Coleção de Artigos Acadêmicos
URI permanente para esta coleçãohttps://repositorio.insper.edu.br/handle/11224/3227
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186 resultados
Resultados da Pesquisa
Artigo Científico A Statistical Method to Distinguish Functional Brain Networks(2017) Fujita, André; MACIEL CALEBE VIDAL; Takahashi, Daniel Y.One major problem in neuroscience is the comparison of functional brain networks of different populations, e.g., distinguishing the networks of controls and patients. Traditional algorithms are based on search for isomorphism between networks, assuming that they are deterministic. However, biological networks present randomness that cannot be well modeled by those algorithms. For instance, functional brain networks of distinct subjects of the same population can be different due to individual characteristics. Moreover, networks of subjects from different populations can be generated through the same stochastic process. Thus, a better hypothesis is that networks are generated by random processes. In this case, subjects from the same group are samples from the same random process, whereas subjects from different groups are generated by distinct processes. Using this idea, we developed a statistical test called ANOGVA to test whether two or more populations of graphs are generated by the same random graph model. Our simulations' results demonstrate that we can precisely control the rate of false positives and that the test is powerful to discriminate random graphs generated by different models and parameters. The method also showed to be robust for unbalanced data. As an example, we applied ANOGVA to an fMRI dataset composed of controls and patients diagnosed with autism or Asperger. ANOGVA identified the cerebellar functional sub-network as statistically different between controls and autism (p < 0.001).Artigo Científico Direitos Humanos, inteligência artificial e privacidade(2019) Cassino, João Francisco; RODOLFO DA SILVA AVELINO; Silveira, Sérgio Amadeu daEste texto trata dos riscos e implicações da inteligência artificial e dos algoritmos para os objetivos contidos na Declaração Universal dos Direitos Humanos. Nesse sentido, as perspectivas de James Der Derian, Frank Pasquale, David Chandler, Shoshana Zuboff, Philip N. Howard e Nick Srnicek foram mobilizadas para a compreensão da atual fase do capitalismo global, do mercado de captura e o processamento em massa de dados pessoais. Diversos casos descritos indicam que a privacidade é cada vez menos respeitada enquanto as empresas protegem seus segredos competitivos com patentes, códigos fechados e acordos de confidencialidade. Técnicas de Big Data e algoritmos em rede podem ser utilizados para melhorar e agilizar a administração pública, mas também resultam em novas práticas discriminatórias que violam o direito à privacidade, à liberdade de expressão e à justiça. Grupos étnicos e raciais, mulheres e comunidade LGBT já sofrem com decisões tomadas por sistemas computacionais autômatos que levam à segregação e ao preconceito.Artigo Científico An investigation of the distribution of gaze estimation errors in head mounted gaze trackers using polynomial functions(2018) Mardanbegi, Diako; ANDREW TOSHIAKI NAKAYAMA KURAUCHI; Morimoto, Carlos H.Second order polynomials are commonly used for estimating the point-of-gaze in head-mounted eye trackers. Studies in remote (desktop) eye trackers show that although some non-standard 3rd order polynomial models could provide better accuracy, high-order polynomials do not necessarily provide better results. Different than remote setups though, where gaze is estimated over a relatively narrow field-of-view surface (e.g. less than 30x20 degrees on typical computer displays), head-mounted gaze trackers (HMGT) are often desired to cover a relatively wider field-of-view to make sure that the gaze is detected in the scene image even for extreme eye angles. In this paper we investigate the behavior of the gaze estimation error distribution throughout the image of the scene camera when using polynomial functions. Using simulated scenarios, we describe effects of four different sources of error: interpolation, extrapolation, parallax, and radial distortion. We show that the use of third order polynomials result in more accurate gaze estimates in HMGT, and that the use of wide angle lenses might be beneficial in terms of error reduction.Artigo Científico Correlation between graphs with an application to brain network analysis(2017) Fujita, André; Takahashi, Daniel Yasumasa; Balardin, Joana Bisol; MACIEL CALEBE VIDAL; Sato, João RicardoThe global functional brain network (graph) is more suitable for characterizing brain states than local analysis of the connectivity of brain regions. Therefore, graph-theoretic approaches are natural methods to use for studying the brain. However, conventional graph theoretical analyses are limited due to the lack of formal statistical methods of estimation and inference. For example, the concept of correlation between two vectors of graphs has not yet been defined. Thus, the introduction of a notion of correlation between graphs becomes necessary to better understand how brain sub-networks interact. To develop a framework to infer correlation between graphs, one may assume that they are generated by models and that the parameters of the models are the random variables. Then, it is possible to define that two graphs are independent when the random variables representing their parameters are independent. In the real world, however, the model is rarely known, and consequently, the parameters cannot be estimated. By analyzing the graph spectrum, it is shown that the spectral radius is highly associated with the parameters of the graph model. Based on this, a framework for correlation inference between graphs is constructed and the approach illustrated on functional magnetic resonance imaging data on 814 subjects comprising 529 controls and 285 individuals diagnosed with autism spectrum disorder (ASD). Results show that correlations between the default-mode and control, default-mode and somatomotor, and default-mode and visual sub-networks are higher in individuals with