PRoNTo: pattern recognition for neuroimaging toolbox.

In the past years, mass univariate statistical analyses of neuroimaging data have been complemented by the use of multivariate pattern analyses, especially based on machine learning models. While these allow an increased sensitivity for the detection of spatially distributed effects compared to univariate techniques, they lack an established and accessible software framework. The goal of this work was to build a toolbox comprising all the necessary functionalities for multivariate analyses of neuroimaging data, based on machine learning models. The "Pattern Recognition for Neuroimaging Toolbox" (PRoNTo) is open-source, cross-platform, MATLAB-based and SPM compatible, therefore being suitable for both cognitive and clinical neuroscience research. In addition, it is designed to facilitate novel contributions from developers, aiming to improve the interaction between the neuroimaging and machine learning communities. Here, we introduce PRoNTo by presenting examples of possible research questions that can be addressed with the machine learning framework implemented in PRoNTo, and cannot be easily investigated with mass univariate statistical analysis.

EEG spike source localization before and after surgery for temporal lobe epilepsy: a BOLD EEG-fMRI and independent component analysis study

Simultaneous measurements of EEG-functional magnetic resonance imaging (fMRI) combine the high temporal resolution of EEG with the distinctive spatial resolution of fMRI. The purpose of this EEG-fMRI study was to search for hemodynamic responses (blood oxygen level-dependent - BOLD responses) associated with interictal activity in a case of right mesial temporal lobe epilepsy before and after a successful selective amygdalohippocampectomy. Therefore, the study found the epileptogenic source by this noninvasive imaging technique and compared the results after removing the atrophied hippocampus. Additionally, the present study investigated the effectiveness of two different ways of localizing epileptiform spike sources, i.e., BOLD contrast and independent component analysis dipole model, by comparing their respective outcomes to the resected epileptogenic region. Our findings suggested a right hippocampus induction of the large interictal activity in the left hemisphere. Although almost a quarter of the dipoles were found near the right hippocampus region, dipole modeling resulted in a widespread distribution, making EEG analysis too weak to precisely determine by itself the source localization even by a sophisticated method of analysis such as independent component analysis. On the other hand, the combined EEG-fMRI technique made it possible to highlight the epileptogenic foci quite efficiently.

EEG spike source localization before and after surgery for temporal lobe epilepsy: a BOLD EEG-fMRI and independent component analysis study.

Simultaneous measurements of EEG-functional magnetic resonance imaging (fMRI) combine the high temporal resolution of EEG with the distinctive spatial resolution of fMRI. The purpose of this EEG-fMRI study was to search for hemodynamic responses (blood oxygen level-dependent--BOLD responses) associated with interictal activity in a case of right mesial temporal lobe epilepsy before and after a successful selective amygdalohippocampectomy. Therefore, the study found the epileptogenic source by this noninvasive imaging technique and compared the results after removing the atrophied hippocampus. Additionally, the present study investigated the effectiveness of two different ways of localizing epileptiform spike sources, i.e., BOLD contrast and independent component analysis dipole model, by comparing their respective outcomes to the resected epileptogenic region. Our findings suggested a right hippocampus induction of the large interictal activity in the left hemisphere. Although almost a quarter of the dipoles were found near the right hippocampus region, dipole modeling resulted in a widespread distribution, making EEG analysis too weak to precisely determine by itself the source localization even by a sophisticated method of analysis such as independent component analysis. On the other hand, the combined EEG-fMRI technique made it possible to highlight the epileptogenic foci quite efficiently.

Sistema hardware de diagnostico de fibrilación ventricular en tiempo real mediante métodos de analisis tiempo-frecuencia / System hardware diagnostic of ventricular fibrillation in real time using methods of time-frequency analysis

Nowadays our society has to face different diseases related to cardiac pathologies which become more and more common. This is due to the daily life habits increasing the risk of suffering cardiac problems such as heart attack which could lead to death...