ABSTRACT
Epilepsy is one of the most common neurological disorders in the general population and affects over 50 million people worldwide. Epilepsy is characterized by the presence of spontaneous recurrent seizures as a result of sudden and abnormal electrical activity in specific areas of the cerebral cortex. However, this condition encompasses much more than simply the presence of seizures. Cognitive problems and behavioral impairments are also frequent actors, as well as mood disorders. These must be precisely described in order to develop more successful pharmacological, or even behavioral, treatments. We review some of the fundamental behavioral experimental rodent protocols that have recently been applied to the study of behavioral impairments in epilepsy, particularly in epilepsy modeled by different chemoconvulsants, such as pilocarpine or kainic acid. These experimental protocols are classified into two categories: Tests designed for studying emotional factors, and those designed for studying cognitive impairments and social behavior. Behavioral impairments and adaptations identified by the use of these procedures are described.
Subject(s)
Convulsants/toxicity , Epilepsy/chemically induced , Epilepsy/complications , Mental Disorders/etiology , Animals , Disease Models, Animal , HumansABSTRACT
The estimation of current distributions from electroencephalographic recordings poses an inverse problem, which can approximately be solved by including dynamical models as spatio-temporal constraints onto the solution. In this paper, we consider the electrocardiography source localization task, where a specific structure for the dynamical model of current distribution is directly obtained from the data by fitting multivariate autoregressive models to electroencephalographic time series. Whereas previous approaches consider an approximation of the internal connectivity of the sources, the proposed methodology takes into account a realistic structure of the model estimated from the data, such that it becomes possible to obtain improved inverse solutions. The performance of the new method is demonstrated by application to simulated electroencephalographic data over several signal to noise ratios, where the source localization task is evaluated by using the localization error and the data fit error. Finally, it is shown that estimating MVAR models makes possible to obtain inverse solutions of considerably improved quality, as compared to the usual instantaneous inverse solutions, even if the regularized inverse of Tikhonov is used.
Subject(s)
Electroencephalography/methods , Signal Processing, Computer-Assisted , Algorithms , Brain/pathology , Computer Simulation , Finite Element Analysis , Humans , Imaging, Three-Dimensional , Linear Models , Models, Statistical , Multivariate Analysis , Regression Analysis , Reproducibility of Results , Signal-To-Noise Ratio , Time FactorsABSTRACT
El reflujo gastroesofagico (RGE) es una de las entidades patologicas más frecuentes en la consulta medica general. Por lo tanto, el conocimiento de la entidad corresponde a todo aquel que tenga que ver con la profesion medica. Clinicamente pueden distinguirse dos tipos de RGE: fisiologico y patologico. La presente revision pretende analizar el manejo que actualmente se propone para el RGE de tipo patologico, haciendo enfasis en los metodos diagnosticos principales y en las alternativas quirurgicas de manejo.
