OBJECTIVE The purpose of this study was to explore the relationship between lesion location and poststroke depression using statistical parametric mapping. METHODS First episode patients with stroke were assessed within 12 days and at 1-month poststroke. Patients with an a priori defined cut-off score of 11 on the Hospital Anxiety and Depression Scale (HADS) at follow-up were further assessed...

This paper proposes a rating methodology that is based on a non-linear classification method, the support vector machine, and a non-parametric technique for mapping rating scores into probabilities of default. We give an introduction to underlying statistical models and represent the results of testing our approach on Deutsche Bundesbank data. In particular we discuss the selection of variables...

In last years, many research efforts in neurosciences have focused in multivariate approaches based on machine learning as an alternative to the use of Statistical Parametric Mapping and the univariate analyses that it provides. However, this relatively new field still lacks of a software framework that completely meets the needs of the scientific community. In this work we present a toolbox de...

Neuroimaging studies have reported greater activation of the human amygdala in response to emotional facial expressions, especially for fear. However, little is known about how fast this activation occurs. We investigated this issue by recording the intracranial field potentials of the amygdala in subjects undergoing pre-neurosurgical assessment (n=6). The subjects observed fearful, happy, and ...

Voxel based analyses (VBA), also known as Statistical Parametric Mapping (SPM), are commonly used for exploratory analysis of functional or structural neuroimaging data. The popular technique is relatively easy to use and can survey the entire brain but the method yields inconsistent results (Kanaan 2005). It is difficult to challenge the validity of published works and review submissions becau...

A Gabor wavelets based method is proposed in this paper for evaluating and tuning the parameters of image registration algorithms. The registration quality is measured by the anatomical variability of the registered images. We propose in this paper a local anatomical structure descriptor, namely the Maximum Responded Gabor Wavelet (MRGW) for such a purpose. The effectiveness of the descriptor i...

An overview of computational procedures for examining neuroanatomical variability is presented. The review focuses on approaches that can be applied using the SPM software package, beginning by explaining briefly how statistical parametric mapping is usually applied to functional imaging data. The review then proceeds to discuss volumetry, with an emphasis on voxel-based morphometry, and the pr...

A Gabor wavelets based method is proposed in this paper for evaluating and tuning the parameters of image registration algorithms. We propose a 3D local anatomical structure descriptor, namely the Maximum Responded Gabor Wavelet (MRGW), for measuring registration quality based on anatomical variability of registered images. The effectiveness of the descriptor is demonstrated through a practical...