2 resultados para Statistical maps.
em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo
Resumo:
The occurrence of white matter (WM) abnormalities in psychotic disorders has been suggested by several studies investigating brain pathology and diffusion tensor measures, but evidence assessing regional WM morphometry is still scarce and conflicting. In the present study, 122 individuals with first-episode psychosis (FEP) (62 fulfilling criteria for schizophrenia/schizophreniform disorder, 26 psychotic bipolar I disorder, and 20 psychotic major depressive disorder) underwent magnetic resonance imaging, as well as 94 epidemiologically recruited controls. Images were processed with the Statistical Parametric Mapping (SPM2) package, and voxel-based morphometry was used to compare groups (t-test) and subgroups (ANOVA). Initially, no regional WM abnormalities were observed when both groups (overall FEP group versus controls) and subgroups (i.e., schizophrenia/schizophreniform, psychotic bipolar I disorder, psychotic depression, and controls) were compared. However, when the voxelwise analyses were repeated excluding subjects with comorbid substance abuse or dependence, the resulting statistical maps revealed a focal volumetric reduction in right frontal WM, corresponding to the right middle frontal gyral WM/third subcomponent of the superior longitudinal fasciculus, in subjects with schizophrenia/schizophreniform disorder (n = 40) relative to controls (n = 89). Our results suggest that schizophrenia/schizophreniform disorder is associated with right frontal WM volume decrease at an early course of the illness. (c) 2012 Elsevier Ireland Ltd. All rights reserved.
Resumo:
We show how to construct a topological Markov map of the interval whose invariant probability measure is the stationary law of a given stochastic chain of infinite order. In particular we characterize the maps corresponding to stochastic chains with memory of variable length. The problem treated here is the converse of the classical construction of the Gibbs formalism for Markov expanding maps of the interval.