Detecting cell assemblies in large neuronal populations

Recent progress in the technology for single unit recordings has given the neuroscientific community theopportunity to record the spiking activity of large neuronal populations. At the same pace, statistical andmathematical tools were developed to deal with high-dimensional datasets typical of such recordings.A major line of research investigates the functional role of subsets of neurons with significant co-firingbehavior: the Hebbian cell assemblies. Here we review three linear methods for the detection of cellassemblies in large neuronal populations that rely on principal and independent component analysis.Based on their performance in spike train simulations, we propose a modified framework that incorpo-rates multiple features of these previous methods. We apply the new framework to actual single unitrecordings and show the existence of cell assemblies in the rat hippocampus, which typically oscillate attheta frequencies and couple to different phases of the underlying field rhythm

Alfabetização de crianças e jovens: superando desafios da inclusão escolar

This work has its genesis in the life of a teacher. It contemplates the report of a great story that expresses the political will of anonymous people who sought/seek to overcome challenges and prejudices, a joint effort to make real the right to literacy. The reported story was developed in the Pedagogic Clinic Teacher Heitor Carrilho, Natal-RN which, concerned about the sentence of 'unable to learn the written language' attributed to children and young public school students, decided to invest in overcoming prejudices and fight against school failure of these underprivileged. The problem that motivated the study was thus set up: What particularities characterize a pedagogical practice which aims to teach literacy to children and youth from public schools, considered not capable of learning the written language? What theoretical and methodological procedures are shown as a boost to literacy in the development of a pedagogical practice systematically targeted to reflect the perspective of educating those students in public schools? Aiming to answer these questions, we conducted a qualitative research having as methodology, Life Stories and Research/Formation. For the construction of the data, it was decided to use the participative observation, semi-structured interviews and document analysis. Guided by the principles of content analysis the data analysis was built, from which emerged two categories: theoretical and methodological procedures aligned to the major axes of literacy and Procedures of the specific theoretical and methodological fundamentals of literacy. As subsets of the transverse procedures others were seized: didactic-pedagogic procedures; social affective procedures. Regarding these ones, the research shows the importance of the teacher to build a relationship of listening to the students and their families in order to organize the pedagogical work, looking at multiple dimensions of the subject: the intellect, the creative, the affective, moral, noting that between the methodology and didactics or as part of it, the links built represent great opportunities to promote literacy. Regarding the specific procedures, others were built: procedures that emphasize oral communication, procedures that favor writing and procedures that privilege reading. Under these procedures, the results of research show that you can only promote literacy if the teacher provides the students effective conditions of understanding the principles of alphabetical notation from the use of various kinds of texts, leading them to comprehend and use them in different contexts. Therefore, instructors must meet the learners' prior knowledge, their language, and the learning real needs that will bring new challenges consistent with their possibilities. The research confirms the importance of the Educational Support extra school. However, it is essential to emphasize that it is a function of the school to promote literacy for all students in the early years of schooling. It is recorded, however, that for the implementation of this desire, we must break the school model characterized by a rigid tradition, in which there is only room for those who learn the content taught in a minimum time. Unfortunately, despite the discourse of inclusion and ensuring the right to education, the school remains exclusive and selective separating the school learning of interpersonal relations and social integration and performance. On the one hand, research showed the difficulties of conducting studies and/or strategies that address the particularities of children and young people believed not capable of learning. On the other hand, the political commitment and motivation have increased the perception that it is possible to mitigate the existing deficits in the educational context, beginning with the everyday teaching practice, in which new knowledge can be learned, methodologies can be improved and, despite everything, the educational success can be built

Sistema inteligente para diagnóstico de patologias na laringe utilizando máquinas de vetor de suporte

