Dysfunctional and compensatory duality in mild cognitive impairment during a continuous recognition memory task

One of the current issues of debate in the study of mild cognitive impairment (MCI) is deviations of oscillatory brain responses from normal brain states and its dynamics. This work aims to characterize the differences of power in brain oscillations during the execution of a recognition memory task in MCI subjects in comparison with elderly controls. Magnetoencephalographic (MEG) signals were recorded during a continuous recognition memory task performance. Oscillatory brain activity during the recognition phase of the task was analyzed by wavelet transform in the source space by means of minimum norm algorithm. Both groups obtained a 77% hit ratio. In comparison with healthy controls, MCI subjects showed increased theta (p < 0.001), lower beta reduction (p < 0.001) and decreased alpha and gamma power (p < 0.002 and p < 0.001 respectively) in frontal, temporal and parietal areas during early and late latencies. Our results point towards a dual pattern of activity (increase and decrease) which is indicative of MCI and specific to certain time windows, frequency bands and brain regions. These results could represent two neurophysiological sides of MCI. Characterizing these opposing processes may contribute to the understanding of the disorder

Complexity of functional connectivity networks in mild cognitive impairment subjects during a working memory task

Objectives: The objective is to study the changes of brain activity in patients with mild cognitive impairment (MCI). Using magneto-encephalogram (MEG) signals, the authors investigate differences of complexity of functional connectivity network between MCI and normal elderly subjects during a working memory task. Methods: MEGs are obtained from 18 right handed patients with MCI and 19 age-matched elderly participants without cognitive impairment used as the control group. The brain networks’ complexities are measured by Graph Index Complexity (Cr) and Efficiency Complexity (Ce). Results: The results obtained by both measurements show complexity of functional networks involved in the working memory function in MCI subjects is reduced at alpha and theta bands compared with subjects with control subjects, and at the theta band this reduction is more pronounced in the whole brain and intra left hemisphere. Conclusions: Ce would be a better measurement for showing the global differences between normal and MCI brains compared with Cr. Significance: The high accuracy of the classification shows Ce at theta band can be used as an index for assessing deficits associated with working memory, a good biomarker for diagnosis of MC

An efficient implementation of the synchronization likelihood algorithm for functional connectivity

Measures of functional connectivity are commonly employed in neuroimaging research. Among the most popular measures is the Synchronization Likelihood which provides a non-linear estimate of the statistical dependencies between the activity time courses of different brain areas. One aspect which has limited a wider use of this algorithm is the fact that it is very computationally and memory demanding. In the present work we propose new implementations and parallelizations of the Synchronization Likelihood algorithm with significantly better performance both in time and in memory use. As a result both the amount of required computational time is reduced by 3 orders of magnitude and the amount of memory needed for calculations is reduced by 2 orders of magnitude. This allows performing analyses that were not feasible before from a computational standpoint

An efficient implementation of the synchronization likelihood algorithm for functional connectivity

Measures of functional connectivity are commonly employed in neuroimaging research. Among the most popular measures is the Synchronization Likelihood which provides a non-linear estimate of the statistical dependencies between the activity time courses of different brain areas. One aspect which has limited a wider use of this algorithm is the fact that it is very computationally and memory demanding. In the present work we propose new implementations and parallelizations of the Synchronization Likelihood algorithm with significantly better performance both in time and in memory use. As a result both the amount of required computational time is reduced by 3 orders of magnitude and the amount of memory needed for calculations is reduced by 2 orders of magnitude. This allows performing analyses that were not feasible before from a computational standpoint

Influence of the synthesis process on the features of Y2O3-stabilized ZrO2 powders obtained by the sol–gel method

Y2O3-stabilized ZrO2 (YSZ) powders have been prepared by the sol–gel method using different synthesis parameters. Specifically, zirconium n-propoxide was dissolved in propanol at pH 0.5 or 5 (provided by HNO3), with or without acetic acid in the hydrolysis medium. Subsequently, the YSZ powders obtained by gelation and drying of these solutions was characterized using scanning and transmission electron microscopies, X-ray diffractometry, and N2-adsorption. Compacts made from these YSZ powders which were then sintered were also analyzed. It was found that the pH of the hydrolysis medium has a notable influence on the microstructure, morphology, color, crystallinity, and sintering behavior process of these YSZ sol–gel powders. It was also found that the use of acetic acid also affects the YSZ powder features, and results in compacts with higher residual porosity after sintering. Finally, the compacts prepared from the YSZ powders obtained at pH 5 and without acetic acid exhibit the greatest sinterabilityFil: Mamana, Nadia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Física de Rosario. Universidad Nacional de Rosario. Instituto de Física de Rosario; ArgentinaFil: Díaz Parralejo, Antonio. Universidad de Extremadura. Badajoz; EspañaFil: Ortiz, Angel L. Universidad de Extremadura. Badajoz; EspañaFil: Sánchez Bajo, Florentino. Universidad de Extremadura. Badajoz; EspañaFil: Caruso, Ricardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Física de Rosario. Universidad Nacional de Rosario. Instituto de Física de Rosario; Argentin

Editorial

In fact, much of the attraction of network theory initially stemmed from the fact that many networks seem to exhibit some sort of universality, as most of them belong to one of three classes: random, scale-free and small-world networks. Structural properties have been shown to translate into different important properties of a given system, including efficiency, speed of information processing, vulnerability to various forms of stress, and robustness. For example, scale-free and random topologies were shown to be..

