Nervous Calculus

Scientists of the University of São Paulo, Brazil, integrate mathematics and neuroscience in the development of a model to explain brain functioning. Report by Paula Rothman, Info Exame, April, 2015. (in Portuguese).

A test of hypotheses for random graph distributions built from EEG data

Andressa Cerqueira, Daniel Fraiman, Claudia D. Vargas, Florencia Leonardi

The theory of random graphs is being applied in recent years to model neural interactions in the brain. While the probabilistic properties of random graphs has been extensively studied in the literature, the development of statistical inference methods for this class of objects has received less attention. In this work we propose a non-parametric test of hypotheses to test if two samples of random graphs were originated from the same probability distribution.

Goodness–of–fit tests for regression models: the functional data case

Goodness–of–fit tests for regression models: the functional data caseIn this talk the topic of the goodness–of–fit for regression models with functional covariates is considered. Although several papers have been published in the last two decades for the checking of regression models, the case where the covariates are functional is quite recent and has became of interest in the last years. We will review the very recent advances in this area and we will propose a new goodness–of–fit test for the null hypothesis of a functional linear model with scalar response. Lecturer: Wenceslao González-Manteiga, Univ. de Santiago de Compostela, Spain.

Functional Regression Analysis

Functional Regression AnalysisThe aim of this presentation is to revise the functional regression models with scalar response (Linear, Nonlinear and Semilinear) and the extension to the more general case where the response belongs to the exponential family (binomial, poisson, gamma, ...). This extension allows to develop new functional classification methods based on this regression models. Some examples along with code implementation in R are provided during the talk. Lecturer: Manuel Febrero Bande, Univ. de Santiago de Compostela, Spain.

Advances in the modelling of a system of interacting neurons

How do the membrane potentials of a set of neurons evolve across time? How may we account for influences on these membrane potentials? These questions have been at the core of the scientific agenda of the Research, Innovation and Dissemination Center for Neuromathematics (NeuroMat), that is dedicated to integrating mathematical modelling and theoretical neuroscience and is funded by the São Paulo Research Foundation (FAPESP).




The Research, Innovation and Dissemination Center for Neuromathematics is hosted by the University of São Paulo and funded by FAPESP (São Paulo Research Foundation).


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