ASD than in the controls.Artigo Científico A Software to Compare Clusters between Groups and Its Application to the Study of Autism Spectrum Disorder(2017) MACIEL CALEBE VIDAL; Sato, João R.; Balardin, Joana B.; Takahashi, Daniel Y.; Fujita, AndréUnderstanding how brain activities cluster can help in the diagnosis of neuropsychological disorders. Thus, it is important to be able to identify alterations in the clustering structure of functional brain networks. Here, we provide an R implementation of Analysis of Cluster Variability (ANOCVA), which statistically tests (1) whether a set of brain regions of interest (ROI) are equally clustered between two or more populations and (2) whether the contribution of each ROI to the differences in clustering is significant. To illustrate the usefulness of our method and software, we apply the R package in a large functional magnetic resonance imaging (fMRI) dataset composed of 896 individuals (529 controls and 285 diagnosed with ASD—autism spectrum disorder) collected by the ABIDE (The Autism Brain Imaging Data Exchange) Consortium. Our analysis show that the clustering structure of controls and ASD subjects are different (p < 0.001) and that specific brain regions distributed in the frontotemporal, sensorimotor, visual, cerebellar, and brainstem systems significantly contributed (p < 0.05) to this differential clustering. These findings suggest an atypical organization of domain-specific functionbrain modules in ASD.Artigo Científico Identification of alterations associated with age in the clustering structure of functional brain networks(2018) Guzman, Grover E. C.; Sato, Joao R.; MACIEL CALEBE VIDAL; Fujita, AndreInitial studies using resting-state functional magnetic resonance imaging on the trajectories of the brain network from childhood to adulthood found evidence of functional integration and segregation over time. The comprehension of how healthy individuals’ functional integration and segregation occur is crucial to enhance our understanding of possible deviations that may lead to brain disorders. Recent approaches have focused on the framework wherein the functional brain network is organized into spatially distributed modules that have been associated with specific cognitive functions. Here, we tested the hypothesis that the clustering structure of brain networks evolves during development. To address this hypothesis, we defined a measure of how well a brain region is clustered (network fitness index), and developed a method to evaluate its association with age. Then, we applied this method to a functional magnetic resonance imaging data set composed of 397 males under 31 years of age collected as part of the Autism Brain Imaging Data Exchange Consortium. As results, we identified two brain regions for which the clustering change over time, namely, the left middle temporal gyrus and the left putamen. Since the network fitness index is associated with both integration and segregation, our finding suggests that the identified brain region plays a role in the development of brain systems.Artigo Científico Particle learning for Bayesian semi-parametric stochasticvolatility model(2019) Virbickaitė, Audronė; HEDIBERT FREITAS LOPES; Ausín, M. Concepción; Galeano, PedroThis article designs a Sequential Monte Carlo (SMC) algorithm for estimation of Bayesian semi-parametric Stochastic Volatility model for financial data. In particular, it makes use of one of the most recent particle filters called Particle Learning (PL). SMC methods are especially well suited for state-space models and can be seen as a cost-efficient alternative to Markov Chain Monte Carlo (MCMC), since they allow for online type inference. The posterior distributions are updated as new data is observed, which is exceedingly costly using MCMC. Also, PL allows for consistent online model comparison using sequential predictive log Bayes factors. A simulated data is used in order to compare the posterior outputs for the PL and MCMC schemes, which are shown to be almost identical. Finally, a short real data application is included.Artigo Científico On the Long-Run Volatility of Stocks(2018) Carvalho, Carlos M.; HEDIBERT FREITAS LOPES; McCulloch, Robert E.In this article, we investigate whether or not the volatility per period of stocks is lower over longer horizons.Taking the perspective of an investor, we evaluate the predictive variance of k-period returns under differentmodel and prior specifications. We adopt the state-space framework of Pástor and Stambaugh to model thedynamics of expected returns and evaluate the effects of prior elicitation in the resulting volatility estimates.Part of the developments includes an extension that incorporates time-varying volatilities and covariancesin a constrained prior information set-up. Our conclusion for the U.S. market, under plausible prior specifi-cations, is that stocks are less volatile in the long run. Model assessment exercises demonstrate the modelsand priors supporting our main conclusions are in accordance with the data. To assess the generality of theresults, we extend our analysis to a number of international equity indices. Supplementary materials for thisarticle are available online.Artigo Científico Walk on the Wild Side: Temporarily Unstable Paths and Multiplicative Sunspots(2019) Ascari, Guido; Bonomolo, Paolo; HEDIBERT FREITAS LOPESWe propose a generalization of the rational expectations framework to allow for temporarily unstable paths. Our approach introduces multiplicative sunspot shocks and it yields drifting parameters and stochastic volatility. Then, we provide an econometric strategy to estimate this generalized model on the data. The methodology allows the data to choose between different possible alternatives: determinacy, indeterminacy, and temporary instability. We apply our methodology to US inflation dynamics in the 1970s through the lens of a simple New Keynesian model. When temporarily unstable paths are allowed, the data unambiguously select them to explain the stagflation period in the 1970s.- Sham Litigation e Garantias Fundamentais do Processo: Três Breves Perguntas (Ou Reflexões)(2019) Osna, Gustavo; Renzetti, Bruno Polonio