disease: further results of randomised trial and confidential inquiry

Objective: To determine whether the excess mortality observed in patients who received both levodopa and selegiline in a randomised trial could be explained by revised diagnosis of Parkinson���s disease, autonomic or cardiovascular effects, more rapid disease progression, or drug interactions.

Apoptosis and necrosis: two distinct events induced, respectively, by mild and intense insults with N-methyl-D-aspartate or nitric oxide/superoxide in cortical cell cultures.

N-Methyl-D-aspartate (NMDA) receptor-mediated neurotoxicity may depend, in part, on the generation of nitric oxide (NO.) and superoxide anion (O2.-), which react to form peroxynitrite (OONO-). This form of neurotoxicity is thought to contribute to a final common pathway of injury in a wide variety of acute and chronic neurologic disorders, including focal ischemia, trauma, epilepsy, Huntington disease, Alzheimer disease, amyotrophic lateral scelerosis, AIDS dementia, and other neurodegenerative diseases. Here, we report that exposure of cortical neurons to relatively short durations or low concentrations of NMDA, S-nitrosocysteine, or 3-morpholinosydnonimine, which generate low levels of peroxynitrite, induces a delayed form of neurotoxicity predominated by apoptotic features. Pretreatment with superoxide dismutase and catalase to scavenge O2.- partially prevents the apoptotic process triggered by S-nitrosocysteine or 3-morpholinosydnonimine. In contrast, intense exposure to high concentrations of NMDA or peroxynitrite induces necrotic cell damage characterized by acute swelling and lysis, which cannot be ameliorated by superoxide dismutase and catalase. Thus, depending on the intensity of the initial insult, NMDA or nitric oxide/superoxide can result in either apoptotic or necrotic neuronal cell damage.

The Use of the Rey 15-Item Test and Recognition Trial to Evaluate Suboptimal Effort in Neuropsychological Assessment with a Pediatric Mild TBI Sample

The utilization of symptom validity tests (SVTs) in pediatric assessment is receiving increasing empirical support. The Rey 15-Item Test (FIT) is an SVT commonly used in adult assessment, with limited research in pediatric populations. Given that FIT classification statistics across studies to date have been quite variable, Boone, Salazar, Lu, Warner-Chacon, and Razani (2002) developed a recognition trial to use with the original measure to enhance accuracy. The current study aims to assess the utility of the FIT and recognition trial in a pediatric mild traumatic brain injury (TBI) sample (N = 112; M = 14.6 years), in which a suboptimal effort base rate of 17% has been previously established (Kirkwood & Kirk, 2010). All participants were administered the FIT as part of an abbreviated neuropsychological evaluation; failure on the Medical Symptom Validity Test (MSVT) was used as the criterion for suspect effort. The traditional adult cut-off score of(99%), but poor sensitivity (6%). When the recognition trial was also utilized, a combination score of(sensitivity = 64%, specificity = 93%). Results indicate that the FIT with recognition trial may be useful in the assessment of pediatric suboptimal effort, at least among relatively high functioning children following mild TBI.

The Utility of the CVLT-C as an Embedded Validity Indicator After Pediatric Mild Traumatic Brain Injury.

Results of neuropsychological examinations depend on valid data. Whereas clinicians previously believed that clinical skill was sufficient to identify non-credible performance by examinees on standard tests, research demonstrates otherwise. Consequently, studies on measures to detect suspect effort in adults have received tremendous attention in the previous twenty years, and incorporation of validity indicators into neuropsychological examinations is now seen as integral. Few studies exist that validate methods appropriate for the measurement of effort in pediatric populations. Of extant studies, most evaluate standalone measures originally developed for use with adults. The present study examined the utility of indices from the California Verbal Learning Test �������� Children's Version (CVLT-C) as embedded validity indicators in a pediatric sample. Participants were 225 outpatients aged 8 to 16 years old referred for clinical assessment after mild traumatic brain injury (mTBI). Non-credible performance (n = 39) was defined as failure of the Medical Symptom Validity Test (MSVT). Logistic regression demonstrated that only the Recognition Discriminability index was predictive of MSVT failure (OR = 2.88, p < .001). A cutoff of z ������� -1.0 was associated with sensitivity of 51% and specificity of 91%. In the current study, CVLT-C Recognition Discriminability was useful in the identification of non-credible performance in a sample of relatively high-functioning pediatric outpatients with mTBI. Thus, this index can be added to the short list of embedded validity indicators appropriate for pediatric neuropsychological assessment.

Preparation, characterisation and testing of CuO/Ce0.8Zr0.2O2 catalysts for NO oxidation to NO2 and mild temperature diesel soot combustion

CuO/ceria-zirconia catalysts have been prepared, deeply characterised (N2 adsorption���desorption isotherms at ���196 ��C, XRD, Raman spectroscopy, XPS, TEM and H2-TPR) and tested for NO oxidation to NO2 in TPR conditions, and for soot combustion at mild temperature (400 ��C) in a NOx/O2 stream. The behaviour has been compared to that of a reference Pt/alumina commercial catalyst. The ceria-zirconia support was prepared by the co-precipitation method, and different amounts of copper (0.5, 1, 2, 4 and 6 wt%) were loaded by incipient wetness impregnation. The results revealed that copper is well-dispersed onto the ceria-zirconia support for the catalysts with low copper loading and CuO particles were only identified by XRD in samples with 4 and 6% of copper. A very low loading of copper increases significantly the activity for the NO oxidation to NO2 with regard to the ceria-zirconia support and an optimum was found for a 4% CuO/ceria-zirconia composition, showing a very high activity (54% at 348 ��C). The soot combustion rate at 400 ��C obtained with the 2% CuO/ceria-zirconia catalyst is slightly lower to that of 1% Pt/alumina in terms of mass of catalyst but higher in terms of price of catalyst.

Synthesis of high surface area TiO2 nanoparticles by mild acid treatment with HCl or HI for photocatalytic propene oxidation

Nanostructured TiO2 photocatalysts with small crystalline sizes have been synthesized by sol-gel using the amphiphilic triblock copolymer Pluronic P123 as template. A new synthesis route, based on the treatment of TiO2 xerogels with acid-ethanol mixtures in two different steps, synthesis and extraction-crystallization, has been investigated, analyzing two acids, hydrochloric and hydriodic acid. As reference, samples have also been prepared by extraction-crystallization in ethanol, being these TiO2 materials amorphous and presenting higher porosities. The prepared materials present different degrees of crystallinity depending on the experimental conditions used. In general, these materials exhibit high surface areas, with an important contribution of microporosity and mesoporosity, and with very small size anatase crystals, ranging from 5 to 7 nm. The activity of the obtained photocatalysts has been assessed in the oxidation of propene in gas phase at low concentration (100 ppmv) under a UVA lamp with 365 nm wavelength. In the conditions studied, these photocatalysts show different activities in the oxidation of propene which do not depend on their surface areas, but on their crystallinity and band gap energies, being sample prepared with HCl both during synthesis and in extraction-crystallizations steps, the most active one, with superior performance than Evonik P25.