Hyperconnectivity is a fundamental response to neurological disruption

In the cognitive and clinical neurosciences, the past decade has been marked by dramatic growth in a literature examining brain "connectivity" using noninvasive methods. We offer a critical review of the blood oxygen level dependent functional MRI (BOLD fMRI) literature examining neural connectivity changes in neurological disorders with focus on brain injury and dementia. The goal is to demonstrate that there are identifiable shifts in local and large-scale network connectivity that can be predicted by the degree of pathology. We anticipate that the most common network response to neurological insult is hyperconnectivity but that this response depends upon demand and resource availability

Mitigation of the ground reflection effect in real-time locating systems based on wireless sensor networks by using artificial neural networks

Wireless sensor networks (WSNs) have become much more relevant in recent years, mainly because they can be used in a wide diversity of applications. Real-time locating systems (RTLSs) are one of the most promising applications based on WSNs and represent a currently growing market. Specifically, WSNs are an ideal alternative to develop RTLSs aimed at indoor environments where existing global navigation satellite systems, such as the global positioning system, do not work correctly due to the blockage of the satellite signals. However, accuracy in indoor RTLSs is still a problem requiring novel solutions. One of the main challenges is to deal with the problems that arise from the effects of the propagation of radiofrequency waves, such as attenuation, diffraction, reflection and scattering. These effects can lead to other undesired problems, such as multipath. When the ground is responsible for wave reflections, multipath can be modeled as the ground reflection effect. This paper presents an innovative mathematical model for improving the accuracy of RTLSs, focusing on the mitigation of the ground reflection effect by using multilayer perceptron artificial neural networks.Wireless sensor networks (WSNs) have become much more relevant in recent years, mainly because they can be used in a wide diversity of applications. Real-time locating systems (RTLSs) are one of the most promising applications based on WSNs and represent a currently growing market. Specifically, WSNs are an ideal alternative to develop RTLSs aimed at indoor environments where existing global navigation satellite systems, such as the global positioning system, do not work correctly due to the blockage of the satellite signals. However, accuracy in indoor RTLSs is still a problem requiring novel solutions. One of the main challenges is to deal with the problems that arise from the effects of the propagation of radiofrequency waves, such as attenuation, diffraction, reflection and scattering. These effects can lead to other undesired problems, such as multipath. When the ground is responsible for wave reflections, multipath can be modeled as the ground reflection effect. This paper presents an innovative mathematical model for improving the accuracy of RTLSs, focusing on the mitigation of the ground reflection effect by using multilayer perceptron artificial neural networks

Concordancia histopatológica entre la citología y la biopsia anal en hombres que tienen sexo con hombres portadores de VIH y neoplasia intraepitelial anal asociada a VPH

Objetivo: determinar la concordancia de los resultados de la citología y la biopsia anal en hombres que tienen sexo con hombres (HSH) portadores de VIH y neoplasia intraepitelial anal (NIA) asociada a virus del papiloma humano (VPH). Materiales y métodos: estudio observacional transversal, de diciembre de 2011 a diciembre de 2013 para determinar la concordancia de los resultados de la citología y la biopsia anal en hombres que tienen sexo con hombres (HSH) portadores de VIH y NIA asociada a VPH en pacientes del hospital de Infectología del Centro Médico Nacional la Raza. Se realizó análisis estadísticos descriptivos. Resultados: se estudiaron 92 sujetos VIH positivos y VPH positivo, el reporte histopatológico definitivo de las biopsias anales fueron: neoplasia intraepitelial de bajo grado en 39 %, neoplasia intraepitelial de alto grado 4 %, células atípicas de significado incierto 3 %, normales en 27 %, con cambios inflamatorios reactivos en 23 % y muestras inadecuadas para el diagnóstico el 9 %. La concordancia observada entre los dos métodos diagnósticos fue de 0.90 según alfa de Crobanch. Conclusión: el grado de concordancia del 90 % de las biopsias y citologías anales, indica que son buenos métodos de seguimiento de los pacientes infectados con VIH y VPH, y permite detectar en forma oportuna lesiones precancerígenas, brindando diagnóstico y tratamiento oportuno