The human voice is an important communication tool and any disorder of the voice can have profound implications for social and professional life of an individual. Techniques of digital signal processing have been used by acoustic analysis of vocal disorders caused by pathologies in the larynx, due to its simplicity and noninvasive nature. This work deals with the acoustic analysis of voice signals affected by pathologies in the larynx, specifically, edema, and nodules on the vocal folds. The purpose of this work is to develop a classification system of voices to help pre-diagnosis of pathologies in the larynx, as well as monitoring pharmacological treatments and after surgery. Linear Prediction Coefficients (LPC), Mel Frequency cepstral coefficients (MFCC) and the coefficients obtained through the Wavelet Packet Transform (WPT) are applied to extract relevant characteristics of the voice signal. For the classification task is used the Support Vector Machine (SVM), which aims to build optimal hyperplanes that maximize the margin of separation between the classes involved. The hyperplane generated is determined by the support vectors, which are subsets of points in these classes. According to the database used in this work, the results showed a good performance, with a hit rate of 98.46% for classification of normal and pathological voices in general, and 98.75% in the classification of diseases together: edema and nodules

Otimização em comitês de classificadores: uma abordagem baseada em filtro para seleção de subconjuntos de atributos

Traditional applications of feature selection in areas such as data mining, machine learning and pattern recognition aim to improve the accuracy and to reduce the computational cost of the model. It is done through the removal of redundant, irrelevant or noisy data, finding a representative subset of data that reduces its dimensionality without loss of performance. With the development of research in ensemble of classifiers and the verification that this type of model has better performance than the individual models, if the base classifiers are diverse, comes a new field of application to the research of feature selection. In this new field, it is desired to find diverse subsets of features for the construction of base classifiers for the ensemble systems. This work proposes an approach that maximizes the diversity of the ensembles by selecting subsets of features using a model independent of the learning algorithm and with low computational cost. This is done using bio-inspired metaheuristics with evaluation filter-based criteria

Seleção de atributos em comitês de classificadores utilizando algoritmos genéticos

Classifier ensembles are systems composed of a set of individual classifiers and a combination module, which is responsible for providing the final output of the system. In the design of these systems, diversity is considered as one of the main aspects to be taken into account since there is no gain in combining identical classification methods. The ideal situation is a set of individual classifiers with uncorrelated errors. In other words, the individual classifiers should be diverse among themselves. One way of increasing diversity is to provide different datasets (patterns and/or attributes) for the individual classifiers. The diversity is increased because the individual classifiers will perform the same task (classification of the same input patterns) but they will be built using different subsets of patterns and/or attributes. The majority of the papers using feature selection for ensembles address the homogenous structures of ensemble, i.e., ensembles composed only of the same type of classifiers. In this investigation, two approaches of genetic algorithms (single and multi-objective) will be used to guide the distribution of the features among the classifiers in the context of homogenous and heterogeneous ensembles. The experiments will be divided into two phases that use a filter approach of feature selection guided by genetic algorithm

Estudoda sismicidade na região de Sobral - CE em 2008

The town of Sobral is located at the northwest part of the Ceará State, 250 km away from its capital, Fortaleza. In January 2008, an intense seismic activity began near Sobral with one event with magnitude 4,2mb on May 21. Since the start of its seismic activity, all events were recorded by the SBBR station (located on EMBRAPA Caprinos Farm), which operates in the region since August 2007. After this event, monitoring the seismic activity was carried out with the deployment of a local three component digital seismographic network, from June 5, 2008 until September 24. Initially, this network was composed of six seismographic stations. Later additional five stations were deployed until August 26 2008. This local network detected approximately 2,800 earthquakes. In this study we analyzed 581 earthquakes recorded by at least three stations for hypocentral and focal mechanism determination, and to contribute to a better explanation of the seismicity which in this region. To determine the hypocenters, we used a half-space model, with vP = 6,00 km/s and vP/vS = 1,71. From the hypocentral determination, it was revealed an active seismic zone with depth ranging between 1 and 8 km, 6 km long in E - W direction. The determination of fault planes and focal mechanism was obtained using the programs FPFIT and PLAN, which allowed comparison between their respective results in order to obtain more accurate results. A set of 24 earthquakes were selected to determine fault using PLAN planes and focal mechanisms using FPFIT. With the aid of detailed map of hypocenters this set, it was possible to identify three structures. Therefore, the set of 24 earthquakes were divided into three subsets. The type of mechanism was predominantly strike-slip with a dextral direction. Although the region has two tectonic structures near the site of the study area: the Café- Ipueiras Fault (normal fault) and the Sobral-Pedro II Lineament (dextral strike-slip fault) it was not possible to correlate the seismicity founded with those structures